stem topics for research quantitative

199+ Best Quantitative Research Topics for STEM Students 2024

Dive into a world of quantitative research topics for STEM students! It’s all about unveiling the secrets of biology, decoding the language of particles, and taking a data-driven ride into the unknown.

Ready for a deep dive into the quantitative wonders of Science, Technology, Engineering, and Math? Our “Quantitative Research Topics for STEM Students” lineup is like a playground for your curious minds.

Imagine it as a buffet of cool ideas waiting for your unique spin. Whether you love crunching numbers to reveal data mysteries or untangling relationships between different things, these topics are your VIP pass to the science party!

So, grab a seat, gear up that brainpower, and let’s turn STEM research into an adventure. Picture these ideas as your scientific rollercoaster – twists, turns, and maybe even a couple of “aha!” moments. Let the quantitative fun kick-off!

Table of Contents

The Importance of Quantitative Research in STEM

Check out the importance of quantitative research in STEM:-

Testing Ideas : It helps us check if our guesses are right.
Spotting Trends : Shows us patterns in data, making discoveries easier.
Measuring Stuff : Lets us measure things accurately for comparing solutions.
Making Big Claims : Helps us say if our findings apply to lots of situations.
Being Fair : Makes sure our findings are true and not just what we hope for.
Teamwork : Easy for lots of researchers to work together and build on each other’s work.

In different STEM areas

Medicine : Checks if new medicines or treatments really work and are safe.
Technology : Tests which designs or features work best in apps and websites.
Engineering : Helps test materials, design efficiently, and keep projects safe.

While we also like qualitative research for exploring experiences, quantitative research is the foundation of solid knowledge in STEM.

How do you choose a research topic in STEM?

Choosing the perfect quantitative research topic is like embarking on a thrilling adventure – it’s all about excitement, challenges, and finding something that truly lights up your STEM-loving heart. So, let’s dive into the wild ride of “Choosing the Right Quantitative Research Topic.”

Choosing the Right Quantitative Research Topic

Follow Your STEM Heartbeat

First things first, what makes your STEM-loving heart race? Is it the allure of cracking genetic codes or navigating the intricate world of algorithms? Choose a topic that makes you go, “Wow, I want to know more!”

Venture into the Unknown

Don’t fear the unknown; embrace it! The most fascinating questions often lurk in uncharted territories. Think of your research topic as a treasure waiting to be discovered in the vast landscape of STEM.

Map Out the Data Terrain

A good adventure needs a map, right? Similarly, ensure there’s enough data to guide you. Having solid and accessible data turns your research journey into a well-prepared expedition.

Keep It Practical

Consider the practical side. Can you realistically embark on experiments, gather data, or dive into analyses within your available resources and timeframe? Let’s keep this adventure doable!

Hunt for Research Gaps

Explore the landscape of existing research. Are there areas where quantitative exploration is scarce? Becoming a gap-filler not only makes you a research superhero but also adds a unique twist to your journey.

Get Inspired

Think of reading research papers and attending seminars as your STEM version of gathering allies for your quest. Surround yourself with inspiration – it’s like finding magical artifacts for your research toolkit.

Seek Wisdom from the Wise

Wise mentors, professors, or seasoned experts are like the Gandalfs of your STEM journey. Seek their counsel. They’ve been through quests and can guide you with their sage advice.

Real-World Impact Check

Consider the real-world impact of your research. How can your findings make a dent in solving problems or pushing the boundaries of knowledge in your STEM realm? It’s like giving your research a superhero cape!

Match Your Skills with Your Quest

Choose a topic that aligns with your skills and strengths. Think of it as selecting a character for a video game – you want one that matches your style and abilities for a victorious and enjoyable quest.

Remember, your quantitative research topic isn’t just a research project – it’s your personal STEM expedition, waiting for your unique exploration and discovery. Let the adventure begin!

Quantitative Research Topics for STEM Students

Check out quantitative research topics in physics:-

Temperature’s effect on enzyme activity.
pH levels and plant growth.
Pollution’s impact on aquatic life.
Solar radiation and crop yield.
Sunscreen effectiveness.
Caffeine intake and heart rate.
Fertilizers’ effects on plants.
Bacterial growth in environments.
Ocean acidification and coral reefs.
Exercise and metabolism.
File compression algorithm testing.
Cloud computing’s data storage.
Cybersecurity measures’ effectiveness.
Renewable energy sources’ output.
Facial recognition accuracy.
Programming language performance.
Computer hardware reliability.
AI’s job automation impact.
Routing algorithms in networks.
Machine learning in stock prediction.

Engineering

Water filtration system efficiency.
Building stability during earthquakes.
Car design’s aerodynamics.
Transportation systems’ energy.
Bridge fatigue under traffic.
Metal tensile strength and temperature.
Electronic device cooling efficiency.
Material composition and heat.
Wind turbine performance.
Wastewater treatment methods.

Mathematics

Prime number distribution.
Math aptitude’s impact.
Teaching methods in math.
Socioeconomic factors and math.
Math in cryptography.
Math modeling in reality.
Optimization algorithms’ efficiency.
Geometry in architecture.
Equation-solving algorithms.
Math research in tech.

Environment

Deforestation and biodiversity.
Air pollution and health.
Recycling methods’ impact.
Temperature rise and sea levels.
Agricultural practices and erosion.
Carbon capture technology.
Ocean temperature and reefs.
Plastic pollution’s impact.
Reforestation’s climate effect.
Urbanization and heat islands.
Vaccine effectiveness.
Diet and heart health.
Sleep duration and cognition.
Exercise and weight loss.
Genetics and disease.
Drug treatments’ efficacy.
Mindfulness meditation and stress.
Socioeconomic status and healthcare.
Rehabilitation programs’ impact.
Mass and gravity.
Space propulsion systems.
Magnetic fields and particles.
Temperature and conductivity.
Energy conversion methods.
Light intensity and photoelectric effect.
Soundproofing materials.
Surface tension and viscosity.
Friction’s impact on motion.
Solar cell efficiency.
Catalysts in reactions.
pH levels and reactions.
Temperature and reaction rate.
Concentration and equilibrium.
Solvent effectiveness.
Molecular structure and properties.
Purification techniques’ efficiency.
Pressure and gas solubility.
Corrosion inhibitors’ effectiveness.
Oxidation-reduction reactions.
Antibiotics’ effectiveness.
Nutrients and plant growth.
Environment and animal behavior.
Cell preservation methods.
Hormones and physiology.
Gene editing techniques.
Biodiversity and stability.
Climate change’s species impact.
Invasive species control.
Telescope efficiency.
Stellar mass and luminosity.
Planetary orbits and gravity.
Cosmic radiation’s impact.
Solar flare prediction.
Galaxy morphology and stars.
Interstellar travel efficiency.
Dark matter’s impact.
Cosmic expansion’s background.
Exoplanet detection methods.

Environmental Engineering

Wastewater treatment efficiency.
Soil erosion control methods.
Green infrastructure in cities.
Land use changes’ water quality.
Agricultural runoff’s impact.
Coastal erosion control.
Air pollution control.
Renewable energy’s emissions.
Climate change’s resilience.
Ecosystem restoration efforts.

Data Science

Weather pattern prediction accuracy.
Data volume and processing.
Data quality and models.
Feature selection impact.
Anomaly detection in cybersecurity.
Data preprocessing methods.
Clustering algorithms’ efficiency.
Sampling techniques’ impact.
Ensemble learning effectiveness.
Data visualization’s role.
Teaching strategies’ math impact.
Student engagement and performance.
Classroom technology and learning.
Teacher development’s impact.
Peer tutoring effectiveness.
Homework’s academic impact.
Early education and development.
Parental involvement’s role.
Personalized learning impact.
School climate and well-being.
Therapy’s anxiety impact.
Sleep quality’s mental health impact.
Personality and academic success.
Mindfulness’s stress reduction.
Reinforcement in behavior.
Social media and mental health.
Parental attachment’s role.
Phobia treatment’s effectiveness.
Psychoeducation in stigma.
Resilience and coping strategies.
Social support and mental health.
Media’s social issue impact.
Neighborhoods and crime.
Diversity and workplace productivity.
Community policing’s impact.
Family structure and education.
Income inequality’s effects.
Gender stereotypes and careers.
Social media and relationships.
Fiscal policy and growth.
Inflation and spending.
Unemployment and poverty.
Trade agreements’ impact.
Monetary policy’s effect.
Government spending and inequality.
Interest rates and investment.
Exchange rates’ impact.
Globalization and income.
Poverty alleviation’s impact.
Customer satisfaction and loyalty.
Motivation and performance.
CSR and consumer behavior.
Leadership styles’ impact.
Supply chain disruptions’ impact.
Marketing strategies’ effectiveness.
Diversity and team performance.
Engagement and turnover.
Innovation and competitiveness.
Financial performance and value.

Political Science

Electoral systems’ representation.
Campaign spending and outcomes.
Ideology and policies.
Media bias and opinion.
Lobbying’s impact.
Voter turnout and demographics.
Transparency and trust.
Foreign aid’s impact.
Conflict resolution’s effectiveness.
Polarization and gridlock.
Urbanization’s impact.
Climate change and disasters.
Population density and resources.
Land degradation and desertification.
Conservation’s impact.
Water scarcity and conflict.
Land tenure and agriculture.
Sea level rise’s impact.
Sustainable development’s role.

Anthropology

Cultural assimilation’s impact.
Migration patterns’ influence.
Language diversity and preservation.
Globalization’s effects.
Cultural heritage preservation.
Gender roles’ impact.
Religion and social cohesion.
Colonialism’s legacy.
Multicultural education’s impact.
Identity and integration.

These concise research topics offer a quick overview of potential quantitative research projects across various STEM disciplines.

What are the best topics for quantitative research for STEM?

Picking the right quantitative research topic in STEM depends on your interests and expertise. Here are some ideas to spark your curiosity:

Natural Sciences

Environmental science.

How pollutants affect air or water quality.
Impact of conservation efforts on wildlife .
Climate change’s link to extreme weather.
Medications’ influence on biological markers.
Genetics and susceptibility to diseases.
Effects of different fertilizers on plant growth.
Mass and acceleration relationships.
Material conductivity for heat or electricity.
Solar panel efficiency in converting sunlight.
Catalysts’ effect on speeding reactions.
Properties of newly synthesized materials.
Chemical reaction rates under different conditions.

Technology and Engineering

Computer science.

Machine learning algorithms for image recognition.
Network congestion’s impact on data speed.
Memory cache sizes and processing speed.
Fuel types’ efficiency for engines.
Material properties and structural integrity.
Bridge design and load capacity.
Predicting stock market trends with models.
Voting systems’ impact on elections.
Geometric shapes and physical properties.

Consider these tips when choosing

Interests: Pick something that excites you.
Data: Make sure you can access relevant information.
Feasibility: Ensure your research fits your timeframe and resources.
Originality: Aim for a fresh perspective.

Remember, these are just starting points! Chat with professors or professionals to refine your topic and dive into your quantitative research journey.

What is the best topic for quantitative research?

Measurable Variables: Pick a topic where you can easily measure things with numbers.
Clear Question: Make sure your topic has a specific question you can answer with data.
Data Access: Think about how you’ll get the data you need.
Originality and Importance: Look for something new or interesting to study, and consider how it might help people or add to what we already know.

Here’s a simple plan

Find Your Passion: Start with what you love in science, tech, or math.
Check What’s Out There: Read some articles in your area to see what’s already been done.
Narrow it Down: Come up with a specific question to study.

And some examples

Does online homework help students learn math?
How does social media affect teenagers’ anxiety?
Do public health campaigns get more people vaccinated?
How does water temperature affect fish growth?
Is there a connection between happy customers and business profits?

Remember, the best topic for you is one that gets you excited and lets you learn something new!

How can you apply quantitative research in STEM?

Quantitative research rocks in STEM (Science, Technology, Engineering, and Mathematics), giving us precise data. Here’s how it rolls:

Understanding Nature

In Biology, measure how fertilizers affect plant growth or how meds impact cells. Then, find patterns in the data. In Physics, test solar panel efficiency or Newton’s Laws with masses.

Use data to confirm or challenge theories. In Environmental Science, survey public opinions on environmental issues and track pollution levels to find sources.

Testing Theories

In Chemistry, hypothesize about chemical reaction rates under different temps. Test it, then analyze results. In Engineering, simulate bridge stresses to see how they hold up.

Use data to improve designs. In Technology, create and test machine learning algorithms for image recognition. Analyze for accuracy.

Making Predictions

In Mathematics, model population growth or city traffic flow using historical data. Check if predictions match reality. In Computer Science, analyze stock market data for patterns and create models for investment insights.

Enhancing Analysis

In Astronomy, gather loads of data on stars. Analyze it statistically to uncover cosmic insights. In Medicine, run large-scale trials on new meds. Analyze data to measure effectiveness and side effects.

Pair quantitative with qualitative research for a fuller picture.
Solid design and analysis are crucial for reliable results.
Ethical practices matter—get consent and protect privacy.
Mastering quantitative research opens doors in STEM, unveiling new knowledge and solutions.

Alright, let’s sum it up! Quantitative research is like going on a cool adventure for STEM students. You dive into data, analyze it, and find all sorts of interesting stuff.

With quantitative methods, you can solve big problems, learn heaps, and actually make a difference. Whether you’re exploring nature, testing out theories, predicting what comes next, or just making things run smoother, there’s so much you can do.

So, dive in, stay curious, and let quantitative research be your trusty guide in the amazing world of STEM!

Frequently Asked Questions (FAQs)

Are there specific resources for stem students engaging in quantitative research.

Yes, there are specialized software tools, academic journals, and online platforms dedicated to quantitative research in STEM. Explore these resources for comprehensive support.

How can I overcome common pitfalls in quantitative research?

Mitigating pitfalls involves thorough planning, robust methodology, and staying aware of potential biases. Learning from the experiences of others can also be invaluable.

Top 300+ Qualitative Research Topics For High School Students

100+ Most Interesting Google Scholar Research Topics For Students [Updated 2024]

200+ Experimental Quantitative Research Topics For STEM Students In 2023

STEM means Science, Technology, Engineering, and Math, which is not the only stuff we learn in school. It is like a treasure chest of skills that help students become great problem solvers, ready to tackle the real world’s challenges.

In this blog, we are here to explore the world of Research Topics for STEM Students. We will break down what STEM really means and why it is so important for students. In addition, we will give you the lowdown on how to pick a fascinating research topic. We will explain a list of 200+ Experimental Quantitative Research Topics For STEM Students.

And when it comes to writing a research title, we will guide you step by step. So, stay with us as we unlock the exciting world of STEM research – it is not just about grades; it is about growing smarter, more confident, and happier along the way.

What Is STEM?

Table of Contents

STEM is Science, Technology, Engineering, and Mathematics. It is a way of talking about things like learning, jobs, and activities related to these four important subjects. Science is about understanding the world around us, technology is about using tools and machines to solve problems, engineering is about designing and building things, and mathematics is about numbers and solving problems with them. STEM helps us explore, discover, and create cool stuff that makes our world better and more exciting.

Why STEM Research Is Important?

STEM research is important because it helps us learn new things about the world and solve problems. When scientists, engineers, and mathematicians study these subjects, they can discover cures for diseases, create new technology that makes life easier, and build things that help us live better. It is like a big puzzle where we put together pieces of knowledge to make our world safer, healthier, and more fun.

STEM research leads to new discoveries and solutions.
It helps find cures for diseases.
STEM technology makes life easier.
Engineers build things that improve our lives.
Mathematics helps us understand and solve complex problems.

How to Choose a Topic for STEM Research Paper

Here are some steps to choose a topic for STEM Research Paper:

Step 1: Identify Your Interests

Think about what you like and what excites you in science, technology, engineering, or math. It could be something you learned in school, saw in the news, or experienced in your daily life. Choosing a topic you’re passionate about makes the research process more enjoyable.

Step 2: Research Existing Topics

Look up different STEM research areas online, in books, or at your library. See what scientists and experts are studying. This can give you ideas and help you understand what’s already known in your chosen field.

Step 3: Consider Real-World Problems

Think about the problems you see around you. Are there issues in your community or the world that STEM can help solve? Choosing a topic that addresses a real-world problem can make your research impactful.

Step 4: Talk to Teachers and Mentors

Discuss your interests with your teachers, professors, or mentors. They can offer guidance and suggest topics that align with your skills and goals. They may also provide resources and support for your research.

Step 5: Narrow Down Your Topic

Once you have some ideas, narrow them down to a specific research question or project. Make sure it’s not too broad or too narrow. You want a topic that you can explore in depth within the scope of your research paper.

Here we will discuss 200+ Experimental Quantitative Research Topics For STEM Students:

Qualitative Research Topics for STEM Students:

Qualitative research focuses on exploring and understanding phenomena through non-numerical data and subjective experiences. Here are 10 qualitative research topics for STEM students:

Exploring the experiences of female STEM students in overcoming gender bias in academia.
Understanding the perceptions of teachers regarding the integration of technology in STEM education.
Investigating the motivations and challenges of STEM educators in underprivileged schools.
Exploring the attitudes and beliefs of parents towards STEM education for their children.
Analyzing the impact of collaborative learning on student engagement in STEM subjects.
Investigating the experiences of STEM professionals in bridging the gap between academia and industry.
Understanding the cultural factors influencing STEM career choices among minority students.
Exploring the role of mentorship in the career development of STEM graduates.
Analyzing the perceptions of students towards the ethics of emerging STEM technologies like AI and CRISPR.
Investigating the emotional well-being and stress levels of STEM students during their academic journey.

Easy Experimental Research Topics for STEM Students:

These experimental research topics are relatively straightforward and suitable for STEM students who are new to research:

Measuring the effect of different light wavelengths on plant growth.
Investigating the relationship between exercise and heart rate in various age groups.
Testing the effectiveness of different insulating materials in conserving heat.
Examining the impact of pH levels on the rate of chemical reactions.
Studying the behavior of magnets in different temperature conditions.
Investigating the effect of different concentrations of a substance on bacterial growth.
Testing the efficiency of various sunscreen brands in blocking UV radiation.
Measuring the impact of music genres on concentration and productivity.
Examining the correlation between the angle of a ramp and the speed of a rolling object.
Investigating the relationship between the number of blades on a wind turbine and energy output.

Research Topics for STEM Students in the Philippines:

These research topics are tailored for STEM students in the Philippines:

Assessing the impact of climate change on the biodiversity of coral reefs in the Philippines.
Studying the potential of indigenous plants in the Philippines for medicinal purposes.
Investigating the feasibility of harnessing renewable energy sources like solar and wind in rural Filipino communities.
Analyzing the water quality and pollution levels in major rivers and lakes in the Philippines.
Exploring sustainable agricultural practices for small-scale farmers in the Philippines.
Assessing the prevalence and impact of dengue fever outbreaks in urban areas of the Philippines.
Investigating the challenges and opportunities of STEM education in remote Filipino islands.
Studying the impact of typhoons and natural disasters on infrastructure resilience in the Philippines.
Analyzing the genetic diversity of endemic species in the Philippine rainforests.
Assessing the effectiveness of disaster preparedness programs in Philippine communities.

Frontend Project Ideas
Business Intelligence Projects For Beginners

Good Research Topics for STEM Students:

These research topics are considered good because they offer interesting avenues for investigation and learning:

Developing a low-cost and efficient water purification system for rural communities.
Investigating the potential use of CRISPR-Cas9 for gene therapy in genetic disorders.
Studying the applications of blockchain technology in securing medical records.
Analyzing the impact of 3D printing on customized prosthetics for amputees.
Exploring the use of artificial intelligence in predicting and preventing forest fires.
Investigating the effects of microplastic pollution on aquatic ecosystems.
Analyzing the use of drones in monitoring and managing agricultural crops.
Studying the potential of quantum computing in solving complex optimization problems.
Investigating the development of biodegradable materials for sustainable packaging.
Exploring the ethical implications of gene editing in humans.

Unique Research Topics for STEM Students:

Unique research topics can provide STEM students with the opportunity to explore unconventional and innovative ideas. Here are 10 unique research topics for STEM students:

Investigating the use of bioluminescent organisms for sustainable lighting solutions.
Studying the potential of using spider silk proteins for advanced materials in engineering.
Exploring the application of quantum entanglement for secure communication in the field of cryptography.
Analyzing the feasibility of harnessing geothermal energy from underwater volcanoes.
Investigating the use of CRISPR-Cas12 for rapid and cost-effective disease diagnostics.
Studying the interaction between artificial intelligence and human creativity in art and music generation.
Exploring the development of edible packaging materials to reduce plastic waste.
Investigating the impact of microgravity on cellular behavior and tissue regeneration in space.
Analyzing the potential of using sound waves to detect and combat invasive species in aquatic ecosystems.
Studying the use of biotechnology in reviving extinct species, such as the woolly mammoth.

Experimental Research Topics for STEM Students in the Philippines

Research topics for STEM students in the Philippines can address specific regional challenges and opportunities. Here are 10 experimental research topics for STEM students in the Philippines:

Assessing the effectiveness of locally sourced materials for disaster-resilient housing construction in typhoon-prone areas.
Investigating the utilization of indigenous plants for natural remedies in Filipino traditional medicine.
Studying the impact of volcanic soil on crop growth and agriculture in volcanic regions of the Philippines.
Analyzing the water quality and purification methods in remote island communities.
Exploring the feasibility of using bamboo as a sustainable construction material in the Philippines.
Investigating the potential of using solar stills for freshwater production in water-scarce regions.
Studying the effects of climate change on the migration patterns of bird species in the Philippines.
Analyzing the growth and sustainability of coral reefs in marine protected areas.
Investigating the utilization of coconut waste for biofuel production.
Studying the biodiversity and conservation efforts in the Tubbataha Reefs Natural Park.

Capstone Research Topics for STEM Students in the Philippines:

Capstone research projects are often more comprehensive and can address real-world issues. Here are 10 capstone research topics for STEM students in the Philippines:

Designing a low-cost and sustainable sanitation system for informal settlements in urban Manila.
Developing a mobile app for monitoring and reporting natural disasters in the Philippines.
Assessing the impact of climate change on the availability and quality of drinking water in Philippine cities.
Designing an efficient traffic management system to address congestion in major Filipino cities.
Analyzing the health implications of air pollution in densely populated urban areas of the Philippines.
Developing a renewable energy microgrid for off-grid communities in the archipelago.
Assessing the feasibility of using unmanned aerial vehicles (drones) for agricultural monitoring in rural Philippines.
Designing a low-cost and sustainable aquaponics system for urban agriculture.
Investigating the potential of vertical farming to address food security in densely populated urban areas.
Developing a disaster-resilient housing prototype suitable for typhoon-prone regions.

Experimental Quantitative Research Topics for STEM Students:

Experimental quantitative research involves the collection and analysis of numerical data to conclude. Here are 10 Experimental Quantitative Research Topics For STEM Students interested in experimental quantitative research:

Examining the impact of different fertilizers on crop yield in agriculture.
Investigating the relationship between exercise and heart rate among different age groups.
Analyzing the effect of varying light intensities on photosynthesis in plants.
Studying the efficiency of various insulation materials in reducing building heat loss.
Investigating the relationship between pH levels and the rate of corrosion in metals.
Analyzing the impact of different concentrations of pollutants on aquatic ecosystems.
Examining the effectiveness of different antibiotics on bacterial growth.
Trying to figure out how temperature affects how thick liquids are.
Finding out if there is a link between the amount of pollution in the air and lung illnesses in cities.
Analyzing the efficiency of solar panels in converting sunlight into electricity under varying conditions.

Descriptive Research Topics for STEM Students

Descriptive research aims to provide a detailed account or description of a phenomenon. Here are 10 topics for STEM students interested in descriptive research:

Describing the physical characteristics and behavior of a newly discovered species of marine life.
Documenting the geological features and formations of a particular region.
Creating a detailed inventory of plant species in a specific ecosystem.
Describing the properties and behavior of a new synthetic polymer.
Documenting the daily weather patterns and climate trends in a particular area.
Providing a comprehensive analysis of the energy consumption patterns in a city.
Describing the structural components and functions of a newly developed medical device.
Documenting the characteristics and usage of traditional construction materials in a region.
Providing a detailed account of the microbiome in a specific environmental niche.
Describing the life cycle and behavior of a rare insect species.

Research Topics for STEM Students in the Pandemic:

The COVID-19 pandemic has raised many research opportunities for STEM students. Here are 10 research topics related to pandemics:

Analyzing the effectiveness of various personal protective equipment (PPE) in preventing the spread of respiratory viruses.
Studying the impact of lockdown measures on air quality and pollution levels in urban areas.
Investigating the psychological effects of quarantine and social isolation on mental health.
Analyzing the genomic variation of the SARS-CoV-2 virus and its implications for vaccine development.
Studying the efficacy of different disinfection methods on various surfaces.
Investigating the role of contact tracing apps in tracking & controlling the spread of infectious diseases.
Analyzing the economic impact of the pandemic on different industries and sectors.
Studying the effectiveness of remote learning in STEM education during lockdowns.
Investigating the social disparities in healthcare access during a pandemic.
Analyzing the ethical considerations surrounding vaccine distribution and prioritization.

Research Topics for STEM Students Middle School

Research topics for middle school STEM students should be engaging and suitable for their age group. Here are 10 research topics:

Investigating the growth patterns of different types of mold on various food items.
Studying the negative effects of music on plant growth and development.
Analyzing the relationship between the shape of a paper airplane and its flight distance.
Investigating the properties of different materials in making effective insulators for hot and cold beverages.
Studying the effect of salt on the buoyancy of different objects in water.
Analyzing the behavior of magnets when exposed to different temperatures.
Investigating the factors that affect the rate of ice melting in different environments.
Studying the impact of color on the absorption of heat by various surfaces.
Analyzing the growth of crystals in different types of solutions.
Investigating the effectiveness of different natural repellents against common pests like mosquitoes.

Technology Research Topics for STEM Students

Technology is at the forefront of STEM fields. Here are 10 research topics for STEM students interested in technology:

Developing and optimizing algorithms for autonomous drone navigation in complex environments.
Exploring the use of blockchain technology for enhancing the security and transparency of supply chains.
Investigating the applications of virtual reality (VR) and augmented reality (AR) in medical training and surgery simulations.
Studying the potential of 3D printing for creating personalized prosthetics and orthopedic implants.
Analyzing the ethical and privacy implications of facial recognition technology in public spaces.
Investigating the development of quantum computing algorithms for solving complex optimization problems.
Explaining the use of machine learning and AI in predicting and mitigating the impact of natural disasters.
Studying the advancement of brain-computer interfaces for assisting individuals with
disabilities.
Analyzing the role of wearable technology in monitoring and improving personal health and wellness.
Investigating the use of robotics in disaster response and search and rescue operations.

Scientific Research Topics for STEM Students

Scientific research encompasses a wide range of topics. Here are 10 research topics for STEM students focusing on scientific exploration:

Investigating the behavior of subatomic particles in high-energy particle accelerators.
Studying the ecological impact of invasive species on native ecosystems.
Analyzing the genetics of antibiotic resistance in bacteria and its implications for healthcare.
Exploring the physics of gravitational waves and their detection through advanced interferometry.
Investigating the neurobiology of memory formation and retention in the human brain.
Studying the biodiversity and adaptation of extremophiles in harsh environments.
Analyzing the chemistry of deep-sea hydrothermal vents and their potential for life beyond Earth.
Exploring the properties of superconductors and their applications in technology.
Investigating the mechanisms of stem cell differentiation for regenerative medicine.
Studying the dynamics of climate change and its impact on global ecosystems.

Interesting Research Topics for STEM Students:

Engaging and intriguing research topics can foster a passion for STEM. Here are 10 interesting research topics for STEM students:

Exploring the science behind the formation of auroras and their cultural significance.
Investigating the mysteries of dark matter and dark energy in the universe.
Studying the psychology of decision-making in high-pressure situations, such as sports or
emergencies.
Analyzing the impact of social media on interpersonal relationships and mental health.
Exploring the potential for using genetic modification to create disease-resistant crops.
Investigating the cognitive processes involved in solving complex puzzles and riddles.
Studying the history and evolution of cryptography and encryption methods.
Analyzing the physics of time travel and its theoretical possibilities.
Exploring the role of Artificial Intelligence in creating art and music.
Investigating the science of happiness and well-being, including factors contributing to life satisfaction.

Practical Research Topics for STEM Students

Practical research often leads to real-world solutions. Here are 10 practical research topics for STEM students:

Developing an affordable and sustainable water purification system for rural communities.
Designing a low-cost, energy-efficient home heating and cooling system.
Investigating strategies for reducing food waste in the supply chain and households.
Studying the effectiveness of eco-friendly pest control methods in agriculture.
Analyzing the impact of renewable energy integration on the stability of power grids.
Developing a smartphone app for early detection of common medical conditions.
Investigating the feasibility of vertical farming for urban food production.
Designing a system for recycling and upcycling electronic waste.
Studying the environmental benefits of green roofs and their potential for urban heat island mitigation.
Analyzing the efficiency of alternative transportation methods in reducing carbon emissions.

Experimental Research Topics for STEM Students About Plants

Plants offer a rich field for experimental research. Here are 10 experimental research topics about plants for STEM students:

Investigating the effect of different light wavelengths on plant growth and photosynthesis.
Studying the impact of various fertilizers and nutrient solutions on crop yield.
Analyzing the response of plants to different types and concentrations of plant hormones.
Investigating the role of mycorrhizal in enhancing nutrient uptake in plants.
Studying the effects of drought stress and water scarcity on plant physiology and adaptation mechanisms.
Analyzing the influence of soil pH on plant nutrient availability and growth.
Investigating the chemical signaling and defense mechanisms of plants against herbivores.
Studying the impact of environmental pollutants on plant health and genetic diversity.
Analyzing the role of plant secondary metabolites in pharmaceutical and agricultural applications.
Investigating the interactions between plants and beneficial microorganisms in the rhizosphere.

Qualitative Research Topics for STEM Students in the Philippines

Qualitative research in the Philippines can address local issues and cultural contexts. Here are 10 qualitative research topics for STEM students in the Philippines:

Exploring indigenous knowledge and practices in sustainable agriculture in Filipino communities.
Studying the perceptions and experiences of Filipino fishermen in coping with climate change impacts.
Analyzing the cultural significance and traditional uses of medicinal plants in indigenous Filipino communities.
Investigating the barriers and facilitators of STEM education access in remote Philippine islands.
Exploring the role of traditional Filipino architecture in natural disaster resilience.
Studying the impact of indigenous farming methods on soil conservation and fertility.
Analyzing the cultural and environmental significance of mangroves in coastal Filipino regions.
Investigating the knowledge and practices of Filipino healers in treating common ailments.
Exploring the cultural heritage and conservation efforts of the Ifugao rice terraces.
Studying the perceptions and practices of Filipino communities in preserving marine biodiversity.

Science Research Topics for STEM Students

Science offers a diverse range of research avenues. Here are 10 science research topics for STEM students:

Investigating the potential of gene editing techniques like CRISPR-Cas9 in curing genetic diseases.
Studying the ecological impacts of species reintroduction programs on local ecosystems.
Analyzing the effects of microplastic pollution on aquatic food webs and ecosystems.
Investigating the link between air pollution and respiratory health in urban populations.
Studying the role of epigenetics in the inheritance of acquired traits in organisms.
Analyzing the physiology and adaptations of extremophiles in extreme environments on Earth.
Investigating the genetics of longevity and factors influencing human lifespan.
Studying the behavioral ecology and communication strategies of social insects.
Analyzing the effects of deforestation on global climate patterns and biodiversity loss.
Investigating the potential of synthetic biology in creating bioengineered organisms for beneficial applications.

Correlational Research Topics for STEM Students

Correlational research focuses on relationships between variables. Here are 10 correlational research topics for STEM students:

Analyzing the correlation between dietary habits and the incidence of chronic diseases.
Studying the relationship between exercise frequency and mental health outcomes.
Investigating the correlation between socioeconomic status and access to quality healthcare.
Analyzing the link between social media usage and self-esteem in adolescents.
Studying the correlation between academic performance and sleep duration among students.
Investigating the relationship between environmental factors and the prevalence of allergies.
Analyzing the correlation between technology use and attention span in children.
Studying how environmental factors are related to the frequency of allergies.
Investigating the link between parental involvement in education and student achievement.
Analyzing the correlation between temperature fluctuations and wildlife migration patterns.

Quantitative Research Topics for STEM Students in the Philippines

Quantitative research in the Philippines can address specific regional issues. Here are 10 quantitative research topics for STEM students in the Philippines

Analyzing the impact of typhoons on coastal erosion rates in the Philippines.
Studying the quantitative effects of land use change on watershed hydrology in Filipino regions.
Investigating the quantitative relationship between deforestation and habitat loss for endangered species.
Analyzing the quantitative patterns of marine biodiversity in Philippine coral reef ecosystems.
Studying the quantitative assessment of water quality in major Philippine rivers and lakes.
Investigating the quantitative analysis of renewable energy potential in specific Philippine provinces.
Analyzing the quantitative impacts of agricultural practices on soil health and fertility.
Studying the quantitative effectiveness of mangrove restoration in coastal protection in the Philippines.
Investigating the quantitative evaluation of indigenous agricultural practices for sustainability.
Analyzing the quantitative patterns of air pollution and its health impacts in urban Filipino areas.

Things That Must Keep In Mind While Writing Quantitative Research Title

Here are few things that must be keep in mind while writing quantitative research tile:

1. Be Clear and Precise

Make sure your research title is clear and says exactly what your study is about. People should easily understand the topic and goals of your research by reading the title.

2. Use Important Words

Include words that are crucial to your research, like the main subjects, who you’re studying, and how you’re doing your research. This helps others find your work and understand what it’s about.

3. Avoid Confusing Words

Stay away from words that might confuse people. Your title should be easy to grasp, even if someone isn’t an expert in your field.

4. Show Your Research Approach

Tell readers what kind of research you did, like experiments or surveys. This gives them a hint about how you conducted your study.

5. Match Your Title with Your Research Questions

Make sure your title matches the questions you’re trying to answer in your research. It should give a sneak peek into what your study is all about and keep you on the right track as you work on it.

STEM students, addressing what STEM is and why research matters in this field. It offered an extensive list of research topics , including experimental, qualitative, and regional options, catering to various academic levels and interests. Whether you’re a middle school student or pursuing advanced studies, these topics offer a wealth of ideas. The key takeaway is to choose a topic that resonates with your passion and aligns with your goals, ensuring a successful journey in STEM research. Choose the best Experimental Quantitative Research Topics For Stem Students today!

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Best 151+ Quantitative Research Topics for STEM Students

In today’s rapidly evolving world, STEM (Science, Technology, Engineering, and Mathematics) fields have gained immense significance. For STEM students, engaging in quantitative research is a pivotal aspect of their academic journey. Quantitative research involves the systematic collection and interpretation of numerical data to address research questions or test hypotheses. Choosing the right research topic is essential to ensure a successful and meaningful research endeavor.

In this blog, we will explore 151+ quantitative research topics for STEM students. Whether you are an aspiring scientist, engineer, or mathematician, this comprehensive list will inspire your research journey. But we understand that the journey through STEM education and research can be challenging at times. That’s why we’re here to support you every step of the way with our Engineering Assignment Help service.

What is Quantitative Research in STEM?

Table of Contents

Quantitative research is a scientific approach that relies on numerical data and statistical analysis to draw conclusions and make predictions. In STEM fields, quantitative research encompasses a wide range of methodologies, including experiments, surveys, and data analysis. The key characteristics of quantitative research in STEM include:

Data Collection: Systematic gathering of numerical data through experiments, observations, or surveys.
Statistical Analysis: Application of statistical techniques to analyze data and draw meaningful conclusions.
Hypothesis Testing: Testing hypotheses and theories using quantitative data.
Replicability: The ability to replicate experiments and obtain consistent results.
Generalizability: Drawing conclusions that can be applied to larger populations or phenomena.

Importance of Quantitative Research Topics for STEM Students

Quantitative research plays a pivotal role in STEM education and research for several reasons:

1. Empirical Evidence

It provides empirical evidence to support or refute scientific theories and hypotheses.

2. Data-Driven Decision-Making

STEM professionals use quantitative research to make informed decisions, from designing experiments to developing new technologies.

3. Innovation

It fuels innovation by providing data-driven insights that lead to the creation of new products, processes, and technologies.

4. Problem Solving

STEM students learn critical problem-solving skills through quantitative research, which are invaluable in their future careers.

5. Interdisciplinary Applications

Quantitative research transcends STEM disciplines, facilitating collaboration and the tackling of complex, real-world problems.

Also Read: Google Scholar Research Topics

Quantitative Research Topics for STEM Students

Now, let’s explore important quantitative research topics for STEM students:

Biology and Life Sciences

Here are some quantitative research topics in biology and life science:

1. The impact of climate change on biodiversity.

2. Analyzing the genetic basis of disease susceptibility.

3. Studying the effectiveness of vaccines in preventing infectious diseases.

4. Investigating the ecological consequences of invasive species.

5. Examining the role of genetics in aging.

6. Analyzing the effects of pollution on aquatic ecosystems.

7. Studying the evolution of antibiotic resistance.

8. Investigating the relationship between diet and lifespan.

9. Analyzing the impact of deforestation on wildlife.

10. Studying the genetics of cancer development.

11. Investigating the effectiveness of various plant fertilizers.

12. Analyzing the impact of microplastics on marine life.

13. Studying the genetics of human behavior.

14. Investigating the effects of pollution on plant growth.

15. Analyzing the microbiome’s role in human health.

16. Studying the impact of climate change on crop yields.

17. Investigating the genetics of rare diseases.

Let’s get started with some quantitative research topics for stem students in chemistry:

1. Studying the properties of superconductors at different temperatures.

2. Analyzing the efficiency of various catalysts in chemical reactions.

3. Investigating the synthesis of novel polymers with unique properties.

4. Studying the kinetics of chemical reactions.

5. Analyzing the environmental impact of chemical waste disposal.

6. Investigating the properties of nanomaterials for drug delivery.

7. Studying the behavior of nanoparticles in different solvents.

8. Analyzing the use of renewable energy sources in chemical processes.

9. Investigating the chemistry of atmospheric pollutants.

10. Studying the properties of graphene for electronic applications.

11. Analyzing the use of enzymes in industrial processes.

12. Investigating the chemistry of alternative fuels.

13. Studying the synthesis of pharmaceutical compounds.

14. Analyzing the properties of materials for battery technology.

15. Investigating the chemistry of natural products for drug discovery.

16. Analyzing the effects of chemical additives on food preservation.

17. Investigating the chemistry of carbon capture and utilization technologies.

Here are some quantitative research topics in physics for stem students:

1. Investigating the behavior of subatomic particles in high-energy collisions.

2. Analyzing the properties of dark matter and dark energy.

3. Studying the quantum properties of entangled particles.

4. Investigating the dynamics of black holes and their gravitational effects.

5. Analyzing the behavior of light in different mediums.

6. Studying the properties of superfluids at low temperatures.

7. Investigating the physics of renewable energy sources like solar cells.

8. Analyzing the properties of materials at extreme temperatures and pressures.

9. Studying the behavior of electromagnetic waves in various applications.

10. Investigating the physics of quantum computing.

11. Analyzing the properties of magnetic materials for data storage.

12. Studying the behavior of particles in plasma for fusion energy research.

13. Investigating the physics of nanoscale materials and devices.

14. Analyzing the properties of materials for use in semiconductors.

15. Studying the principles of thermodynamics in energy efficiency.

16. Investigating the physics of gravitational waves.

17. Analyzing the properties of materials for use in quantum technologies.

Engineering

Let’s explore some quantitative research topics for stem students in engineering:

1. Investigating the efficiency of renewable energy systems in urban environments.

2. Analyzing the impact of 3D printing on manufacturing processes.

3. Studying the structural integrity of materials in aerospace engineering.

4. Investigating the use of artificial intelligence in autonomous vehicles.

5. Analyzing the efficiency of water treatment processes in civil engineering.

6. Studying the impact of robotics in healthcare.

7. Investigating the optimization of supply chain logistics using quantitative methods.

8. Analyzing the energy efficiency of smart buildings.

9. Studying the effects of vibration on structural engineering.

10. Investigating the use of drones in agricultural practices.

11. Analyzing the impact of machine learning in predictive maintenance.

12. Studying the optimization of transportation networks.

13. Investigating the use of nanomaterials in electronic devices.

14. Analyzing the efficiency of renewable energy storage systems.

15. Studying the impact of AI-driven design in architecture.

16. Investigating the optimization of manufacturing processes using Industry 4.0 technologies.

17. Analyzing the use of robotics in underwater exploration.

Environmental Science

Here are some top quantitative research topics in environmental science for students:

1. Investigating the effects of air pollution on respiratory health.

2. Analyzing the impact of deforestation on climate change.

3. Studying the biodiversity of coral reefs and their conservation.

4. Investigating the use of remote sensing in monitoring deforestation.

5. Analyzing the effects of plastic pollution on marine ecosystems.

6. Studying the impact of climate change on glacier retreat.

7. Investigating the use of wetlands for water quality improvement.

8. Analyzing the effects of urbanization on local microclimates.

9. Studying the impact of oil spills on aquatic ecosystems.

10. Investigating the use of renewable energy in mitigating greenhouse gas emissions.

11. Analyzing the effects of soil erosion on agricultural productivity.

12. Studying the impact of invasive species on native ecosystems.

13. Investigating the use of bioremediation for soil cleanup.

14. Analyzing the effects of climate change on migratory bird patterns.

15. Studying the impact of land use changes on water resources.

16. Investigating the use of green infrastructure for urban stormwater management.

17. Analyzing the effects of noise pollution on wildlife behavior.

Computer Science

Let’s get started with some simple quantitative research topics for stem students:

1. Investigating the efficiency of machine learning algorithms for image recognition.

2. Analyzing the security of blockchain technology in financial transactions.

3. Studying the impact of quantum computing on cryptography.

4. Investigating the use of natural language processing in chatbots and virtual assistants.

5. Analyzing the effectiveness of cybersecurity measures in protecting sensitive data.

6. Studying the impact of algorithmic trading in financial markets.

7. Investigating the use of deep learning in autonomous robotics.

8. Analyzing the efficiency of data compression algorithms for large datasets.

9. Studying the impact of virtual reality in medical simulations.

10. Investigating the use of artificial intelligence in personalized medicine.

11. Analyzing the effectiveness of recommendation systems in e-commerce.

12. Studying the impact of cloud computing on data storage and processing.

13. Investigating the use of neural networks in predicting disease outbreaks.

14. Analyzing the efficiency of data mining techniques in customer behavior analysis.

15. Studying the impact of social media algorithms on user behavior.

16. Investigating the use of machine learning in natural language translation.

17. Analyzing the effectiveness of sentiment analysis in social media monitoring.

Mathematics

Let’s explore the quantitative research topics in mathematics for students:

1. Investigating the properties of prime numbers and their distribution.

2. Analyzing the behavior of chaotic systems using differential equations.

3. Studying the optimization of algorithms for solving complex mathematical problems.

4. Investigating the use of graph theory in network analysis.

5. Analyzing the properties of fractals in natural phenomena.

6. Studying the application of probability theory in risk assessment.

7. Investigating the use of numerical methods in solving partial differential equations.

8. Analyzing the properties of mathematical models for population dynamics.

9. Studying the optimization of algorithms for data compression.

10. Investigating the use of topology in data analysis.

11. Analyzing the behavior of mathematical models in financial markets.

12. Studying the application of game theory in strategic decision-making.

13. Investigating the use of mathematical modeling in epidemiology.

14. Analyzing the properties of algebraic structures in coding theory.

15. Studying the optimization of algorithms for image processing.

16. Investigating the use of number theory in cryptography.

17. Analyzing the behavior of mathematical models in climate prediction.

Earth Sciences

Here are some quantitative research topics for stem students in earth science:

1. Investigating the impact of volcanic eruptions on climate patterns.

2. Analyzing the behavior of earthquakes along tectonic plate boundaries.

3. Studying the geomorphology of river systems and erosion.

4. Investigating the use of remote sensing in monitoring wildfires.

5. Analyzing the effects of glacier melt on sea-level rise.

6. Studying the impact of ocean currents on weather patterns.

7. Investigating the use of geothermal energy in renewable power generation.

8. Analyzing the behavior of tsunamis and their destructive potential.

9. Studying the impact of soil erosion on agricultural productivity.

10. Investigating the use of geological data in mineral resource exploration.

11. Analyzing the effects of climate change on coastal erosion.

12. Studying the geomagnetic field and its role in navigation.

13. Investigating the use of radar technology in weather forecasting.

14. Analyzing the behavior of landslides and their triggers.

15. Studying the impact of groundwater depletion on aquifer systems.

16. Investigating the use of GIS (Geographic Information Systems) in land-use planning.

17. Analyzing the effects of urbanization on heat island formation.

Health Sciences and Medicine

Here are some quantitative research topics for stem students in health science and medicine:

1. Investigating the effectiveness of telemedicine in improving healthcare access.

2. Analyzing the impact of personalized medicine in cancer treatment.

3. Studying the epidemiology of infectious diseases and their spread.

4. Investigating the use of wearable devices in monitoring patient health.

5. Analyzing the effects of nutrition and exercise on metabolic health.

6. Studying the impact of genetics in predicting disease susceptibility.

7. Investigating the use of artificial intelligence in medical diagnosis.

8. Analyzing the behavior of pharmaceutical drugs in clinical trials.

9. Studying the effectiveness of mental health interventions in schools.

10. Investigating the use of gene editing technologies in treating genetic disorders.

11. Analyzing the properties of medical imaging techniques for early disease detection.

12. Studying the impact of vaccination campaigns on public health.

13. Investigating the use of regenerative medicine in tissue repair.

14. Analyzing the behavior of pathogens in antimicrobial resistance.

15. Studying the epidemiology of chronic diseases like diabetes and heart disease.

16. Investigating the use of bioinformatics in genomics research.

17. Analyzing the effects of environmental factors on health outcomes.

Quantitative research is the backbone of STEM fields, providing the tools and methodologies needed to explore, understand, and innovate in the world of science and technology . As STEM students, embracing quantitative research not only enhances your analytical skills but also equips you to address complex real-world challenges. With the extensive list of 155+ quantitative research topics for stem students provided in this blog, you have a starting point for your own STEM research journey. Whether you’re interested in biology, chemistry, physics, engineering, or any other STEM discipline, there’s a wealth of quantitative research topics waiting to be explored. So, roll up your sleeves, grab your lab coat or laptop, and embark on your quest for knowledge and discovery in the exciting world of STEM.

I hope you enjoyed this blog post about quantitative research topics for stem students.

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189+ Good Quantitative Research Topics For STEM Students

Quantitative research is an essential part of STEM (Science, Technology, Engineering, and Mathematics) fields. It involves collecting and analyzing numerical data to answer research questions and test hypotheses.

In 2023, STEM students have a wealth of exciting research opportunities in various disciplines. Whether you’re an undergraduate or graduate student, here are quantitative research topics to consider for your next project.

If you are looking for the best list of quantitative research topics for stem students, then you can check the given list in each field. It offers STEM students numerous opportunities to explore and contribute to their respective fields in 2023 and beyond.

Whether you’re interested in astrophysics, biology, engineering, mathematics, or any other STEM field.

Also Read: Most Exciting Qualitative Research Topics For Students

What Is Quantitative Research

Table of Contents

Quantitative research is a type of research that focuses on the organized collection, analysis, and evaluation of numerical data to answer research questions, test theories, and find trends or connections between factors. It is an organized, objective way to do study that uses measurable data and scientific methods to come to results.

Quantitative research is often used in many areas, such as the natural sciences, social sciences, economics, psychology, education, and market research. It gives useful information about patterns, trends, cause-and-effect relationships, and how often things happen. Quantitative tools are used by researchers to answer questions like “How many?” and “How often?” “Is there a significant difference?” or “What is the relationship between the variables?”

In comparison to quantitative research, qualitative research uses non-numerical data like conversations, notes, and open-ended surveys to understand and explore the ideas, experiences, and points of view of people or groups. Researchers often choose between quantitative and qualitative methods based on their research goals, questions, and the type of thing they are studying.

How To Choose Quantitative Research Topics For STEM

Here’s a step-by-step guide on how to choose quantitative research topics for STEM:

Step 1:- Identify Your Interests and Passions

Start by reflecting on your personal interests within STEM. What areas or subjects in STEM excite you the most? Choosing a topic you’re passionate about will keep you motivated throughout the research process.

Step 2:- Review Coursework and Textbooks

Look through your coursework, textbooks, and class notes. Identify concepts, theories, or areas that you found particularly intriguing or challenging. These can be a source of potential research topics.

Step 3:- Consult with Professors and Advisors

Discuss your research interests with professors, academic advisors, or mentors. They can provide valuable insights, suggest relevant topics, and guide you toward areas with research opportunities.

Step 4:- Read Recent Literature

Explore recent research articles, journals, and publications in STEM fields. This will help you identify current trends, gaps in knowledge, and areas where further research is needed.

Step 5:- Narrow Down Your Focus

Once you have a broad area of interest, narrow it down to a specific research focus. Consider questions like:

What specific problem or phenomenon do you want to investigate?
Are there unanswered questions or controversies in this area?
What impact could your research have on the field or society?

Step 6:- Consider Resources and Access

Assess the resources available to you, including access to laboratories, equipment, databases, and funding. Ensure that your chosen topic aligns with the resources you have or can access.

Step 7:- Think About Practicality

Consider the feasibility of conducting research on your chosen topic. Are the data readily available, or will you need to collect data yourself? Can you complete the research within your available time frame?

Step 8:- Define Your Research Question

Formulate a clear and specific research question or hypothesis. Your research question should guide your entire study and provide a focus for your data collection and analysis.

Step 9:- Conduct a Literature Review

Dive deeper into the existing literature related to your chosen topic. This will help you understand the current state of research, identify gaps, and refine your research question.

Step 10:- Consider the Impact

Think about the potential impact of your research. How does your topic contribute to the advancement of knowledge in your field? Does it have practical applications or implications for society?

Step 11:- Brainstorm Research Methods

Determine the quantitative research methods and data collection techniques you plan to use. Consider whether you’ll conduct experiments, surveys, data analysis, simulations, or use existing datasets.

Step 12:- Seek Feedback

Share your research topic and ideas with peers, advisors, or mentors. They can provide valuable feedback and help you refine your research focus.

Step 13:- Assess Ethical Considerations

Consider ethical implications related to your research, especially if it involves human subjects, sensitive data, or potential environmental impacts. Ensure that your research adheres to ethical guidelines.

Step 14:- Finalize Your Research Topic

Once you’ve gone through these steps, finalize your research topic. Write a clear and concise research proposal that outlines your research question, objectives, methods, and expected outcomes.

Step 15:- Stay Open to Adjustments

Be open to adjusting your research topic as you progress. Sometimes, new insights or challenges may lead you to refine or adapt your research focus.

Following are the most interesting quantitative research topics for stem students. These are given below.

Quantitative Research Topics In Physics and Astronomy

Quantum Computing Algorithms : Investigate new algorithms for quantum computers and their potential applications.
Dark Matter Detection Methods : Explore innovative approaches to detect dark matter particles.
Quantum Teleportation : Study the principles and applications of quantum teleportation.
Exoplanet Characterization : Analyze data from telescopes to characterize exoplanets.
Nuclear Fusion Modeling : Create mathematical models for nuclear fusion reactions.
Superconductivity at High Temperatures : Research the properties and applications of high-temperature superconductors.
Gravitational Wave Analysis : Analyze gravitational wave data to study astrophysical phenomena.
Black Hole Thermodynamics : Investigate the thermodynamics of black holes and their entropy.

Quantitative Research Topics In Biology and Life Sciences

Genome-Wide Association Studies (GWAS) : Conduct GWAS to identify genetic factors associated with diseases.
Pharmacokinetics and Pharmacodynamics : Study drug interactions in the human body.
Ecological Modeling : Model ecosystems to understand population dynamics.
Protein Folding : Research the kinetics and thermodynamics of protein folding.
Cancer Epidemiology : Analyze cancer incidence and risk factors in specific populations.
Neuroimaging Analysis : Develop algorithms for analyzing brain imaging data.
Evolutionary Genetics : Investigate evolutionary patterns using genetic data.
Stem Cell Differentiation : Study the factors influencing stem cell differentiation.

Engineering and Technology Quantitative Research Topics

Renewable Energy Efficiency : Optimize the efficiency of solar panels or wind turbines.
Aerodynamics of Drones : Analyze the aerodynamics of drone designs.
Autonomous Vehicle Safety : Evaluate safety measures for autonomous vehicles.
Machine Learning in Robotics : Implement machine learning algorithms for robot control.
Blockchain Scalability : Research methods to scale blockchain technology.
Quantum Computing Hardware : Design and test quantum computing hardware components.
IoT Security : Develop security protocols for the Internet of Things (IoT).
3D Printing Materials Analysis : Study the mechanical properties of 3D-printed materials.

Quantitative Research Topics In Mathematics and Statistics

Following are the best Quantitative Research Topics For STEM Students in mathematics and statistics.

Prime Number Distribution : Investigate the distribution of prime numbers.
Graph Theory Algorithms : Develop algorithms for solving graph theory problems.
Statistical Analysis of Financial Markets : Analyze financial data and market trends.
Number Theory Research : Explore unsolved problems in number theory.
Bayesian Machine Learning : Apply Bayesian methods to machine learning models.
Random Matrix Theory : Study the properties of random matrices in mathematics and physics.
Topological Data Analysis : Use topology to analyze complex data sets.
Quantum Algorithms for Optimization : Research quantum algorithms for optimization problems.

Experimental Quantitative Research Topics In Science and Earth Sciences

Climate Change Modeling : Develop climate models to predict future trends.
Biodiversity Conservation Analysis : Analyze data to support biodiversity conservation efforts.
Geographic Information Systems (GIS) : Apply GIS techniques to solve environmental problems.
Oceanography and Remote Sensing : Use satellite data for oceanographic research.
Air Quality Monitoring : Develop sensors and models for air quality assessment.
Hydrological Modeling : Study the movement and distribution of water resources.
Volcanic Activity Prediction : Predict volcanic eruptions using quantitative methods.
Seismology Data Analysis : Analyze seismic data to understand earthquake patterns.

Chemistry and Materials Science Quantitative Research Topics

Nanomaterial Synthesis and Characterization : Research the synthesis and properties of nanomaterials.
Chemoinformatics : Analyze chemical data for drug discovery and materials science.
Quantum Chemistry Simulations : Perform quantum simulations of chemical reactions.
Materials for Renewable Energy : Investigate materials for energy storage and conversion.
Catalysis Kinetics : Study the kinetics of chemical reactions catalyzed by materials.
Polymer Chemistry : Research the properties and applications of polymers.
Analytical Chemistry Techniques : Develop new analytical techniques for chemical analysis.
Sustainable Chemistry : Explore green chemistry approaches for sustainable materials.

Computer Science and Information Technology Topics

Natural Language Processing (NLP) : Work on NLP algorithms for language understanding.
Cybersecurity Analytics : Analyze cybersecurity threats and vulnerabilities.
Big Data Analytics : Apply quantitative methods to analyze large data sets.
Machine Learning Fairness : Investigate bias and fairness issues in machine learning models.
Human-Computer Interaction (HCI) : Study user behavior and interaction patterns.
Software Performance Optimization : Optimize software applications for performance.
Distributed Systems Analysis : Analyze the performance of distributed computing systems.
Bioinformatics Data Mining : Develop algorithms for mining biological data.

Good Quantitative Research Topics Students In Medicine and Healthcare

Clinical Trial Data Analysis : Analyze clinical trial data to evaluate treatment effectiveness.
Epidemiological Modeling : Model disease spread and intervention strategies.
Healthcare Data Analytics : Analyze healthcare data for patient outcomes and cost reduction.
Medical Imaging Algorithms : Develop algorithms for medical image analysis.
Genomic Medicine : Apply genomics to personalized medicine approaches.
Telemedicine Effectiveness : Study the effectiveness of telemedicine in healthcare delivery.
Health Informatics : Analyze electronic health records for insights into patient care.

Agriculture and Food Sciences Topics

Precision Agriculture : Use quantitative methods for optimizing crop production.
Food Safety Analysis : Analyze food safety data and quality control.
Aquaculture Sustainability : Research sustainable practices in aquaculture.
Crop Disease Modeling : Model the spread of diseases in agricultural crops.
Climate-Resilient Agriculture : Develop strategies for agriculture in changing climates.
Food Supply Chain Optimization : Optimize food supply chain logistics.
Soil Health Assessment : Analyze soil data for sustainable land management.

Social Sciences with Quantitative Approaches

Educational Data Mining : Analyze educational data for improving learning outcomes.
Sociodemographic Surveys : Study social trends and demographics using surveys.
Psychometrics : Develop and validate psychological measurement instruments.
Political Polling Analysis : Analyze political polling data and election trends.
Economic Modeling : Develop economic models for policy analysis.
Urban Planning Analytics : Analyze data for urban planning and infrastructure.
Climate Policy Evaluation : Evaluate the impact of climate policies on society.

Environmental Engineering Quantitative Research Topics

Water Quality Assessment : Analyze water quality data for environmental monitoring.
Waste Management Optimization : Optimize waste collection and recycling programs.
Environmental Impact Assessments : Evaluate the environmental impact of projects.
Air Pollution Modeling : Model the dispersion of air pollutants in urban areas.
Sustainable Building Design : Apply quantitative methods to sustainable architecture.

Quantitative Research Topics Robotics and Automation

Robotic Swarm Behavior : Study the behavior of robot swarms in different tasks.
Autonomous Drone Navigation : Develop algorithms for autonomous drone navigation.
Humanoid Robot Control : Implement control algorithms for humanoid robots.
Robotic Grasping and Manipulation : Study robotic manipulation techniques.
Reinforcement Learning for Robotics : Apply reinforcement learning to robotic control.

Quantitative Research Topics Materials Engineering

Additive Manufacturing Process Optimization : Optimize 3D printing processes.
Smart Materials for Aerospace : Research smart materials for aerospace applications.
Nanostructured Materials for Energy Storage : Investigate energy storage materials.
Corrosion Prevention : Develop corrosion-resistant materials and coatings.

Nuclear Engineering Quantitative Research Topics

Nuclear Reactor Safety Analysis : Study safety aspects of nuclear reactor designs.
Nuclear Fuel Cycle Analysis : Analyze the nuclear fuel cycle for efficiency.
Radiation Shielding Materials : Research materials for radiation protection.

Quantitative Research Topics In Biomedical Engineering

Medical Device Design and Testing : Develop and test medical devices.
Biomechanics Analysis : Analyze biomechanics in sports or rehabilitation.
Biomaterials for Medical Implants : Investigate materials for medical implants.

Good Quantitative Research Topics Chemical Engineering

Chemical Process Optimization : Optimize chemical manufacturing processes.
Industrial Pollution Control : Develop strategies for pollution control in industries.
Chemical Reaction Kinetics : Study the kinetics of chemical reactions in industries.

Best Quantitative Research Topics In Renewable Energy

Energy Storage Systems : Research and optimize energy storage solutions.
Solar Cell Efficiency : Improve the efficiency of photovoltaic cells.
Wind Turbine Performance Analysis : Analyze and optimize wind turbine designs.

Brilliant Quantitative Research Topics In Astronomy and Space Sciences

Astrophysical Simulations : Simulate astrophysical phenomena using numerical methods.
Spacecraft Trajectory Optimization : Optimize spacecraft trajectories for missions.
Exoplanet Detection Algorithms : Develop algorithms for exoplanet detection.

Quantitative Research Topics In Psychology and Cognitive Science

Cognitive Psychology Experiments : Conduct quantitative experiments in cognitive psychology.
Emotion Recognition Algorithms : Develop algorithms for emotion recognition in AI.
Neuropsychological Assessments : Create quantitative assessments for brain function.

Geology and Geological Engineering Quantitative Research Topics

Geological Data Analysis : Analyze geological data for mineral exploration.
Geological Hazard Prediction : Predict geological hazards using quantitative models.

Great Quantitative Research Topics In Cybersecurity

Network Intrusion Detection : Develop quantitative methods for intrusion detection.
Cryptocurrency Analysis : Analyze blockchain data and cryptocurrency trends.

Mathematical Biology Quantitative Research Topics

Epidemiological Modeling : Model disease spread and control in populations.
Population Genetics : Analyze genetic data to understand population dynamics.

Quantitative Research Topics In Chemical Analysis

Analytical Chemistry Methods : Develop quantitative methods for chemical analysis.
Spectroscopy Analysis : Analyze spectroscopic data for chemical identification.

Mathematics Education Quantitative Research Topics

Mathematics Curriculum Analysis : Analyze curriculum effectiveness in mathematics education.
Mathematics Assessment Development : Develop quantitative assessments for mathematics skills.

Quantitative Research Topics In Social Research

Social Network Analysis : Analyze social network structures and dynamics.
Survey Research : Conduct quantitative surveys on social issues and trends.

Quantitative Research Topics In Computational Neuroscience

Neural Network Modeling : Model neural networks and brain functions computationally.
Brain Connectivity Analysis : Analyze functional and structural brain connectivity.

Best Topics In Transportation Engineering

Traffic Flow Modeling : Model and optimize traffic flow in urban areas.
Public Transportation Efficiency : Analyze the efficiency of public transportation systems.

Good Quantitative Research Topics In Energy Economics

Energy Policy Analysis : Evaluate the economic impact of energy policies.
Renewable Energy Cost-Benefit Analysis : Assess the economic viability of renewable energy projects.

Quantum Information Science

Quantum Cryptography Protocols : Develop and analyze quantum cryptography protocols.
Quantum Key Distribution : Study the security of quantum key distribution systems.

Human Genetics

Genome Editing Ethics : Investigate ethical issues in genome editing technologies.
Population Genomics : Analyze genomic data for population genetics research.

Marine Biology

Coral Reef Health Assessment : Quantitatively assess the health of coral reefs.
Marine Ecosystem Modeling : Model marine ecosystems and biodiversity.

Data Science and Machine Learning

Machine Learning Explainability : Develop methods for explaining machine learning models.
Data Privacy in Machine Learning : Study privacy issues in machine learning applications.
Deep Learning for Image Analysis : Develop deep learning models for image recognition.

Environmental Engineering

Robotics and automation, materials engineering, nuclear engineering, biomedical engineering, chemical engineering, renewable energy, astronomy and space sciences, psychology and cognitive science, geology and geological engineering, forensic science, cybersecurity, mathematical biology, chemical analysis, mathematics education, quantitative social research, computational neuroscience, quantitative research topics in transportation engineering, quantitative research topics in energy economics, topics in quantum information science, amazing quantitative research topics in human genetics, quantitative research topics in marine biology, what is a common goal of qualitative and quantitative research.

A common goal of both qualitative and quantitative research is to generate knowledge and gain a deeper understanding of a particular phenomenon or topic. However, they approach this goal in different ways:

1. Understanding a Phenomenon

Both types of research aim to understand and explain a specific phenomenon, whether it’s a social issue, a natural process, a human behavior, or a complex event.

2. Testing Hypotheses

Both qualitative and quantitative research can involve hypothesis testing. While qualitative research may not use statistical hypothesis tests in the same way as quantitative research, it often tests hypotheses or research questions by examining patterns and themes in the data.

3. Contributing to Knowledge

Researchers in both approaches seek to contribute to the body of knowledge in their respective fields. They aim to answer important questions, address gaps in existing knowledge, and provide insights that can inform theory, practice, or policy.

4. Informing Decision-Making

Research findings from both qualitative and quantitative studies can be used to inform decision-making in various domains, whether it’s in academia, government, industry, healthcare, or social services.

5. Enhancing Understanding

Both approaches strive to enhance our understanding of complex phenomena by systematically collecting and analyzing data. They aim to provide evidence-based explanations and insights.

6. Application

Research findings from both qualitative and quantitative studies can be applied to practical situations. For example, the results of a quantitative study on the effectiveness of a new drug can inform medical treatment decisions, while qualitative research on customer preferences can guide marketing strategies.

7. Contributing to Theory

In academia, both types of research contribute to the development and refinement of theories in various disciplines. Quantitative research may provide empirical evidence to support or challenge existing theories, while qualitative research may generate new theoretical frameworks or perspectives.

Conclusion – Quantitative Research Topics For STEM Students

So, selecting a quantitative research topic for STEM students is a pivotal decision that can shape the trajectory of your academic and professional journey. The process involves a thoughtful exploration of your interests, a thorough review of the existing literature, consideration of available resources, and the formulation of a clear and specific research question.

Your chosen topic should resonate with your passions, align with your academic or career goals, and offer the potential to contribute to the body of knowledge in your STEM field. Whether you’re delving into physics, biology, engineering, mathematics, or any other STEM discipline, the right research topic can spark curiosity, drive innovation, and lead to valuable insights.

Moreover, quantitative research in STEM not only expands the boundaries of human knowledge but also has the power to address real-world challenges, improve technology, and enhance our understanding of the natural world. It is a journey that demands dedication, intellectual rigor, and an unwavering commitment to scientific inquiry.

What is quantitative research in STEM?

Quantitative research in this context is designed to improve our understanding of the science system’s workings, structural dependencies and dynamics.

What are good examples of quantitative research?

Surveys and questionnaires serve as common examples of quantitative research. They involve collecting data from many respondents and analyzing the results to identify trends, patterns

What are the 4 C’s in STEM?

They became known as the “Four Cs” — critical thinking, communication, collaboration, and creativity.

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Top 151+ Great Quantitative Research Topics For STEM Students

Are you a STEM enthusiast eager to dive into quantitative research but uncertain about the best topics to explore? Look no further! In this comprehensive guide, we’ll navigate through the top 27+ Quantitative Research Topics for STEM Students.

There are we give the best topics for future scientists, engineers, and math whizzes! Are you curious about diving into the fantastic world of quantitative research? Well, you’re in for an exciting way! Today, we’re going to explore some super cool Quantitative Research Topics for STEM Students like you. But first, what’s all this talk about “quantitative research”? Don’t worry; it’s not as tricky as it sounds!

Quantitative research simply means using numbers and data to study things. For example, solving a math problem or conducting a science experiment where you count, measure, or analyze stuff to learn more. Cool, right? Now, let’s talk about STEM. No, not the plant stem, but STEM subjects—science, Technology, Engineering, and Mathematics. These subjects are like the crucial part of knowledge!

So, here’s the exciting part! We’ve got a bunch of fascinating topics lined up for you to explore in these STEM fields using numbers, stats, and math. From studying how robots help doctors predict climate change to finding ways to make renewable energy work better in cities, these topics will make your brain more creative!

Also Like To Know: Sk Project Ideas

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What Is Experimental Quantitative Research Topics For STEM Students

Experimental quantitative research topics for STEM students involve conducting investigations using numbers and measurements to find answers to questions related to science, technology, engineering, and mathematics. These topics help students gather data through controlled experiments and use mathematical analysis to understand how things work or solve problems in subjects like biology, physics, chemistry, or mathematics. For example, they might explore topics like testing how different temperatures affect plant growth or analyzing the relationship between force and motion using simple experiments and numbers.

How Do You Identify A Quantitative Research Title?

Here are 7 easy steps to identify a quantitative research title:

1. Define Your Research Area

Start by identifying the general subject or field you want to study. For instance, it could be related to science, education, psychology, etc.

2. Focus on a Specific Topic

Narrow down your field to a particular region or issue. For instance, if you’re keen on brain research, you should zero in on the impacts of web-based entertainment on teens’ psychological wellness.

3. Identify Variables

Determine the variables or factors you want to measure or investigate. In quantitative research, these are typically measurable quantities or numerical data.

4. Formulate a Research Question

Develop a clear and concise research question that reflects what you want to study. Ensure it is specific and can be addressed using quantitative methods.

5. Consider the Population or Sample

Determine the population you want to study or the sample you’ll collect data from. This will help shape the scope of your research.

6. Quantifiable Outcome

Guarantee that the exploration title recommends a result that can be estimated mathematically. Quantitative exploration means assembling mathematical information and investigating it genuinely.

7. Review and Refine

After forming a speculative title, survey it to guarantee it aligns with the examination targets, is clear and concise, and precisely mirrors the focal point of your review. Make any essential refinements to further develop clarity and accuracy.

List of Best 127+ Great Quantitative Research Topics For STEM Students

Here are the 127+ Great Quantitative Research Topics For STEM Students:

Best Mathematics Quantitative Research Topics For STEM Students

Applications of Machine Learning in Mathematical Problem Solving
Chaos Theory and Its Applications in Nonlinear Systems
Algorithmic Trading Strategies and Mathematical Modeling
Data Compression Techniques: Efficiency and Accuracy Trade-offs
Exploring Applications of Topological Data Analysis
Analyzing Random Matrix Theory in Statistical Physics
Mathematical Models for Climate Change Predictions
Analyzing Cryptocurrency Trends Using Mathematical Models
Investigating Mathematical Models for Social Networks
Studying Mathematical Foundations of Quantum Computing

Easy Quantitative Research Topics For STEM Students In Physics

Quantum Entanglement and Its Applications in Communication
Plasma Physics: Understanding Fusion Reactors
Superconductivity and Its Practical Applications
Statistical Mechanics in Complex Systems
Applications of String Theory in Cosmology
Gravitational Wave Detection and Interpretation
Quantum Field Theory and Particle Interactions
Quantum Computing: Designing Error-Correcting Codes
Analyzing Exoplanet Data Using Astrophysical Models
Studying Black Hole Physics and Information Paradox
Computational Chemistry for Drug Design and Discovery
Quantum Chemistry: Exploring Molecular Properties
Applications of Nanomaterials in Renewable Energy
Analyzing Chemical Reaction Kinetics
Environmental Impact Assessment of Chemical Pollutants
Polymer Chemistry: Designing Advanced Materials
Studying Catalysis and Surface Chemistry
Exploring Electrochemical Energy Storage Systems
Bioinorganic Chemistry: Metalloprotein Modeling
Investigating Supramolecular Chemistry for Functional Materials

Biology Quantitative Research Topics For STEM Students

Systems Biology: Modeling Cellular Signaling Networks
Computational Neuroscience: Brain Network Analysis
Population Genetics and Evolutionary Dynamics
Mathematical Modeling of Infectious Diseases
Studying Protein Folding Using Computational Methods
Ecological Niche Modeling for Biodiversity Conservation
Quantitative Analysis of Gene Regulatory Networks
Metagenomics: Analyzing Microbial Communities
Bioinformatics Applications in Personalized Medicine
Integrative Biology: Understanding Multi-Omics Data

Engineering

Robotics and Autonomous Systems: Motion Planning Algorithms
Finite Element Analysis for Structural Engineering
Machine Learning in Image Processing and Computer Vision
Control Systems Engineering in Autonomous Vehicles
Renewable Energy Grid Integration and Optimization
Optimization of Transportation Networks
Analyzing Fluid Dynamics in Aerospace Engineering
Materials Science: Quantum Mechanics in Materials Design
Sustainable Infrastructure Planning and Design
Cyber-Physical Systems: Security and Resilience

Computer Science Quantitative Research Topics For STEM Students

Big Data Analytics: Scalable Algorithms for Data Processing
Natural Language Processing for Sentiment Analysis
Blockchain Technology: Security and Consensus Algorithms
Understanding How Quantum Computers Solve Problems
Creating AI Models that Explain Decisions for Help in Making Choices
Protecting Privacy While Mining Data
Keeping Networks Safe: Spotting Intruders
Making the Most of Cloud Computing: Sharing Resources Better
Humans and Robots Working Together Better
Improving How We Keep Secrets Safe with Quantum Cryptography

Earth and Environmental Sciences

Predicting How Weather Will Change in Different Areas
Using Maps and Data to Study the Environment
Managing Water and Predicting How Much We’ll Have
Looking at Pictures from Far Away to Watch the Environment
Studying Earthquakes and Where They Happen
Learning About the Ocean and How It Affects Weather
Checking How Green Energy Projects Affect the Environment
Measuring Soil Damage and How Nutrients Move
Looking at Air Quality and Figuring Out What’s Making It Bad
Seeing How Much Nature Helps Us Using Numbers

Agriculture and Food Sciences

Precision Agriculture: Using Data Analytics for Crop Management
Genetics and Genomics in Crop Improvement Strategies
Quantitative Analysis of Food Supply Chains
Agricultural Policy Analysis and Economic Modeling
Nutritional Analysis Using Quantitative Methods
Modeling Pesticide Use and Environmental Impact
Aquaculture: Optimization of Fish Farming Practices
Soil Fertility Modeling and Nutrient Management
Food Safety Assessment Using Quantitative Techniques
Sustainable Agriculture: Systems Modeling and Optimization

Health Sciences and Medicine: quantitative research topics in nursing

Epidemiology: Modeling Disease Transmission Dynamics
Healthcare Analytics: Predictive Modeling for Patient Outcomes
Pharmacokinetics and Drug Dosage Optimization
Health Informatics: Quantitative Analysis of Electronic Health Records
Medical Imaging Analysis Using Quantitative Techniques
Health Economics: Cost-Benefit Analysis of Healthcare Policies
Genomic Medicine: Analyzing Genetic Data for Disease Risk Prediction
Public Health Policy Evaluation Using Quantitative Methods
Biostatistics: Designing Clinical Trials and Statistical Analysis
Computational Anatomy for Disease Diagnosis and Treatment

Psychology and Social Sciences

Quantitative Analysis of Social Network Dynamics
Behavioral Economics: Decision-Making Models
Psychometrics: Measurement Models in Psychological Testing
Quantitative Study of Human Cognition and Memory
Social Media Analytics: Sentiment Analysis and Trends
Sociology: Modeling Social Movements and Cultural Dynamics
Educational Data Mining and Learning Analytics
Quantitative Research in Political Science and Policy Analysis
Consumer Behavior Analysis Using Quantitative Methods
Quantitative Approaches to Studying Emotion and Personality

Astronomy and Astrophysics

Cosmic Microwave Background Radiation: Analyzing Anisotropies
Time-domain Astronomy: Statistical Analysis of Variable Stars
Gravitational Lensing: Quantifying Distortions in Cosmic Images
Stellar Evolution Modeling and Simulations
Exoplanet Atmosphere Characterization Using Quantitative Methods
Galaxy Formation and Evolution: Statistical Approaches
Multimessenger Astronomy: Data Fusion Techniques
Dark Matter and Dark Energy: Analyzing Cosmological Models
Astrophysical Jets: Modeling High-Energy Particle Emissions
Supernova Studies: Quantitative Analysis of Stellar Explosions

Linguistics and Language Sciences

Computational Linguistics: Natural Language Generation Models
Phonetics and Speech Analysis Using Quantitative Techniques
Sociolinguistics: Statistical Analysis of Dialect Variation
Syntax and Grammar Modeling in Linguistic Theory
Quantitative Study of Language Acquisition in Children
Corpus Linguistics: Quantifying Textual Data
Language Typology and Universals: Cross-Linguistic Analysis
Psycholinguistics: Quantitative Study of Language Processing
Machine Translation: Improving Accuracy and Efficiency
Quantitative Approaches to Historical Linguistics

Business and Economics: quantitative research topics in education

Financial Risk Management: Quantitative Modeling of Risks
Econometrics: Statistical Methods in Economic Analysis
Marketing Analytics: Consumer Behavior Modeling
Quantitative Analysis of Macroeconomic Policies
Operations Research: Optimization in Supply Chain Management
Quantitative Methods in Corporate Finance
Labor Economics: Analyzing Employment Trends Using Data
Economic Impact Assessment of Policy Interventions
Quantitative Analysis of Market Dynamics and Competition
Behavioral Finance: Quantifying Psychological Aspects in Financial Decision-Making

Education and Pedagogy

Educational Data Mining for Adaptive Learning Systems
Quantitative Analysis of Learning Outcomes and Student Performance
Technology Integration in Education: Assessing Efficacy
Assessment and Evaluation Models in Educational Research
Quantitative Study of Teacher Effectiveness and Practices
Cognitive Load Theory: Quantifying Learning Processes
Educational Psychology: Quantitative Analysis of Motivation
Online Education: Analytics for Engagement and Success
Curriculum Development: Quantitative Approaches to Design
Educational Policy Analysis Using Quantitative Methods

Communication and Media Studies

Media Effects Research: Quantitative Analysis of Influence
Computational Journalism: Data-driven Storytelling
Social Media Influence Metrics and Analysis
Quantitative Study of Public Opinion and Opinion Formation
Media Content Analysis Using Statistical Methods
Communication Network Analysis: Quantifying Connections
Quantitative Approaches to Media Bias Assessment
Entertainment Analytics: Audience Behavior Modeling
Digital Media Consumption Patterns: Statistical Analysis
Crisis Communication: Quantitative Assessment of Responses

quantitative research topics for accounting students in the Philippines

Here are ten quantitative research topics suitable for accounting students in the Philippines:

“Impact of Tax Changes on Small and Medium Businesses (SMEs) in the Philippines: A Numbers-Based Study”
“Evaluating How Well Philippine Banks are Doing Financially: A Comparison Using Simple Measures”
“Checking How Good Internal Controls are at Stopping Fraud: Looking at Numbers in Filipino Businesses”
“Looking at How Companies in the Philippines are Run and How Well They’re Doing Financially”
“Figuring Out What Makes Auditing Good: A Study on Auditing in the Philippines”
“Seeing How Using Accounting Systems Helps Companies Work Better: A Study Using Numbers”
“Finding Out What Makes Financial Reports Good Quality in the Philippines: A Numbers Approach”
“Seeing How Following International Financial Reporting Standards (IFRS) Affects Philippine Companies”
“Studying What Factors Affect How Well College Students in the Philippines Understand Finances”
“Managing Money Flow and Keeping Small Businesses in the Philippines Stable: A Numbers-Based Look”

What are the 10 examples of research titles in school quantitative?

Here are ten examples of quantitative research titles suitable for school-related studies:

“Technology’s Influence on Grades: A Number-Based Look”
“How Class Size Affects How Well Students Learn: A Number Study”
“Parents Getting Involved and How Well Kids Do in School: A Numbers Look”
“Checking if Different Math Teaching Ways Work Well”
“Connecting How Much Students Get Into School with Test Scores”
“Bullying in Schools: Looking at How Much and How It Affects Grades”
“Looking at How Money Affects How Good Kids Are at Reading”
“Checking if Counseling Helps Kids’ Feelings: A Number Way”
“Do After-School Stuff Help Kids Do Better in School?”
“Seeing if a New Way to Grade is Better Than the Old Way: Comparing with Numbers”

Best experimental quantitative research topics for stem students in the Philippines

The following are the best quantitative research topics for stem students:

Biology Quantitative Research Topics

In the realm of Biology, quantitative research delves into the numerical aspects of living organisms, ecosystems, and genetics, aiding in understanding diverse biological phenomena.

Chemistry Quantitative Research Topics

Chemistry’s quantitative research explores numerical relationships within chemical reactions, material properties, and various compounds, offering insights into chemical phenomena through measurable data.

Physics Quantitative Research Topics

In Physics, quantitative research scrutinizes measurable physical quantities and their interactions, exploring fundamental principles and phenomena of the natural world.

Mathematics Quantitative Research Topics

Mathematics, in its quantitative research, investigates numerical patterns, structures, and mathematical theories, exploring the quantifiable aspects of various mathematical concepts.

We’ve investigated the marvels of utilizing numbers, information, and math to disentangle the secrets of science, innovation, design, and math. Quantitative research isn’t about staggering recipes or complex speculations. It’s tied in with utilizing straightforward math and measurements to grasp our general surroundings. Whether it’s anticipating the effect of environmental change, investigating how robots help medical services, or sorting out ways of making our urban communities greener, every point we’ve examined holds the potential for meaningful revelations.

As you proceed with your educational process, keep this interest alive. Embrace the delight of getting clarification on some pressing issues, testing, and investigating. Your passion for STEM subjects can prompt astounding things—from inventing innovations to tracking down answers for worldwide difficulties.

All in all, what’s next for you? Pick a topic that invigorates you, jump into the universe of quantitative exploration, and let your creative mind take off! Who knows, you’ll be the one to find something staggering that impacts the world.

Frequently Asked Questions

Can i conduct quantitative research in any stem field.

Yes, quantitative research methods can be applied across various STEM disciplines, including biology, chemistry, physics, computer science, environmental science, engineering, mathematics, and more.

Do I need advanced mathematical skills to conduct quantitative research in STEM?

While a solid understanding of mathematics is beneficial, many quantitative research projects in STEM can be conducted with basic mathematical principles. However, depending on the complexity of the topic and methods used, advanced mathematical skills may be necessary.

What tools and software are commonly used in quantitative research in STEM?

Common tools and software include statistical software such as R, Python (with libraries like NumPy and SciPy), MATLAB, SPSS, and Excel. Depending on the research topic, specialized software for data visualization, simulation, and mathematical modeling may also be used.

Best 101 Quantitative Research Topics for STEM Students

Are you a STEM (Science, Technology, Engineering, and Mathematics) student looking for exciting research topics? Well, you’ve come to the right place! Quantitative research can be both challenging and rewarding, but finding the right topic is the first step to success. In this blog, we’ve gathered 101 quantitative research topics in the easiest language possible to help you kickstart your research journey.

Table of Contents

101 Quantitative Research Topics for STEM Students

Biology research topics.

Effect of Temperature on Enzyme Activity: Investigate how different temperatures affect the efficiency of enzymes in biological reactions.
The Impact of Pollution on Aquatic Ecosystems: Analyze the correlation between pollution levels and the health of aquatic ecosystems.
Genetic Variability in Human Populations: Study the genetic diversity within different human populations and its implications.
Bacterial Resistance to Antibiotics: Examine how bacteria develop resistance to antibiotics and potential solutions.
Photosynthesis Efficiency in Different Light Conditions: Measure photosynthesis rates in various light conditions to understand plant adaptation.
Effect of pH Levels on Seed Germination: Investigate how different pH levels affect the germination of seeds.
Diversity of Insect Species in Urban vs. Rural Areas: Compare insect species diversity in urban and rural environments.
The Impact of Exercise on Heart Rate: Study how exercise affects heart rate and overall cardiovascular health.
Plant Growth in Response to Different Fertilizers: Analyze the growth of plants using different types of fertilizers.
Genetic Basis of Inherited Diseases: Explore the genetic mutations responsible for inherited diseases.

Chemistry Research Topics

Chemical Analysis of Water Sources: Investigate the composition of water from different sources and its suitability for consumption.
Stoichiometry of Chemical Reactions: Study the relationships between reactants and products in chemical reactions.
Kinetics of Chemical Reactions: Examine the speed and mechanisms of various chemical reactions.
The Impact of Temperature on Chemical Equilibrium: Analyze how temperature influences chemical equilibrium in reversible reactions.
Quantifying Air Pollution Levels: Measure air pollution components and their effects on human health.
Analysis of Food Additives: Investigate the safety and effects of common food additives.
Chemical Composition of Different Soils: Study the chemical properties of soils from different regions.
Electrochemical Cell Efficiency: Examine the efficiency of electrochemical cells in energy storage.
Quantitative Analysis of Drugs in Pharmaceuticals: Develop methods to quantify drug concentrations in pharmaceutical products.
Chemical Analysis of Renewable Energy Sources: Investigate the chemical composition of renewable energy sources like biofuels and solar cells.

Physics Research Topics

Quantum Mechanics and Entanglement: Explore the mysterious world of quantum entanglement and its applications.
The Physics of Black Holes: Study the properties and behavior of black holes in the universe.
Analysis of Superconductors: Investigate the phenomenon of superconductivity and its practical applications.
The Doppler Effect and its Applications: Explore the Doppler effect in various contexts, such as in astronomy and medicine.
Nanotechnology and Its Future: Analyze the potential of nanotechnology in various scientific fields.
The Behavior of Light Waves: Study the properties and behaviors of light waves, including diffraction and interference.
Quantifying Friction in Mechanical Systems: Measure and analyze friction in mechanical systems for engineering applications.
The Physics of Renewable Energy: Investigate the physics behind renewable energy sources like wind turbines and solar panels.
Particle Accelerators and High-Energy Physics: Explore the world of particle physics and particle accelerators.
Astrophysics and Dark Matter: Analyze the mysteries of dark matter and its role in the universe.

Mathematics Research Topics

Prime Number Distribution Patterns: Study the distribution of prime numbers and look for patterns.
Graph Theory and Network Analysis: Analyze real-world networks using graph theory techniques.
Optimization of Algorithms: Optimize algorithms for faster computation and efficiency.
Statistical Analysis of Economic Data: Apply statistical methods to analyze economic trends and data.
Mathematical Modeling of Disease Spread: Model the spread of diseases using mathematical equations.
Game Theory and Decision Making: Explore decision-making processes in strategic games.
Cryptographic Algorithms and Security: Study cryptographic algorithms and their role in data security.
Machine Learning and Predictive Analytics: Apply machine learning techniques to predict future events.
Number Theory and Cryptography: Investigate the mathematical foundations of cryptography.
Mathematics in Art and Design: Explore the intersection of mathematics and art through patterns and fractals.

Engineering Research Topics

Structural Analysis of Bridges: Evaluate the structural integrity of different types of bridges.
Renewable Energy Integration in Smart Grids: Study the integration of renewable energy sources in smart grid systems.
Materials Science and Composite Materials: Analyze the properties and applications of composite materials.
Robotics and Automation in Manufacturing: Explore the role of robotics in modern manufacturing processes.
Aerodynamics of Aircraft Design: Investigate the aerodynamics principles behind aircraft design.
Traffic Flow Analysis: Analyze traffic patterns and propose solutions for congestion.
Environmental Impact of Transportation: Study the environmental effects of various transportation methods.
Civil Engineering and Urban Planning: Explore solutions for urban development and infrastructure planning.
Biomechanics and Prosthetics: Study the mechanics of the human body and design prosthetic devices.
Environmental Engineering and Water Treatment: Investigate methods for efficient water treatment and pollution control.

Computer Science Research Topics

Machine Learning for Image Recognition: Develop algorithms for image recognition using machine learning.
Cybersecurity and Intrusion Detection: Study methods to detect and prevent cyber intrusions.
Natural Language Processing for Sentiment Analysis: Analyze sentiment in text data using natural language processing techniques.
Big Data Analytics and Predictive Modeling: Apply big data analytics to predict trends and make data-driven decisions.
Artificial Intelligence in Healthcare: Explore the applications of AI in diagnosing diseases and patient care.
Computer Vision and Autonomous Vehicles: Study computer vision techniques for autonomous vehicle navigation.
Quantum Computing and Cryptography: Investigate the potential of quantum computing in breaking current cryptographic systems.
Social Media Data Analysis: Analyze social media data to understand trends and user behavior.
Software Development for Accessibility: Develop software solutions for individuals with disabilities.
Virtual Reality and Simulation: Explore the use of virtual reality in simulations and training.

Environmental Science Research Topics

Climate Change and Sea-Level Rise: Study the effects of climate change on sea-level rise in coastal areas.
Ecosystem Restoration and Biodiversity: Explore methods to restore and conserve ecosystems and biodiversity.
Air Quality Monitoring in Urban Areas: Analyze air quality in urban environments and its health implications.
Sustainable Agriculture and Crop Yield: Investigate sustainable farming practices for improved crop yield.
Water Resource Management: Study methods for efficient water resource management and conservation.
Waste Management and Recycling: Analyze waste management strategies and recycling programs.
Natural Disaster Prediction and Mitigation: Develop models for predicting and mitigating natural disasters.
Renewable Energy and Environmental Impact: Investigate the environmental impact of renewable energy sources.
Climate Modeling and Predictions: Study climate models and make predictions about future climate changes.
Pollution Control and Remediation Techniques: Explore methods to control and remediate various types of pollution.

Psychology Research Topics

Effects of Social Media on Mental Health: Analyze the relationship between social media usage and mental health.
Cognitive Development in Children: Study cognitive development in children and its factors.
The Impact of Stress on Academic Performance: Analyze how stress affects academic performance.
Gender Differences in Decision-Making: Investigate gender-related variations in decision-making processes.
Psychological Factors in Addiction: Study the psychological factors contributing to addiction.
Perception and Memory in Aging: Explore changes in perception and memory as people age.
Cross-Cultural Psychological Studies: Compare psychological phenomena across different cultures.
Positive Psychology and Well-Being: Investigate factors contributing to overall well-being and happiness.
Emotional Intelligence and Leadership: Study the relationship between emotional intelligence and effective leadership.
Psychological Effects of Virtual Reality: Analyze the psychological impact of immersive virtual reality experiences.

Earth Science Research Topics

Volcanic Activity and Predictions: Study volcanic eruptions and develop prediction models.
Plate Tectonics and Earthquakes: Analyze the movement of tectonic plates and earthquake patterns.
Geomorphology and Landscape Evolution: Investigate the processes shaping Earth’s surface.
Glacial Retreat and Climate Change: Study the retreat of glaciers and its connection to climate change.
Mineral Exploration and Resource Management: Explore methods for mineral resource exploration and sustainable management.
Meteorology and Weather Forecasting: Analyze weather patterns and improve weather forecasting accuracy.
Oceanography and Marine Life: Study marine ecosystems, ocean currents, and their impact on marine life.
Soil Erosion and Conservation: Investigate soil erosion processes and conservation techniques.
Remote Sensing and Earth Observation: Use remote sensing technology to monitor Earth’s surface changes.
Geographic Information Systems (GIS) Applications: Apply GIS technology for various geographical analyses.

Materials Science Research Topics

Nanomaterials for Drug Delivery: Investigate the use of nanomaterials for targeted drug delivery.
Superconducting Materials and Energy Efficiency: Study materials with superconducting properties for energy applications.
Advanced Composite Materials for Aerospace: Analyze advanced composites for lightweight aerospace applications.
Solar Cell Efficiency Improvement: Investigate materials for more efficient solar cell technology .
Biomaterials and Medical Implants: Explore materials used in medical implants and their biocompatibility.
Smart Materials for Electronics: Study materials that can change their properties in response to external stimuli.
Materials for Energy Storage: Analyze materials for improved energy storage solutions.
Quantum Dots in Display Technology: Investigate the use of quantum dots in display technology.
Materials for 3D Printing: Explore materials suitable for 3D printing in various industries.
Materials for Water Purification: Study materials used in water purification processes.
Data Analysis of Social Media Trends: Explore the quantitative analysis of social media trends to understand their impact on society and marketing strategies.

There you have it—101 quantitative research topics for STEM students! Remember that the key to a successful research project is choosing a topic that genuinely interests you. Whether you’re passionate about biology, chemistry, physics, mathematics, engineering, computer science, environmental science, psychology, or earth science, there’s a quantitative research topic waiting for you to explore. So, roll up your sleeves, gather your data, and embark on your research journey with enthusiasm.

60+ Best Quantitative Research Topics for STEM Students: Dive into Data

Embark on a captivating journey through the cosmos of knowledge with our curated guide on Quantitative Research Topics for STEM Students. Explore innovative ideas in science, technology, engineering, and mathematics, designed to ignite curiosity and shape the future.

Unleash the power of quantitative research and dive into uncharted territories that go beyond academics, fostering innovation and discovery.

Hey, you future scientists, tech wizards, engineering maestros, and math superheroes – gather ’round! We’re about to dive headfirst into the rad world of quantitative research topics, tailor-made for the rockstars of STEM.

In the crazy universe of science, technology, engineering, and math (STEM), quantitative research isn’t just a nerdy term—it’s your VIP pass to an interstellar adventure. Picture this: you’re strapping into a rocket ship, zooming through the cosmos, and decoding the universe’s coolest secrets, all while juggling numbers like a cosmic DJ.

But here’s the real scoop: finding the ultimate research topic is like picking the juiciest star in the galaxy. It’s about stumbling upon something so mind-blowing that you can’t resist plunging into the data. It’s about choosing questions that make your STEM-loving heart do the cha-cha.

In this guide, we’re not just your sidekicks; we’re your partners in crime through the vast jungle of quantitative research topics. Whether you’re a rookie gearing up for your first lab escapade or a seasoned explorer hunting for a new thrill, think of this article as your treasure map, guiding you to the coolest STEM discoveries.

From the teeny wonders of biology to the brain-bending puzzles of physics, the cutting-edge vibes of engineering, and the downright gorgeous dance of mathematics – we’ve got your back.

So, buckle up, fellow STEM enthusiasts! We’re setting sail on a cosmic adventure through the groovy galaxy of quantitative research topics. Get ready to unravel the secrets of science and tech, one sizzling digit at a time.

Stick around for a ride that’s part data, part disco, and all STEM swagger!

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Benefits of Choosing Quantitative Research

Embarking on the quantitative research journey is like stepping into a treasure trove of benefits across a spectrum of fields. Let’s dive into the exciting advantages that make choosing quantitative research a game-changer:

Numbers That Speak Louder

Quantitative research deals in cold, hard numbers. This means your data isn’t just informative; it’s objective, measurable, and has a voice of its own.

Statistical Swagger

Crunching numbers isn’t just for show. With quantitative research, statistical tools add a touch of pizzazz, boosting the validity of your findings and turning your study into a credible performance.

For the Masses

Quantitative research loves a crowd. Larger sample sizes mean your discoveries aren’t just for the lucky few – they’re for everyone. It’s the science of sharing the knowledge wealth.

Data Showdown

Ready for a duel between variables? Quantitative research sets the stage for epic battles, letting you compare, contrast, and uncover cause-and-effect relationships in the data arena.

Structured and Ready to Roll

Think of quantitative research like a well-organized party. It follows a structured plan, making replication a breeze. Because who doesn’t love a party that’s easy to recreate?

Data Efficiency Dance

Efficiency is the name of the game. Surveys, experiments, and structured observations make data collection a dance – choreographed, smooth, and oh-so-efficient.

Data Clarity FTW

No decoding needed here. Quantitative research delivers crystal-clear results. It’s like reading a good book without the need for interpretation – straightforward and to the point.

Spotting Trends Like a Pro

Ever wish you had a crystal ball for trends? Quantitative analysis is the next best thing. It’s like having a trend-spotting superpower, revealing patterns that might have otherwise stayed hidden.

Bias Be Gone

Quantitative research takes bias out of the equation. Systematic data collection and statistical wizardry reduce researcher bias, leaving you with results that are as unbiased as a judge at a talent show.

Key Components of a Quantitative Research Study

Launching into a quantitative research study is like embarking on a thrilling quest, and guess what? You’re the hero of this research adventure! Let’s unravel the exciting components that make your study a blockbuster:

Quest-Starter: Research Question or Hypothesis

It’s your “once upon a time.” Kick off your research journey with a bang by crafting a captivating research question or hypothesis. This is the spark that ignites your curiosity.

Backstory Bonanza: Literature Review

Think of it as your research Netflix binge. Dive into existing literature for the backstory. It’s not just research – it’s drama, plot twists, and the foundation for your epic tale.

Blueprint Brilliance: Research Design

Time to draw up the plans for your study castle. Choose your research design – is it a grand experiment or a cunning observational scheme? Your design is the architectural genius behind your research.

Casting Call: Population and Sample

Who’s in your star-studded lineup? Define your dream cast – your target population – and then handpick a sample that’s ready for the research red carpet.

Gear Up: Data Collection Methods

Choose your research tools wisely – surveys, experiments, or maybe a bit of detective work. Your methods are like the gadgets in a spy movie, helping you collect the data treasures.

The Numbers Game: Variables and Measures

What’s in the spotlight? Identify your main characters – independent and dependent variables. Then, sprinkle in some measures to add flair and precision to your study.

Magic Analysis Wand: Data Analysis Techniques

Enter the wizardry zone! Pick your magic wand – statistical methods, tests, or software – and watch as it unravels the mysteries hidden in your data.

Ethical Superhero Cape: Ethical Considerations

Every hero needs a moral compass. Clearly outline how you’ll be the ethical superhero of your study, protecting the well-being and secrets of your participants.

Grand Finale: Results and Findings

It’s showtime! Showcase your results like the grand finale of a fireworks display. Tables, charts, and statistical dazzle – let your findings steal the spotlight.

Wrap-Up Party: Conclusion and Implications

Bring out the confetti! Summarize your findings, discuss their VIP status in the research world, and hint at the afterparty – how your results shape the future.

Behind-the-Scenes Blooper Reel: Limitations and Future Research

No Hollywood film is perfect. Share the bloopers – the limitations of your study – and hint at the sequel with ideas for future research. It’s all part of the cinematic journey.

Roll Credits: References

Give a shout-out to the supporting cast! Cite your sources – it’s the credits that add credibility to your blockbuster.

Bonus Scene: Appendix

Think of it as the post-credits scene. Tuck in any extra goodies – surveys, questionnaires, or behind-the-scenes material – for those eager to dive deeper into your research universe.

By weaving these storylines together, your quantitative research study becomes a cinematic masterpiece, leaving a lasting impact on the grand stage of academia. Happy researching, hero!

Quantitative Research Topics for STEM Students

Check out the best quantitative research topics for STEM students:-

Investigating the Effects of Different Soil pH Levels on Plant Growth.
Analyzing the Impact of Pesticide Exposure on Bee Populations.
Studying the Genetic Variability in Endangered Species.
Quantifying the Relationship Between Temperature and Microbial Growth in Water.
Analyzing the Effects of Ocean Acidification on Coral Reefs.
Investigating the Correlation Between Pollinator Diversity and Crop Yield.
Studying the Role of Gut Microbiota in Human Health and Disease.
Quantifying the Impact of Antibiotics on Soil Microbial Communities.
Analyzing the Effects of Light Pollution on Nocturnal Animal Behavior.
Investigating the Relationship Between Altitude and Plant Adaptations in Mountain Ecosystems.
Measuring the Speed of Light Using Interferometry Techniques.
Investigating the Quantum Properties of Photons in Quantum Computing.
Analyzing the Factors Affecting Magnetic Field Strength in Electromagnets.
Studying the Behavior of Superfluids at Ultra-Low Temperatures.
Quantifying the Efficiency of Energy Transfer in Photovoltaic Cells.
Analyzing the Properties of Quantum Dots for Future Display Technologies.
Investigating the Behavior of Particles in High-Energy Particle Accelerators.
Studying the Effects of Gravitational Waves on Space-Time.
Quantifying the Frictional Forces on Objects at Different Surfaces.
Analyzing the Characteristics of Dark Matter and Dark Energy in the Universe.

Engineering

Optimizing the Design of Wind Turbine Blades for Maximum Efficiency.
Investigating the Use of Smart Materials in Structural Engineering.
Analyzing the Impact of 3D Printing on Prototyping in Product Design.
Studying the Behavior of Composite Materials Under Extreme Temperatures.
Evaluating the Efficiency of Water Treatment Plants in Removing Contaminants.
Investigating the Aerodynamics of Drones for Improved Flight Control.
Quantifying the Effects of Traffic Flow on Roadway Maintenance.
Analyzing the Impact of Vibration Damping in Building Structures.
Studying the Mechanical Properties of Biodegradable Polymers in Medical Devices.
Investigating the Use of Artificial Intelligence in Autonomous Robotic Systems.

Mathematics

Exploring Chaos Theory and Its Applications in Nonlinear Systems.
Modeling the Spread of Infectious Diseases in Population Dynamics.
Analyzing Data Mining Techniques for Predictive Analytics in Business.
Studying the Mathematics of Cryptography Algorithms for Data Security.
Quantifying the Patterns in Stock Market Price Movements Using Time Series Analysis.
Investigating the Applications of Fractal Geometry in Computer Graphics.
Analyzing the Behavior of Differential Equations in Climate Modeling.
Studying the Optimization of Supply Chain Networks Using Linear Programming.
Investigating the Mathematical Concepts Behind Machine Learning Algorithms.
Quantifying the Patterns of Prime Numbers in Number Theory.
Investigating the Chemical Mechanisms Behind Enzyme Catalysis.
Analyzing the Thermodynamic Properties of Chemical Reactions.
Studying the Kinetics of Chemical Reactions in Different Solvents.
Quantifying the Concentration of Pollutants in Urban Air Quality.
Evaluating the Effectiveness of Antioxidants in Food Preservation.
Investigating the Electrochemical Properties of Batteries for Energy Storage.
Studying the Behavior of Nanomaterials in Drug Delivery Systems.
Analyzing the Chemical Composition of Exoplanet Atmospheres Using Spectroscopy.
Quantifying Heavy Metal Contamination in Soil and Water Sources.
Investigating the Correlation Between Chemical Exposure and Human Health.

Computer Science

Analyzing Machine Learning Algorithms for Natural Language Processing.
Investigating Quantum Computing Algorithms for Cryptography Applications.
Studying the Efficiency of Data Compression Methods for Big Data Storage.
Quantifying Cybersecurity Threats and Vulnerabilities in IoT Devices.
Evaluating the Impact of Cloud Computing on Distributed Systems.
Investigating the Use of Artificial Intelligence in Autonomous Vehicles.
Analyzing the Behavior of Neural Networks in Deep Learning Applications.
Studying the Performance of Blockchain Technology in Supply Chain Management.
Quantifying User Behavior in Social Media Analytics.
Investigating Quantum Machine Learning for Enhanced Data Processing.

These additional project ideas provide a diverse range of opportunities for STEM students to engage in quantitative research and explore various aspects of their respective fields. Each project offers a unique avenue for discovery and contribution to the world of science and technology.

What is an example of a quantitative research?

Quantitative research is a powerful investigative approach, wielding numbers to shed light on intricate relationships and phenomena. Let’s dive into an example of quantitative research to understand its workings:

Research Question

What is the correlation between the time students devote to studying and their academic grades?

Students who invest more time in studying are likely to achieve higher grades.

Research Design

Imagine a researcher embarking on a journey within a high school. They distribute surveys to students, inquiring about their weekly study hours and their corresponding grades in core subjects.

Data Analysis

Equipped with statistical tools, our researcher scrutinizes the collected data. Lo and behold, a significant positive correlation emerges—students who dedicate more time to studying generally earn higher grades.

With data as their guide, the researcher concludes that indeed, a relationship exists between study time and academic grades. The more time students commit to their studies, the brighter their academic stars tend to shine.

This example merely scratches the surface of quantitative research’s potential. It can delve into an extensive array of subjects and investigate complex hypotheses. Here are a few more examples:

Assessing a New Drug’s Effectiveness: Quantifying the impact of a novel medication in treating a specific illness.
Socioeconomic Status and Crime Rates: Investigating the connection between economic conditions and criminal activity.
Analyzing the Influence of an Advertising Campaign on Sales: Measuring the effectiveness of a marketing blitz on product purchases.
Factors Shaping Customer Satisfaction: Using data to pinpoint the elements contributing to customer contentment.
Government Policies and Employment Rates: Evaluating the repercussions of new governmental regulations on job opportunities.

Quantitative research serves as a potent beacon, illuminating the complexities of our world through data-driven inquiry. Researchers harness its might to collect, analyze, and draw valuable conclusions about a vast spectrum of phenomena. It’s a vital tool for unraveling the intricacies of our universe.

As we bid adieu to our whirlwind tour of quantitative research topics tailor-made for the STEM dreamers, it’s time to soak in the vast horizons that science, technology, engineering, and mathematics paint for us.

We’ve danced through the intricate tango of poverty and crime, peeked into the transformative realm of cutting-edge technologies, and unraveled the captivating puzzles of quantitative research. But these aren’t just topics; they’re open invitations to dive headfirst into the uncharted seas of knowledge.

To you, the STEM trailblazers, these research ideas aren’t mere academic pursuits. They’re portals to curiosity, engines of innovation, and blueprints for shaping the future of our world. They’re the sparks that illuminate the trail leading to discovery.

As you set sail on your research odyssey, remember that quantitative research isn’t just about unlocking answers—it’s about nurturing that profound sense of wonder, igniting innovation, and weaving your unique thread into the fabric of human understanding.

Whether you’re stargazing, decoding the intricate language of genes, engineering marvels, or tackling global challenges head-on, realize that your STEM and quantitative research journey is a perpetual adventure.

May your questions be audacious, your data razor-sharp, and your discoveries earth-shattering. Keep that innate curiosity alive, keep exploring, and let the spirit of STEM be your North Star, guiding you towards a future that’s not just brighter but brilliantly enlightened.

And with that, fellow adventurers, go forth, embrace the unknown, and let your journey in STEM be the epic tale that reshapes the narrative of tomorrow!

Frequently Asked Questions

How can i ensure the ethical conduct of my quantitative research project.

To ensure ethical conduct, obtain informed consent from participants, maintain data confidentiality, and adhere to ethical guidelines established by your institution and professional associations.

Are there any software tools recommended for data analysis in STEM research?

Yes, there are several widely used software tools for data analysis in STEM research, including R, Python, MATLAB, and SPSS. The choice of software depends on your specific research needs and familiarity with the tools.

100+ Quantitative Research Topics For Students

Quantitative research is a research strategy focusing on quantified data collection and analysis processes. This research strategy emphasizes testing theories on various subjects. It also includes collecting and analyzing non-numerical data.

Quantitative research is a common approach in the natural and social sciences , like marketing, business, sociology, chemistry, biology, economics, and psychology. So, if you are fond of statistics and figures, a quantitative research title would be an excellent option for your research proposal or project.

How to Get a Title of Quantitative Research

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Finding a great title is the key to writing a great quantitative research proposal or paper. A title for quantitative research prepares you for success, failure, or mediocre grades. This post features examples of quantitative research titles for all students.

Putting together a research title and quantitative research design is not as easy as some students assume. So, an example topic of quantitative research can help you craft your own. However, even with the examples, you may need some guidelines for personalizing your research project or proposal topics.

So, here are some tips for getting a title for quantitative research:

Consider your area of studies
Look out for relevant subjects in the area
Expert advice may come in handy
Check out some sample quantitative research titles

Making a quantitative research title is easy if you know the qualities of a good title in quantitative research. Reading about how to make a quantitative research title may not help as much as looking at some samples. Looking at a quantitative research example title will give you an idea of where to start.

However, let’s look at some tips for how to make a quantitative research title:

The title should seem interesting to readers
Ensure that the title represents the content of the research paper
Reflect on the tone of the writing in the title
The title should contain important keywords in your chosen subject to help readers find your paper
The title should not be too lengthy
It should be grammatically correct and creative
It must generate curiosity

An excellent quantitative title should be clear, which implies that it should effectively explain the paper and what readers can expect. A research title for quantitative research is the gateway to your article or proposal. So, it should be well thought out. Additionally, it should give you room for extensive topic research.

A sample of quantitative research titles will give you an idea of what a good title for quantitative research looks like. Here are some examples:

What is the correlation between inflation rates and unemployment rates?
Has climate adaptation influenced the mitigation of funds allocation?
Job satisfaction and employee turnover: What is the link?
A look at the relationship between poor households and the development of entrepreneurship skills
Urbanization and economic growth: What is the link between these elements?
Does education achievement influence people’s economic status?
What is the impact of solar electricity on the wholesale energy market?
Debt accumulation and retirement: What is the relationship between these concepts?
Can people with psychiatric disorders develop independent living skills?
Children’s nutrition and its impact on cognitive development

Quantitative research applies to various subjects in the natural and social sciences. Therefore, depending on your intended subject, you have numerous options. Below are some good quantitative research topics for students:

The difference between the colorific intake of men and women in your country
Top strategies used to measure customer satisfaction and how they work
Black Friday sales: are they profitable?
The correlation between estimated target market and practical competitive risk assignment
Are smartphones making us brighter or dumber?
Nuclear families Vs. Joint families: Is there a difference?
What will society look like in the absence of organized religion?
A comparison between carbohydrate weight loss benefits and high carbohydrate diets?
How does emotional stability influence your overall well-being?
The extent of the impact of technology in the communications sector

Creativity is the key to creating a good research topic in quantitative research. Find a good quantitative research topic below:

How much exercise is good for lasting physical well-being?
A comparison of the nutritional therapy uses and contemporary medical approaches
Does sugar intake have a direct impact on diabetes diagnosis?
Education attainment: Does it influence crime rates in society?
Is there an actual link between obesity and cancer rates?
Do kids with siblings have better social skills than those without?
Computer games and their impact on the young generation
Has social media marketing taken over conventional marketing strategies?
The impact of technology development on human relationships and communication
What is the link between drug addiction and age?

Need more quantitative research title examples to inspire you? Here are some quantitative research title examples to look at:

Habitation fragmentation and biodiversity loss: What is the link?
Radiation has affected biodiversity: Assessing its effects
An assessment of the impact of the CORONA virus on global population growth
Is the pandemic truly over, or have human bodies built resistance against the virus?
The ozone hole and its impact on the environment
The greenhouse gas effect: What is it and how has it impacted the atmosphere
GMO crops: are they good or bad for your health?
Is there a direct link between education quality and job attainment?
How have education systems changed from traditional to modern times?
The good and bad impacts of technology on education qualities

Your examiner will give you excellent grades if you come up with a unique title and outstanding content. Here are some quantitative research examples titles.

Online classes: are they helpful or not?
What changes has the global CORONA pandemic had on the population growth curve?
Daily habits influenced by the global pandemic
An analysis of the impact of culture on people’s personalities
How has feminism influenced the education system’s approach to the girl child’s education?
Academic competition: what are its benefits and downsides for students?
Is there a link between education and student integrity?
An analysis of how the education sector can influence a country’s economy
An overview of the link between crime rates and concern for crime
Is there a link between education and obesity?

Research title example quantitative topics when well-thought guarantees a paper that is a good read. Look at the examples below to get started.

What are the impacts of online games on students?
Sex education in schools: how important is it?
Should schools be teaching about safe sex in their sex education classes?
The correlation between extreme parent interference on student academic performance
Is there a real link between academic marks and intelligence?
Teacher feedback: How necessary is it, and how does it help students?
An analysis of modern education systems and their impact on student performance
An overview of the link between academic performance/marks and intelligence
Are grading systems helpful or harmful to students?
What was the impact of the pandemic on students?

Irrespective of the course you take, here are some titles that can fit diverse subjects pretty well. Here are some creative quantitative research title ideas:

A look at the pre-corona and post-corona economy
How are conventional retail businesses fairing against eCommerce sites like Amazon and Shopify?
An evaluation of mortality rates of heart attacks
Effective treatments for cardiovascular issues and their prevention
A comparison of the effectiveness of home care and nursing home care
Strategies for managing effective dissemination of information to modern students
How does educational discrimination influence students’ futures?
The impacts of unfavorable classroom environment and bullying on students and teachers
An overview of the implementation of STEM education to K-12 students
How effective is digital learning?

If your paper addresses a problem, you must present facts that solve the question or tell more about the question. Here are examples of quantitative research titles that will inspire you.

An elaborate study of the influence of telemedicine in healthcare practices
How has scientific innovation influenced the defense or military system?
The link between technology and people’s mental health
Has social media helped create awareness or worsened people’s mental health?
How do engineers promote green technology?
How can engineers raise sustainability in building and structural infrastructures?
An analysis of how decision-making is dependent on someone’s sub-conscious
A comprehensive study of ADHD and its impact on students’ capabilities
The impact of racism on people’s mental health and overall wellbeing
How has the current surge in social activism helped shape people’s relationships?

Are you looking for an example of a quantitative research title? These ten examples below will get you started.

The prevalence of nonverbal communication in social control and people’s interactions
The impacts of stress on people’s behavior in society
A study of the connection between capital structures and corporate strategies
How do changes in credit ratings impact equality returns?
A quantitative analysis of the effect of bond rating changes on stock prices
The impact of semantics on web technology
An analysis of persuasion, propaganda, and marketing impact on individuals
The dominant-firm model: what is it, and how does it apply to your country’s retail sector?
The role of income inequality in economy growth
An examination of juvenile delinquents’ treatment in your country

Excellent Topics For Quantitative Research

Here are some titles for quantitative research you should consider:

Does studying mathematics help implement data safety for businesses
How are art-related subjects interdependent with mathematics?
How do eco-friendly practices in the hospitality industry influence tourism rates?
A deep insight into how people view eco-tourisms
Religion vs. hospitality: Details on their correlation
Has your country’s tourist sector revived after the pandemic?
How effective is non-verbal communication in conveying emotions?
Are there similarities between the English and French vocabulary?
How do politicians use persuasive language in political speeches?
The correlation between popular culture and translation

Here are some quantitative research titles examples for your consideration:

How do world leaders use language to change the emotional climate in their nations?
Extensive research on how linguistics cultivate political buzzwords
The impact of globalization on the global tourism sector
An analysis of the effects of the pandemic on the worldwide hospitality sector
The influence of social media platforms on people’s choice of tourism destinations
Educational tourism: What is it and what you should know about it
Why do college students experience math anxiety?
Is math anxiety a phenomenon?
A guide on effective ways to fight cultural bias in modern society
Creative ways to solve the overpopulation issue

An example of quantitative research topics for 12 th -grade students will come in handy if you want to score a good grade. Here are some of the best ones:

The link between global warming and climate change
What is the greenhouse gas impact on biodiversity and the atmosphere
Has the internet successfully influenced literacy rates in society
The value and downsides of competition for students
A comparison of the education system in first-world and third-world countries
The impact of alcohol addiction on the younger generation
How has social media influenced human relationships?
Has education helped boost feminism among men and women?
Are computers in classrooms beneficial or detrimental to students?
How has social media improved bullying rates among teenagers?

High school students can apply research titles on social issues or other elements, depending on the subject. Let’s look at some quantitative topics for students:

What is the right age to introduce sex education for students
Can extreme punishment help reduce alcohol consumption among teenagers?
Should the government increase the age of sexual consent?
The link between globalization and the local economy collapses
How are global companies influencing local economies?

There are numerous possible quantitative research topics you can write about. Here are some great quantitative research topics examples:

The correlation between video games and crime rates
Do college studies impact future job satisfaction?
What can the education sector do to encourage more college enrollment?
The impact of education on self-esteem
The relationship between income and occupation

You can find inspiration for your research topic from trending affairs on social media or in the news. Such topics will make your research enticing. Find a trending topic for quantitative research example from the list below:

How the country’s economy is fairing after the pandemic
An analysis of the riots by women in Iran and what the women gain to achieve
Is the current US government living up to the voter’s expectations?
How is the war in Ukraine affecting the global economy?
Can social media riots affect political decisions?

A proposal is a paper you write proposing the subject you would like to cover for your research and the research techniques you will apply. If the proposal is approved, it turns to your research topic. Here are some quantitative titles you should consider for your research proposal:

Military support and economic development: What is the impact in developing nations?
How does gun ownership influence crime rates in developed countries?
How can the US government reduce gun violence without influencing people’s rights?
What is the link between school prestige and academic standards?
Is there a scientific link between abortion and the definition of viability?

You can never have too many sample titles. The samples allow you to find a unique title you’re your research or proposal. Find a sample quantitative research title here:

Does weight loss indicate good or poor health?
Should schools do away with grading systems?
The impact of culture on student interactions and personalities
How can parents successfully protect their kids from the dangers of the internet?
Is the US education system better or worse than Europe’s?

If you’re a business major, then you must choose a research title quantitative about business. Let’s look at some research title examples quantitative in business:

Creating shareholder value in business: How important is it?
The changes in credit ratings and their impact on equity returns
The importance of data privacy laws in business operations
How do businesses benefit from e-waste and carbon footprint reduction?
Organizational culture in business: what is its importance?

We Are A Call Away

Interesting, creative, unique, and easy quantitative research topics allow you to explain your paper and make research easy. Therefore, you should not take choosing a research paper or proposal topic lightly. With your topic ready, reach out to us today for excellent research paper writing services .

Research and trends in STEM education: a systematic analysis of publicly funded projects

Yeping Li 1 ,
Ke Wang 2 ,
Yu Xiao 1 ,
Jeffrey E. Froyd 3 &
Sandra B. Nite 1

International Journal of STEM Education volume 7 , Article number: 17 ( 2020 ) Cite this article

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Taking publicly funded projects in STEM education as a special lens, we aimed to learn about research and trends in STEM education. We identified a total of 127 projects funded by the Institute of Education Sciences (IES) of the US Department of Education from 2003 to 2019. Both the number of funded projects in STEM education and their funding amounts were high, although there were considerable fluctuations over the years. The number of projects with multiple principal investigators increased over time. The project duration was typically in the range of 3–4 years, and the goals of these projects were mostly categorized as “development and innovation” or “efficacy and replication.” The majority of the 127 projects focused on individual STEM disciplines, especially mathematics. The findings, based on IES-funded projects, provided a glimpse of the research input and trends in STEM education in the USA, with possible implications for developing STEM education research in other education systems around the world.

Introduction

The rapid development of science, technology, engineering, and mathematics (STEM) education and research since the beginning of this century has benefited from strong, ongoing support from many different entities, including government agencies, professional organizations, industries, and education institutions (Li, 2014 ). Typically, studies that summarized the status of research in STEM education have used publications as the unit of their analyses (e.g., Li et al., 2019 ; Li et al., 2020 ; Margot & Kettler, 2019 ; Minichiello et al., 2018 ; Otten, Van den Heuvel-Panhuizen, & Veldhuis, 2019 ; Schreffler et al., 2019 ). Another approach, which has been used less frequently, is to study research funding. Although not all research publications were generated from funded projects and not all funded projects have been equally productive, as measured by publications, research funding and publications present two different, but related perspectives on the state of research in STEM education. Our review focuses on research funding.

Types of funding support to education research

There are different types of sources and mechanisms in place to allocate, administer, distribute, and manage funding support to education. In general, there are two sources of funding: public and private.

Public funding sources are commonly government agencies that support education program development and training, project evaluation, and research. For example, multiple state and federal agencies in the USA provide and manage funding support to education research, programs and training, including the US Department of Education (ED), the National Science Foundation (NSF), and the National Endowment for the Humanities—Division of Education Programs. Researchers seeking support from public funding sources often submit proposals that are vetted through a well-structured peer-review process. The process is competitive, and the decision to fund a project validates both its importance and alignment with the funding agency’s development agenda. Changes in the agencies’ agendas and funding priorities can reflect governmental intentions and priorities for education and research.

Private funding sources have played a very important role in supporting education programs and research with a long history. Some private funding sources in the USA can be sizeable, such as the Bill & Melinda Gates Foundation ( https://www.gatesfoundation.org ), while many also have specific foci, such as the Howard Hughes Medical Institute ( https://www.hhmi.org ) that is dedicated to advancing science through research and science education. At the same time, private funding sources often have their own development agendas, flexibility in deciding funding priorities, and specific mechanisms in making funding decisions, including how funds can be used, distributed, and managed. Indeed, private funding sources differ from public funding sources in many ways. Given many special features associated with private funding sources, including the lack of transparency, we chose to examine projects that were supported by public funding sources in this review.

Approaches to examining public research funding support

One approach to studying public research funding support to STEM education would be to examine requests-for-proposals (RFPs) issued by different government agencies. However, those RFPs tend to provide guidelines, which are not sufficiently concrete to learn about specific research that is funded. In contrast, reviewing those projects selected for funding can provide more detailed information on research activity. Figure 1 shows a flowchart of research activity and distinguishes how funded projects and publications might provide different perspectives on research. In this review, we focus on the bolded portion of the flowchart, i.e., projects funded to promote STEM education.

A general flowchart of RFPs to publications

Current review

Why focus on research funding in the usa.

Recent reviews of journal publications in STEM education have consistently revealed that scholars in the USA played a leading role in producing and promoting scholarship in STEM education, with about 75% of authorship credits for all publications in STEM education either in the International Journal of STEM Education alone from 2014 to 2018 (Li et al., 2019 ) or in 36 selected journals published from 2000 to 2018 (Li et al., 2020 ). The strong scholarship development in the USA is likely due to a research environment that is well supported and conducive to high research output. Studying public funding support for STEM education research in the USA will provide information on trends and patterns, which will be valuable both in the USA and in other countries.

The context of policy and public funding support to STEM education in the USA

The tremendous development of STEM education in the USA over the past decades has benefited greatly from both national policies and strong funding support from the US governmental agencies as well as private funding sources. Federal funding for research and development in science, mathematics, technology, and engineering-related education in the USA was restarted in the late 1980s, in the latter years of the Reagan administration, which had earlier halted funding. In recent years, the federal government has strongly supported STEM education research and development. For example, the Obama administration in the USA (The White House, 2009 ) launched the “Educate to Innovate” campaign in November 2009 for excellence in STEM education as a national priority, with over 260 million USD in financial and in-kind support commitment. The Trump administration has continued to emphasize STEM education. For example, President Trump signed a memorandum in 2017 to direct ED to spend 200 million USD per year on competitive grants promoting STEM (The White House, 2017 ). In response, ED awarded 279 million USD in STEM discretionary grants in Fiscal Year 2018 (US Department of Education, 2018 ). The Trump administration took a step further to release a report in December 2018 detailing its five-year strategic plan of boosting STEM education in the USA (The White House, 2018 ). The strategic plan envisions that “All Americans will have lifelong access to high-quality STEM education and the USA will be the global leader in STEM literacy, innovation, and employment.” (Committee on STEM Education, 2018 , p. 1). Consistently, current Secretory of Education DeVos in the Trump administration has taken STEM as a centerpiece of her comprehensive education agenda (see https://www.ed.gov/stem ). The consistency in national policies and public funding support shows that STEM education continues to be a strategic priority in the USA.

Among many federal agencies that funded STEM education programs, the ED and NSF have functioned as two primary agencies. For ED, the Institute of Education Sciences (Institute of Education Sciences (IES), n.d. , see https://ies.ed.gov/aboutus/ ) was created by the Education Sciences Reform Act of 2002 as its statistics, research, and evaluation arm. ED’s support to STEM education research has been mainly administered and managed by IES since 2003. In contrast to the focus of ED on education, NSF (see https://www.nsf.gov/about/ ) was created by Congress in 1950 to support basic research in many fields such as mathematics, computer sciences, and social sciences. Education and Human Resources is one of its seven directorates that provides important funding support to STEM education programs and research. In addition to these two federal agencies, some other federal agencies also provide funding support to STEM education programs and research from time to time.

Any study of public funding support to STEM education research in the USA would need to limit its scope, given the complexity of various public funding sources available in the system, the ambiguity associated with the meaning of STEM education across different federal agencies (Li et al., 2020 ), and the number of programs that have funded STEM education research over the years. For the purpose of this review, we have chosen to focus on the projects in STEM education funded by IES.

Research questions

Given the preceding research approach decision to focus on research projects funded by IES, we generated the following questions:

What were the number of projects, total project funding, and the average funding per project from 2003 to 2019 in STEM education research?

What were the trends of having single versus multiple principal investigator(s) in STEM education?

What were the types of awardees of the projects?

What were the participant populations in the projects?

What were the types of projects in terms of goals for program development and research in STEM education?

What were the disciplinary foci of the projects?

What research methods did projects tend to use in conducting STEM education research?

Based on the above discussion to focus on funding support from IES, we first specified the time period, and then searched the IES website to identify STEM education research projects funded by IES within the specified time period.

Time period

As discussed above, IES was established in 2002 and it did not start to administer and manage research funding support for ED until 2003. Therefore, we considered IES funded projects from 2003 to the end of 2019.

Searching and identifying IES funded projects in STEM education

Given the diverse perspectives about STEM education across different agencies and researchers (Li et al., 2020 ), we did not discuss and define the meaning of STEM education. Instead, we used the process described in the following paragraph to identify STEM education research projects funded by IES.

On the publicly accessible IES website ( https://ies.ed.gov ), one menu item is “FUNDING OPPORTUNITIES”, and there is a list of choices within this menu item. One choice is “SEARCH FUNDED RESEARCH GRANTS AND CONTRACTS.” On this web search page, we can choose “Program” under “ADDITIONAL SEARCH OPTIONS.” There are two program categories related to STEM under the option of “Program.” One is “Science, Technology, Engineering, and Mathematics (STEM) Education” under one large category of “Education Research” and the other is “Science, Technology, Engineering, and Mathematics” under another large category of “Special Education Research.” We searched for funded projects under these two program categories, and the process returned 98 funded projects in “Science, Technology, Engineering, and Mathematics (STEM) Education” under “Education Research” and 29 funded projects in “Science, Technology, Engineering, and Mathematics” under “Special Education Research,” for a total of 127 funded projects in these two programs designated for STEM education by IES Footnote 1 .

Data analysis

To address questions 1, 2, 3, and 4, we collected the following information about these projects identified using above procedure: amount of funding, years of duration, information about the PI, types of awardees that received and administered the funding (i.e., university versus those non-university including non-profit organization such as WestEd, Educational Testing Service), and projects’ foci on school level and participants. When a project’s coverage went beyond one category, the project was then coded in terms of its actual number of categories being covered. For example, we used the five categories to classify project’s participants: Pre–K, grades 1–4, grades 5–8, grades 9–12, and adult. If a funded project involved participants from Pre-school to grade 8, then we coded the project as having participants in three categories: Pre-K, grades 1–4, and grades 5–8.

To address question 5, we analyzed projects based on goal classifications from IES. IES followed the classification of research types that was produced through a joint effort between IES and NSF in 2013 (Institute of Education Sciences (IES) and National Science Foundation (NSF), 2013 ). The effort specified six types of research that provide guidance on the goals and level of funding support: foundational research, early-stage or exploratory research, design and development research, efficacy research, effectiveness research, and scale-up research. Related to these types, IES classified goals for funded projects: development and innovation, efficacy and replication, exploration, measurement, and scale-up evaluation, as described on the IES website.

To address question 6, we coded the disciplinary focus using the following five categories: mathematics, science, technology, engineering, and integrated (meaning an integration of any two or more of STEM disciplines). In some cases, we coded a project with multiple disciplinary foci into more than one category. The following are two project examples and how we coded them in terms of disciplinary foci:

The project of “A Randomized Controlled Study of the Effects of Intelligent Online Chemistry Tutors in Urban California School Districts” (2008, https://ies.ed.gov/funding/grantsearch/details.asp?ID=601 ) was to test the efficacy of the Quantum Chemistry Tutors, a suite of computer-based cognitive tutors that are designed to give individual tutoring to high school students on 12 chemistry topics. Therefore, we coded this project as having three categories of disciplinary foci: science because it was chemistry, technology because it applied instructional technology, and integrated because it integrated two or more of STEM disciplines.

The project of “Applications of Intelligent Tutoring Systems (ITS) to Improve the Skill Levels of Students with Deficiencies in Mathematics” (2009, https://ies.ed.gov/funding/grantsearch/details.asp?ID=827 ) was coded as having three categories of disciplinary foci: mathematics, technology because it used intelligent tutoring systems, and integrated because it integrated two or more of STEM disciplines.

To address question 7, all 127 projects were coded using a classification category system developed and used in a previous study (Wang et al., 2019 ). Specifically, each funded project was coded in terms of research type (experimental, interventional, longitudinal, single case, correlational) Footnote 2 , data collection method (interview, survey, observation, researcher designed tests, standardized tests, computer data Footnote 3 ), and data analysis method (descriptive statistics, ANOVA*, general regression, HLM, IRT, SEM, others) Footnote 4 . Based on a project description, specific method(s) were identified and coded following a procedure similar to what we used in a previous study (Wang et al., 2019 ). Two researchers coded each project’s description, and the agreement between them for all 127 projects was 88.2%. When method and disciplinary focus-coding discrepancies occurred, a final decision was reached after discussion.

Results and discussion

In the following sections, we report findings as corresponding to each of the seven research questions.

Question 1: the number of projects, total funding, and the average funding per project from 2003 to 2019

Figure 2 shows the distribution of funded projects over the years in each of the two program categories, “Education Research” and “Special Education Research,” as well as combined (i.e., “STEM” for projects funded under “Education Research,” “Special STEM” for projects funded under “Special Education Research,” and “Combined” for projects funded under both “Education Research” and “Special Education Research”). As Fig. 2 shows, the number of projects increased each year up to 2007, with STEM education projects started in 2003 under “Education Research” and in 2006 under “Special Education Research.” The number of projects in STEM under “Special Education Research” was generally less than those funded under the program category of “Education Research,” especially before 2011. There are noticeable decreases in combined project counts from 2009 to 2011 and from 2012 to 2014, before the number count increased again in 2015. We did not find a consistent pattern across the years from 2003 to 2019.

The distribution of STEM education projects over the years. (Note: STEM refers to projects funded under “Education Research,” Special STEM refers to projects funded under “Special Education Research,” and “Combined” refers to projects funded under both “Education Research” and “Special Education Research.” The same annotations are used in the rest of the figures.)

A similar trend can be observed in the total funding amount for STEM education research (see Fig. 3 ). The figure shows noticeably big year-to-year swings from 2003 to 2019, with the highest funding amount of more than 33 million USD in 2007 and the lowest amount of 2,698,900 USD in 2013 from these two program categories. Although it is possible that insufficient high-quality grant proposals were available in one particular year to receive funding, the funded amount and the number of projects (Fig. 2 ) provide insights about funding trends over the time period of the review.

Annual funding totals

As there are diverse perspectives and foci about STEM education, we also wondered if STEM education research projects might be funded by IES but in program options other than those designated options of “Science, Technology, Engineering, and Mathematics (STEM) Education.” We found a total of 54 funded projects from 2007 to 2019, using the acronym “STEM” as a search term under the option of “SEARCH FUNDED RESEARCH GRANTS AND CONTRACTS” without any program category restriction. Only 2 (3.7%) out of these 54 projects were in the IES designated program options of STEM education in the category of “Education Research.” Further information about these 54 projects and related discussion can be found as additional notes at the end of this review.

Results from two different approaches to searching for IES-funded projects will likely raise questions about what kinds of projects were funded in the designated program option of “Science, Technology, Engineering, and Mathematics (STEM) Education,” if only two funded projects under this option contained the acronym “STEM” in a project’s title and/or description. We shall provide further information in the following sub-sections, especially when answering question 6 related to projects’ disciplinary focus.

Figure 4 illustrates the trend of average funding amount per project each year in STEM education research from 2003 to 2019. The average funding per project varied considerably in the program category “Special Education Research,” and no STEM projects were funded in 2014 and 2017 in this category. In contrast, average funding per project was generally within the range of 1,132,738 USD in 2019 to 3,475,975 USD in 2014 for the projects in the category of “Education Research” and also for project funding in the combined category.

The trend of average funding amount per project funded each year in STEM education research

Figure 5 shows the number of projects in different funding amount categories (i.e., less than 1 million USD, 1–2 million USD, 2–3 million USD, 3 million USD or more). The majority of the 127 projects obtained funding of 1–2 million USD (77 projects, 60.6%), with 60 out of 98 projects (61.2%) under “Education Research” program and 17 out of 29 projects (58.6%) in the program category “Special Education Research.” The category with second most projects is funding of 3 million USD or more (21 projects, 16.5%), with 15 projects (15.3% of 98 projects) under “Education Research” and 6 projects (20.7% of 29 projects) under “Special Education Research.”

The number of projects in terms of total funding amount categories

Figure 6 shows the average amount of funding per project funded across these different funding amount and program categories. In general, the projects funded under “Education Research” tended to have a higher average amount than those funded under “Special Education Research,” except for those projects in the total funding amount category of “less than 1 million USD.” Considering all 127 funded projects, the average amount of funding was 1,960,826.3 USD per project.

The average amount of funding per project across different total funding amount and program categories

Figure 7 shows that the vast majority of these 127 projects were 3- or 4-year projects. In particular, 59 (46.5%) projects were funded as 4-year projects, with 46 projects (46.9%) under “Education Research” and 13 projects (44.8%) under “Special Education Research.” This category is followed closely by 3-year projects (54 projects, 42.5%), with 41 projects (41.8%) under “Education Research” and 13 projects (44.8%) under “Special Education Research.”

The number of projects in terms of years of project duration. (Note, 2: 2-year projects; 3: 3-year projects; 4: 4-year projects; 5: 5-year projects)

Question 2: trends of single versus multiple principal investigator(s) in STEM education

Figure 8 shows the distribution of projects over the years grouped by a single PI or multiple PIs where the program categories of “Education Research” and “Special Education Research” have been combined. The majority of projects before 2009 had a single PI, and the trend has been to have multiple PIs for STEM education research projects since 2009. The trend illustrates the increased emphases on collaboration in STEM education research, which is consistent with what we learned from a recent study of journal publications in STEM education (Li et al., 2020 ).

The distribution of projects with single versus multiple PIs over the years (combined)

Separating projects by program categories, Fig. 9 shows projects funded in the program category “Education Research.” The trends of single versus multiple PIs in Fig. 9 are similar to the trends shown in Fig. 8 for the combined programs. In addition, almost all projects in STEM education funded under this regular research program had multiple PIs since 2010.

The distribution of projects with single versus multiple PIs over the years (in “Education Research” program)

Figure 10 shows projects funded in the category “Special Education Research.” The pattern in Fig. 10 , where very few projects funded under this category had multiple PIs before 2014, is quite different from the patterns in Figs. 8 and 9 . We did not learn if single PIs were appropriate for the nature of these projects. The trend started to change in 2015 as the number of projects with multiple PIs increased and the number of projects with single PIs declined.

The distribution of projects with single versus multiple PIs over the years (in “Special Education Research” program)

Question 3: types of awardees of these projects

Besides the information about the project’s PI, the nature of the awardees can help illustrate what types of entity or organization were interested in developing and carrying out STEM education research. Figure 11 shows that the university was the main type of awardee before 2012, with 80 (63.0%) projects awarded to universities from 2003 to 2019. At the same time, non-university entities received funding support for 47 (37.0%) projects and they seem to have become even more active and successful in obtaining research funding in STEM education over the past several years. The result suggests that diverse organizations develop and conduct STEM education research, another indicator of the importance of STEM education research.

The distribution of projects funded to university versus non-university awardees over the years

Question 4: participant populations in the projects

Figure 12 indicates that the vast majority of projects were focused on student populations in preschool to grade 12. This is understandable as IES is the research funding arm of ED. Among those projects, middle school students were the participants in the most projects (70 projects), followed by student populations in elementary school (48 projects), and high school (38 projects). The adult population (including post-secondary students and teachers) was the participant group in 36 projects in a combined program count.

The number of projects in STEM education for different groups of participants (Note: Pre-K: preschool-kindergarten; G1–4: grades 1–4; G5–8: grades 5–8; G9–12: grades 9–12; adult: post-secondary students and teachers)

If we separate “Education Research” and “Special Education Research” programs, projects in the category “Special Education Research” focused on student populations in elementary and middle school most frequently, and then adult population. In contrast, projects in the category “Education Research” focused most frequently on middle school student population, followed by student populations in high school and elementary school.

Given the importance of funded research in special education Footnote 5 at IES, we considered projects focused on participants with disabilities. Figure 13 shows there were 28 projects in the category “Special Education Research” for participants with disabilities. There were also three such projects funded in the category “Education Research,” which together accounted for a total of 31 (24.4%) projects. In addition, some projects in the category “Education Research” focused on other participants, including 11 projects focused on ELL students (8.7%) projects and 37 projects focused on low SES students (29.1%).

The number of funded projects in STEM education for three special participant populations (Note: ELL: English language learners, Low SES: low social-economic status)

Figure 14 shows the trend of projects in STEM education for special participant populations. Participant populations with ELL and/or Low SES gained much attention before 2011 among these projects. Participant populations with disabilities received relatively consistent attention in projects on STEM education over the years. Research on STEM education with special participant populations is important and much needed. However, related scholarship is still in an early development stage. Interested readers can find related publications in this journal (e.g., Schreffler et al., 2019 ) and other journals (e.g., Lee, 2014 ).

The distribution of projects in STEM education for special participant populations over the years

Question 5: types of projects in terms of goals for program development and research

Figure 15 shows that “development and innovation” was the most frequently funded type of project (58 projects, 45.7%), followed by “efficacy and replication” (34 projects, 26.8%), and “measurement” (21 projects, 16.5%). The pattern is consistent across “Education Research,” “Special Education Research,” and combined. However, it should be noted that all five projects with the goal of “scale-up evaluation” were in the category “Education Research” Footnote 6 and funding for these projects were large.

The number of projects in terms of the types of goals

Examining the types of projects longitudinally, Fig. 16 shows that while “development and innovation” and “efficacy and replication” types of projects were most frequently funded in the “Education Research” program, the types of projects being funded changed longitudinally. The number of “development and innovation” projects was noticeably fewer over the past several years. In contrast, the number of “measurement” projects and “efficacy and replication” projects became more dominant. The change might reflect a shift in research development and needs.

The distribution of projects in terms of the type of goals over the years (in “Education Research” program)

Figure 17 shows the distribution of project types in the category “Special Education Research.” The pattern is different from the pattern shown in Fig. 16 . The types of “development and innovation” and “efficacy and replication” projects were also the dominant types of projects under “Special Education Research” program category in most of these years from 2007 to 2019. Projects in the type “measurement” were only observed in 2010 when that was the only type of project funded.

The distribution of projects in terms of goals over the years (in “Special Education Research” program)

Question 6: disciplinary foci of projects in developing and conducting STEM education research

Figure 18 shows that the majority of the 127 projects under such specific programs included disciplinary foci on individual STEM disciplines: mathematics in 88 projects, science in 51 projects, technology in 43 projects, and engineering in 2 projects. The tremendous attention to mathematics in these projects is a bit surprising, as mathematics was noted as being out of balance in STEM education (English, 2016 ) and also in STEM education publications (Li, 2018b , 2019 ). As noted above, each project can be classified in multiple disciplinary foci. However, of the 88 projects with a disciplinary focus on mathematics, 54 projects had mathematics as the only disciplinary focus (38 under “Education Research” program and 16 under “Special Education Research” program). We certainly hope that there will be more projects that further scholarship where mathematics is included as part of (integrated) STEM education (see Li & Schoenfeld, 2019 ).

The number of projects in terms of disciplinary focus

There were also projects with specific focus on integrated STEM education (i.e., combining any two or more disciplines of STEM), with a total of 55 (43.3%) projects in a combined program count. The limited number of projects on integrated STEM in the designated STEM funding programs further confirms the common perception that the development of integrated STEM education and research is still in its initial stage (Honey et al., 2014 ; Li, 2018a ).

In examining possible funding trends, Fig. 19 shows that mathematics projects were more frequently funded before 2012. Engineering was a rare disciplinary focus. Integrated STEM was a disciplinary focus from time to time among these projects. No other trends were observed.

The distribution of projects in terms of disciplinary focus over the years

Question 7: research types and methods that projects used

Figure 20 indicates that “interventional” (in 104 projects, 81.9%) and “experimental research” (in 89 projects, 70.1%) were the most frequently funded types of research. The percentages of projects funded under the regular education research program were similar to those funded under “Special Education Research” program, except that projects funded under “Special Education Research” tended to utilize correlational research more often.

The number of projects in terms of the type of research conducted

Research in STEM education uses diverse data collection and analysis methods; therefore, we wanted to study types of methods (Figs. 21 and 22 , respectively). Among the six types of methods used for data collection, Fig. 21 indicates that “standardized tests” and “designed tests” were the most commonly used methods for data collection, followed by “survey,” “observation,” and “interview.” The majority of projects used three quantitative methods (“standardized tests,” “researcher designed tests,” and “survey”). The finding is consistent with the finding from analysis of journal publications in STEM education (Li et al., 2020 ). Data collected through “interview” and “observation” were more likely to be analyzed using qualitative methods as part of a project’s research methodology.

The number of projects categorized by the type of data collection methods

The number of projects categorized by the type of data analysis methods

Figure 22 shows the use of seven (including others) data analysis methods among these projects. The first six methods (i.e., descriptive, ANOVA*, general regression, HLM, IRT, and SEM) as well as some methods in “others” are quantitative data analysis methods. The number of projects that used these quantitative methods is considerably larger than the number of projects that used qualitative methods (i.e., included in “others” category).

Concluding remarks

The systematic analysis of IES-funded research projects in STEM education presented an informative picture about research support for STEM education development in the USA, albeit based on only one public funding agency from 2003 to 2019. Over this 17-year span, IES funded 127 STEM education research projects (an average of over seven projects per year) in two designated STEM program categories. Although we found no discernable longitudinal funding patterns in these two program categories, both the number of funded projects in STEM education and their funding amounts were high. If we included an additional 52 projects with the acronym “STEM” funded by many other programs from 2007 to 2019 (see “ Notes ” section below), the total number of projects in STEM education research would be even higher, and the number of projects with the acronym “STEM” would also be larger. The results suggested the involvement of many researchers with diverse expertise in STEM education research was supported by a broad array of program areas in IES.

Addressing the seven questions showed several findings. Funding support for STEM education research was strong, with an average of about 2 million USD per project for a typical 3–4 year duration. Also, our analysis showed that the number of projects with multiple PIs over the years increased over the study time period, which we speculate was because STEM education research increasingly requires collaboration. STEM education research is still in early development stage, evidenced by the predominance of project goals in either “development and innovation” or “efficacy and replication” categories. We found very few projects (5 out of 127 projects, 4.0%) that were funded for “scale-up evaluation.” Finally, as shown by our analysis of project participants, IES had focused on funding projects for students in grades 1–12. Various quantitative research methods were frequently used by these projects for data collection and analyses.

These results illustrated how well STEM education research was supported through both the designated STEM education and many other programs during the study time period, which helps to explain why researchers in the USA have been so productive in producing and promoting scholarship in STEM education (Li et al., 2019 ; Li et al., 2020 ). We connected several findings from this study to findings from recent reviews of journal publications in STEM education. For example, publications in STEM education appeared in many different journals as many researchers with diverse expertise were supported to study various issues related to STEM education, STEM education publications often have co-authorship, and there is heavy use of quantitative research methods. The link between public funding and significant numbers of publications in STEM education research from US scholars offers a strong argument for the importance of providing strong funding support to research and development in STEM education in the USA and also in many other countries around the world.

The systematic analysis also revealed that STEM education, as used by IES in naming the designated programs, did not convey a clear definition or scope. In fact, we found diverse disciplinary foci in these projects. Integrated STEM was not a main focus of these designated programs in funding STEM education. Instead, many projects in these programs had clear subject content focus in individual disciplines, which is very similar to discipline-based education research (DBER, National Research Council, 2012 ). Interestingly enough, STEM education research had also been supported in many other programs of IES with diverse foci Footnote 7 , such as “Small Business Innovation Research,” “Cognition and Student Learning,” and “Postsecondary and Adult Education.” This funding reality further suggested the broad scope of issues associated with STEM education, as well as the growing need of building STEM education research as a distinct field (Li, 2018a ).

Inspired by our recent review of journal publications as research output in STEM education, this review started with an ambitious goal to study funding support as research input for STEM education. However, we had to limit the scope of the study for feasibility. We limited funding sources to one federal agency in the USA. Therefore, we did not analyze funding support from private funding sources including many private foundations and corporations. Although public funding sources have been one of the most important funding supports available for researchers to develop and expand their research work, the results of this systematic analysis suggest the importance future studies to learn more about research support and input to STEM education from other sources including other major public funding agencies, private foundations, and non-profit professional organizations.

Among these 54 funded projects containing the acronym “STEM” from 2007 to 2019, Table 1 shows that only 2 (3.7%) were in the IES designated program option of STEM education in the category of “Education Research.” Forty-nine projects were in 13 other program options in the category of “Education Research,” with surprisingly large numbers of projects under the “Small Business Innovation Research” option (17, 31.5%) and “Cognition and Student Learning” (11, 20.4%). Three of the 54 funded projects were in the program category of “Special Education Research.” To be specific, two of the three were in the program of “Small Business Innovation Research in Special Education,” and one was in the program of “Special Topic: Career and Technical Education for Students with Disabilities.”

The results suggest that many projects, focusing on various issues and questions directly associated with STEM education, were funded even when researchers applied for funding support in program options not designated as “Science, Technology, Engineering, and Mathematics (STEM) Education.” It implies that issues associated with STEM education had been generally acknowledged as important across many different program areas in education research and special education research. The funding support available in diverse program areas likely allowed numerous scholars with diverse expertise to study many different questions and publish their research in diverse journals, as we noted in the recent review of journal publications in STEM education (Li et al., 2020 ).

A previous study identified and analyzed a total of 46 IES funded projects from 2007 to 2018 (with an average of fewer than 4 projects per year) that contain the acronym “STEM” in a project’s title and/or description (Wang et al., 2019 ). Finding eight newly funded projects in 2019 suggested a growing interest in research on issues directly associated with STEM education in diverse program areas. In fact, five out of these eight newly funded projects specifically included the acronym “STEM” in the project’s title to explicitly indicate the project’s association with STEM education.

Availability of data and materials

The data and materials used and analyzed for the review are publicly available at the IES website, White House website, and other government agency websites.

In a previous study (Wang, Li, & Xiao, 2019), we used the acronym “STEM” as a search term under the option of “SEARCH FUNDED RESEARCH GRANTS AND CONTRACTS” without any program category restriction, and identified and analyzed 46 funded projects from 2007 to 2018 that contain “STEM” in a project’s title and/or description after screening out unrelated key words containing “stem” such as “system”. To make comparisons when needed, we did the same search using the acronym “STEM” and found 8 more funded projects in 2019 for a total of 54 funded projects across many different program categories from 2007 to 2019.

The project of “A Randomized Controlled Study of the Effects of Intelligent Online Chemistry Tutors in Urban California School Districts” (2008). In the project description, its subtitle shows intervention information. We coded this project as “interventional.” Then, the project also included the treatment group and the control group. We coded this project as “experimental.” Finally, this project was to test the efficacy of computer-based cognitive tutors. This was a correlational study. We thus coded it as “correlational.”

Computer data means that the project description indicated this kind of information, such as log data on students.

Descriptive means “descriptive statistics.” General regression means multiple regression, linear regression, logistical regression, except hierarchical linear regression model. ANOVA* is used here as a broad term to include analysis of variance, analysis of covariance, multivariate analysis of variance, and/or multivariate analysis of variance. Others include factor analysis, t tests, Mann-Whitney tests, and binomial tests, log data analysis, meta-analysis, constant comparative data analysis, and qualitative analysis.

Special education originally was about students with disabilities. It has broadened in scope over the years.

The number of students under Special Education was 14% of students in public schools in the USA in 2017–2018. https://nces.ed.gov/programs/coe/indicator_cgg.asp

For example, “Design Environment for Educator-Student Collaboration Allowing Real-Time Engineering-centric, STEM (DESCARTES) Exploration in Middle Grades” (2017) was funded as a 2-year project to Parametric Studios, Inc. (awardee) under the program option of “Small Business Innovation Research” (here is the link: https://ies.ed.gov/funding/grantsearch/details.asp?ID=1922 ). “Exploring the Spatial Alignment Hypothesis in STEM Learning Environments” (2017) was funded as a 4-year project to WestEd (awardee) under the program option of “Cognition and Student Learning” (link: https://ies.ed.gov/funding/grantsearch/details.asp?ID=2059 ). “Enhancing Undergraduate STEM Education by Integrating Mobile Learning Technologies with Natural Language Processing” (2018) was funded as a 4-year project to Purdue University (awardee) under the program option of “Postsecondary and Adult Education” (link: https://ies.ed.gov/funding/grantsearch/details.asp?ID=2130 ).

Abbreviations

Analysis of variance

Discipline-based education research

Department of Education

Hierarchical linear modeling

Institute of Education Sciences

Item response theory

National Science Foundation

Pre-school–grade 12

Requests-for-proposal

Structural equation modeling

Science, technology, engineering, and mathematics

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This review was supported by a grant from the National Science Foundation (DUE-1852942). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

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YL conceptualized the study and drafted the manuscript. KW contributed with data collection, coding, analyses, and manuscript reviews. YX contributed to data collection, coding, and manuscript reviews. JEF and SBN contributed to manuscript improvement through manuscript reviews and revisions. All authors read and approved the final manuscript.

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Li, Y., Wang, K., Xiao, Y. et al. Research and trends in STEM education: a systematic analysis of publicly funded projects. IJ STEM Ed 7 , 17 (2020). https://doi.org/10.1186/s40594-020-00213-8

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Trends and Hot Topics of STEM and STEM Education: a Co-word Analysis of Literature Published in 2011–2020

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Ying-Shao Hsu ORCID: orcid.org/0000-0002-1635-8213 1 , 2 ,
Kai-Yu Tang ORCID: orcid.org/0000-0002-3965-3055 3 &
Tzu-Chiang Lin ORCID: orcid.org/0000-0003-3842-3749 4 , 5

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This study explored research trends in science, technology, engineering, and mathematics (STEM) education. Descriptive analysis and co-word analysis were used to examine articles published in Social Science Citation Index journals from 2011 to 2020. From a search of the Web of Science database, a total of 761 articles were selected as target samples for analysis. A growing number of STEM-related publications were published after 2016. The most frequently used keywords in these sample papers were also identified. Further analysis identified the leading journals and most represented countries among the target articles. A series of co-word analyses were conducted to reveal word co-occurrence according to the title, keywords, and abstract. Gender moderated engagement in STEM learning and career selection. Higher education was critical in training a STEM workforce to satisfy societal requirements for STEM roles. Our findings indicated that the attention of STEM education researchers has shifted to the professional development of teachers. Discussions and potential research directions in the field are included.

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Hsu, YS., Tang, KY. & Lin, TC. Trends and Hot Topics of STEM and STEM Education: a Co-word Analysis of Literature Published in 2011–2020. Sci & Educ (2023). https://doi.org/10.1007/s11191-023-00419-6

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85 Unique Research Topics for STEM Students

Table of Contents

Are you a STEM (Science, Technology, Engineering, and Mathematics) student? If yes, then during your academic journey, you must do qualitative or quantitative research on your field of study. Generally, for doing research, an ideal topic is essential. Since STEM covers broad disciplines, it might be challenging for you to identify the right topic for your research. But, with our assistance, you can effectively handle your research topic selection process. Here, we have suggested 85 best research topics for STEM students on different subjects.

In addition to the list of STEM research topics, we have also shared the importance of STEM research and tips for choosing a perfect STEM research topic.

Explore this entire blog and get exclusive qualitative and quantitative STEM research ideas across a variety of fields.

What is STEM?

STEM refers to Science, Technology, Engineering, and Mathematics. It is a manner of discussing things like education, employment, and activities relating to these four fundamental areas.

Science is the study of the world around us. Technology is the use of tools and equipment to solve problems. Engineering is the design and construction of things. Mathematics is the study of numbers and their applications. STEM enables every student to research, discover, and build interesting things that make our world better and more enjoyable.

Importance of STEM Research

In recent times, our world has been facing tremendous growth in the science and technology fields. This advancement is a result of the continuous research in the STEM areas. Moreover, STEM research is also significant in several aspects as listed below.

STEM research discovers new things and solves certain problems.
It contributes to finding treatments for diseases.
STEM research helps to develop new technology and makes human lives easier.
Engineers create products that improve the quality of human life.
Mathematics helps to comprehend and solve complicated problems.

STEM Research Type: Quantitative vs. Qualitative

STEM students can conduct either quantitative or qualitative research.

Quantitative research entails the methodical gathering and evaluation of numerical data to answer research questions, test hypotheses, identify trends, or find correlations between various factors. It is a systematic, objective approach to research that uses quantifiable data and scientific techniques to generate conclusions.

On the other hand, qualitative research is a methodical and exploratory method of research that focuses on comprehending and analyzing the challenges of human experiences, actions, and occurrences. Its goal is to provide deep insights into the “how” and “why” of various problems by studying them in their natural settings and surroundings.

When compared to quantitative research, qualitative research uses non-numerical data, such as discussions, notes, and open-ended surveys to investigate and comprehend the opinions, experiences, and ideas of individuals or groups.

STEM Researchers frequently select between quantitative and qualitative methods depending on their research objectives, questions, and the subject they are studying.

Know How to Choose a Good STEM Research Topic

As said earlier, for preparing a brilliant STEM research paper, an excellent topic is necessary. In case, you are unsure how to identify the right STEM research topic, follow the topic selection tips we have recommended below.

Determine Your Interests

Consider your interests and areas of excitement in science, technology, engineering, or math. It might be something you encountered in daily life, learned in school, or saw in the news. Simply, by selecting a topic that you are passionate about, you can enhance the pleasure of conducting research.

Examine Existing Subjects

Investigate several STEM research areas on the internet, in books, or at the library. Discover what subject specialists and scientists are researching. This can provide you with new ideas. Also, it can assist you in comprehending what is already known in your subject of choice.

Give Importance to Real-time Problems

Focus on the problems that exist around you. In specific, think about whether you can solve any issues in your community or world by using STEM concepts. Usually, selecting a study topic that fixes a real-world issue might bring more impact to your research.

Discuss with Teachers or Mentors

Talk to your teachers, mentors, or professors regarding what you are passionate about. They will offer assistance and propose STEM research topics that are relevant to your talents and goals. Furthermore, they may provide resources and help for your research.

Narrow Down the Topic

Once you’ve generated some ideas, limit them down to a specific study issue or project. Make sure the topic you select is not too wide or too narrow. Always pick a topic that you can thoroughly investigate within the boundaries of your STEM research paper.

Also Read: 200+ Excellent Research Paper Topics of 2023

List of the Best Research Topics for STEM Students

In case, you are confused about what STEM research topic to choose, then explore the list published below. In the list, you will get 85 outstanding STEM research topics on a wide range of subjects.

Quantitative Research Topics for STEM Students

Measure the effect of different light wavelengths on plant growth.
Examine the impact of pH levels on the rate of chemical reactions.
Investigate the relation between the number of blades on a wind turbine and energy output
Optimize algorithms for autonomous drone navigation in complex environments.
Explore the use of artificial intelligence in predicting and preventing forest fires.
Test the effectiveness of different insulating materials in conserving heat.
Analyze the effect of different concentrations of a substance on bacterial growth.
Investigate the effects of microplastic pollution on aquatic ecosystems.
Analyze the efficiency of solar panels in converting sunlight into electricity under varying conditions.
Study the behavior of magnets in different temperature conditions.
Explore the ethical implications of gene editing in humans.
Analyze the feasibility of harnessing geothermal energy from underwater volcanoes.
Explain the use of machine learning and AI in predicting and mitigating the impact of natural disasters.
Investigate the mechanisms of stem cell differentiation for regenerative medicine.
Explore the science behind the formation of auroras and their cultural significance.

Qualitative Research Topics for STEM Students

Share user experiences with augmented reality applications.
Analyze the impact of social media on political activism.
Present qualitative analysis of online gaming communities.
Analyze the impact of educational apps on student engagement.
Discuss ethical considerations in artificial intelligence development.
Share the perceptions of online privacy and data security.
Narratives of whistleblowers in scientific misconduct cases.
Explain the experiences of individuals participating in virtual reality environments.
Discuss the perceptions of artificial intelligence and automation among STEM Professionals.
Qualitative exploration of team dynamics in engineering projects.
Present the qualitative analysis of the digital divide in education.
Analyze the role of ethics in emerging technology development.
Discuss the perceptions of scientific responsibility in climate change.
Explore the decision-making process in biomedical research.
Qualitative analysis of the ethics of genetic engineering.

Science Research Topics for STEM Students

Study the relationship between diet and lifespan.
Analyze the synthesis of novel polymers with unique properties.
Examine the properties of dark matter and dark energy.
Study the effectiveness of various plant fertilizers.
Explore the dynamics of black holes and their gravitational effects.
Study the behavior of nanoparticles in different solvents.
Analyze the impact of climate change on crop yields.
Explore the physics of renewable energy sources like solar cells.
Study the properties of superfluids at low temperatures.
Investigate the chemistry of alternative fuels.
Explore the quantum properties of entangled particles.
Examine the physics of nanoscale materials and devices.
Analyze the effects of chemical additives on food preservation.
Investigate the chemistry of atmospheric pollutants.
Examine the physics of gravitational waves.

Math Research Topics for STEM Students

Analyze the properties of mathematical models for population dynamics.
Investigate the use of mathematical modeling in epidemiology.
Examine the use of numerical methods in solving partial differential equations.
Analyze the properties of algebraic structures in coding theory.
Explore the behavior of mathematical models in financial markets.
Analyze the behavior of chaotic systems using differential equations.
Examine the use of number theory in cryptography.
Investigate the properties of prime numbers and their distribution.
Analyze the behavior of mathematical models in climate prediction.
Study the optimization of algorithms for solving complex mathematical problems.

Engineering Research Ideas for STEM Students

Explore the efficiency of renewable energy storage systems.
Examine the impact of machine learning in predictive maintenance.
Study the impact of AI-driven design in architecture.
Examine the optimization of supply chain logistics using quantitative methods.
Analyze the effects of vibration on structural engineering.
Discuss the efficiency of water treatment processes in civil engineering.
Analyze the energy efficiency of smart buildings.
Examine the impact of 3D printing on manufacturing processes.
Explore the use of robotics in underwater exploration.
Study the structural integrity of materials in aerospace engineering.

STEM Research Paper Ideas on Computer Science and Technology

Analyze the effectiveness of recommendation systems in e-commerce.
Study the impact of cloud computing on data storage and processing.
Examine the use of neural networks in predicting disease outbreaks.
Explore the efficiency of data mining techniques in customer behavior analysis.
Examine the security of blockchain technology in financial transactions.
Study the impact of quantum computing on cryptography.
Analyze the effectiveness of sentiment analysis in social media monitoring.
Analyze the effectiveness of cybersecurity measures in protecting sensitive data.
Study the impact of algorithmic trading in financial markets.
Analyze the efficiency of data compression algorithms for large datasets.

Also Read: 140 Captivating Public Health Topics for Academic Paper

STEM Research Paper Topics on Health and Medicine

Analyze the impact of personalized medicine in cancer treatment.
Examine the use of wearable devices in monitoring patient health.
Study the epidemiology of chronic disease
Analyze the behavior of pharmaceutical drugs in clinical trials.
Investigate the use of bioinformatics in genomics research.
Analyze the properties of medical imaging techniques for early disease detection.
Study the impact of genetics in predicting disease susceptibility.
Explore the use of regenerative medicine in tissue repair.
Examine the use of artificial intelligence in medical diagnosis.
Analyze the behavior of pathogens in antimicrobial resistance.

Out of the numerous ideas suggested above, choose any topic of your choice and compose a great STEM research paper. If it is more difficult for you to choose a good research topic, perform STEM research, and prepare a brilliant thesis, then call us immediately.

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CBE Life Sci Educ
v.21(1); Spring 2022

Integrating Critical Approaches into Quantitative STEM Equity Work

Meaghan i. pearson.

† Combined Program in Education and Psychology, University of Michigan, Ann Arbor, MI 48109

Sarah D. Castle

‡ Program in Mathematics Education, Michigan State University, East Lansing, MI 48824

Rebecca L. Matz

§ Center for Academic Innovation, University of Michigan, Ann Arbor, MI 48109

Benjamin P. Koester

ǁ Department of Physics, University of Michigan, Ann Arbor, MI 48109

W. Carson Byrd

¶ National Center for Institutional Diversity, University of Michigan, Ann Arbor, MI 48109

The recent anti-racist movements in the United States have inspired a national call for more research on the experiences of racially marginalized and minoritized students in science, technology, engineering, and mathematics (STEM) fields. As researchers focused on promoting diversity, equity, and inclusion, we contend that STEM education must, as a discipline, grapple with how analytic approaches may not fully support equity efforts. We discuss how researchers and educational practitioners should more critically approach STEM equity analyses and why modifying our approaches matters for STEM equity goals. Engaging with equity as a process rather than a static goal, we provide a primer of reflective questions to assist researchers with framing, analysis, and interpretation of student-level data frequently used to identify disparities and assess course-level and programmatic interventions. This guidance can inform analyses conducted by campus units such as departments and programs, but also across universities and the scientific community to enhance how we understand and address systemic inequity in STEM fields.

INTRODUCTION

Over the past 2 years, the world watched as police in the United States killed Black, Hispanic and Latinx Americans ( Egbuonu, 2020 ); hate crimes toward Asians, Asian Americans, and Pacific Islanders surged ( Gover et al. , 2020 ); and disproportionate numbers of Black, Hispanic and Latinx, and Native American people fell victim to the COVID-19 pandemic ( Alcendor, 2020 ). Questions arose across countries, institutions, and communities about how these devastating and brutal events reflect underlying systemic inequities that exist across the globe (e.g., Collins et al. , 2021 ). Higher education in particular witnessed another reinvestment in diversity, equity, and inclusion (DEI) efforts with reinvigorated commitments to faculty cluster hires, curricular revisions, and changes to admissions criteria ( Heinecke and Beach 2020 ; Peoples and Dillard, 2020 ). History has shown, however, that diversity initiatives can serve as mechanisms for institutions to send out signals of advancement without actually translating to systemic changes ( Ahmed, 2012 ; Ray, 2019a , b ; Johnson, 2020 ; Thomas 2020 ).

Likewise, science, technology, engineering, and mathematics (STEM) fields are focusing significant attention toward improving DEI in reflection on student enrollment and success data marred by gendered, racialized, and classed patterns ( Asai, 2020 ; Griffin et al. , 2020 ; McGee, 2020a , b ). Quantitative analyses in and focused on STEM education that rely on commonly available demographic variables (herein we consider gender, race, income, and parental education) are ever more present ( Li et al. , 2020 ). The key issue we address here with STEM equity analyses is that demographic variables are often used automatically in “assessing student success” without situating these student characteristics in relation to the overlapping structural inequities that shape students’ experiences and academic performance.

Because of this tendency, there are often mismatches between the outcomes of equity analyses and how they are interpreted to inform institutional efforts that promote DEI in STEM. By inadequately grappling with the theoretical framing of students’ identities in relation to inequities, current methodological approaches guiding equity analyses can contribute to individualizing inequality ( Byrd, 2021 ). As a consequence, educational initiatives are developed that prioritize changing students and not the STEM environments that perpetuate such inequalities.

STEM equity analyses are conducted by researchers in many different settings across academia—for example, STEM departments and programs do assessment work, institutional research offices conduct internal studies, and even individual instructors may be equipped to investigate their own courses. These analyses are also conducted by federal agencies, policy institutes, and corporations. That is, whether explicitly or implicitly described as “equity analyses” within a department, program, or organization, STEM equity analyses are part and parcel of everyday assessment and evaluation in STEM. Therefore, our intention here is to provide information that is applicable for researchers across the broader STEM community. Fostering an authentic discussion of issues raised by these questions will lead to better analyses that support justice for students who have historically been excluded from and continue to experience marginalization in STEM fields.

The purpose of this essay is twofold. We first discuss the importance of integrating critical perspectives in STEM equity research that relies on quantitative analyses. Then, through a series of critical questions, we aim to engender reflection and conversation with researchers and practitioners who do STEM equity research so that we all can use quantitative data more responsibly and accurately. This discussion was sparked by our own challenges in working with institutional data to better represent and understand the experiences and outcomes of marginalized and minoritized students 1 in STEM through the interdisciplinary Sloan Equity and Inclusion in STEM Introductory Courses (SEISMIC) collaboration. We (the authors) represent the fields of chemistry and biology education, physics and astronomy, mathematics and mathematics education, educational psychology, and sociology and engage in quantitative research regularly in our positions as faculty, staff, and graduate students. We identify mostly as cis-heterosexual men and women, and all of us, except for one author, identify as white. Nonetheless, we all identify with and embrace the need for our fields and institutions to continually improve research and decision making aimed at tackling campus inequalities and injustices.

WHAT ARE CRITICAL APPROACHES TO RESEARCH?

As researchers, the lens through which we view the world has implications for the research questions we seek to explore and our methodological and analytical choices. Those who receive their academic training in STEM fields are generally socialized to adopt a postpositivist lens ( Guba and Lincoln, 1994 ; Harding, 2006 ). Postpositivists assume that objectivity is achievable, where truths about the world remain credible if those seeking it follow the scientific method. This rationale works when observing scientific and mathematical phenomena like gravity or volcanic eruptions but breaks down when studying human experiences. Humans are situated in social contexts that have been shaped by historical events, structural forces, and interaction with other human beings. Thus, humans are more than objects of inquiry; humans and their experiences are a by-product of the structures in which they are embedded ( Horkheimer, 1972 ; Bohman, 2005 ; Devetak, 2005 ).

In contrast to postpositivism, a critical lens assumes that what can be known about the world is socially constructed. Critical theorists separate themselves from traditional theorists across fields ( Bohman, 2005 ). Critical theories explore how historical events and society have shaped present-day experiences and understandings of how the world functions ( Horkheimer, 1972 ). So, whereas traditional theoretical approaches place the phenomenon of interest at the center of analysis, critical theorists seek to place societal contexts that shape a phenomenon as the focal point. Currently, several critical perspectives—that is, feminist, race, queer, disability, and decolonial theories—are accepted in the critical canon ( Bell, 1995 ; hooks, 2000 ; Watson, 2005 ; Siebers, 2008 ; Mignolo, 2012 ). The common theme in these theoretical perspectives is their assertion that society has produced oppressive structures (e.g., patriarchy, racism, sexism, colonialism, and ableism) that harm those who are not white, cisgendered, male, heterosexual, able-bodied, wealthy, and Western individuals. As a result, there exists the need for society and those in it to interrogate how those oppressive ideologies show up in ourselves and connect to oppressive structures in the world around us. From there, we can begin to imagine new strategies for how to make life better for those who find themselves on the margins ( Bohman, 2005 ; Devetak, 2005 ; hooks, 2000 ).

WHY ARE CRITICAL APPROACHES NEEDED IN STEM EQUITY RESEARCH?

Before we can discuss why a critical approach is needed, we must first define the goal of conducting STEM equity research. Over the past 2 years, we have seen increases in the numbers of people wanting to participate in research practices that focus on equity efforts in STEM, many of whom aim to increase the representation of marginalized and minoritized students in STEM fields for the betterment of our institutions and the U.S. economy ( President’s Council of Advisors on Science and Technology, 2020 ). However, placing the United States and our institutions as the motivations for our work and not the students, who often find themselves pushed out of the fields they once found joy in ( McGee, 2020a ), is a striking concern we must all sit with. We argue that engaging in critical research is an effort to re-center the students, to create safer and healthier environments for them to pursue their passions.

STEM equity researchers must grapple with the historical events that have shaped what STEM fields look like today. STEM environments have led to scientific discoveries and innovation, but these environments also have a history of reproducing systemic inequities that harm individuals ( Graves, 2001 ; Roberts, 2011 ; Wilder, 2013 ; Gholson, 2016 ; Joseph et al. , 2019 ; Saini, 2019 ; Cech and Waidzunas, 2021 ; Reinholz and Ridgway, 2021 ). Additionally, it is important to acknowledge that STEM fields have a history of conducting research, creating theories, and making measurements that primarily centered white, cisgendered, male, heterosexual, able-bodied, wealthy individuals ( Harding, 2006 ). Consequently, the prioritization of individuals from privileged groups in STEM has produced research and policies that are susceptible to the structural inequities and personal biases that have historically harmed and excluded marginalized and minoritized communities.

Thus, we argue that the necessity of integrating critical approaches is directly linked to the need for revision in STEM education. Kiese Laymon, a Black Mississippian writer and professor, notes that “revision is a dynamic practice of revisitation, premised on ethically reimagining the ingredients, scope, and primary audience of one’s initial vision” ( Laymon, 2021 , para. 16). Laymon (2021) also argues that the current racial inequities we see in American society are a product of America’s failure to wrestle with and acknowledge its history of “anti-black terror” (para. 28). These arguments apply to STEM equity research, in which our inability to confront our institutions’ historical legacy of slavery, indigenous erasure, and exclusion of those who were not white, cisgendered, male, heterosexual, able-bodied, wealthy in our research and institutions is tied to the lack of representation we see in STEM fields. We assert that STEM equity researchers must commit to an act of revision in which we reflect on our motivations, historical and societal influences, and research processes in the hopes that we can imagine and work toward a more equitable future.

WHAT DO CRITICAL APPROACHES LOOK LIKE IN QUANTITATIVE RESEARCH?

For the purposes of this essay, we outline how to incorporate critical approaches in quantitative STEM equity research. Quantitative analyses are pivotal tools for examining DEI in STEM, but it is imperative to understand that researchers’ positions in relation to race, gender, socioeconomic status, where they are located within universities, academic training, and other characteristics can shape how they approach data and analyses. Researchers employing quantitative methods within a postpositivist framework tend to eschew acknowledging how the positionality of researchers impacts analytic decision making (Zuberi and Bonilla Silva, 2008; Gillborn et al. , 2018 ; López et al. , 2018 ). Additionally, centering individual demographic variables (e.g., race, gender, and ability) instead of structural inequities positions marginalized and minoritized students as solely responsible for their lack of representation in STEM fields. These unrecognized beliefs can lead to misinterpretations of people’s experiences, which in turn negatively affects campus decision making and policies ( Sultana, 2007 ).

Critical quantitative (QuantCrit) approaches are helpful for those interested in studying ways to improve the experiences of marginalized and minoritized students from a quantitative standpoint. The foundational elements of QuantCrit are tied to critical race theory but are also aligned with other perspectives of the critical canon. Critical race theory explores where and how racism prevents people of color from accessing social and economic opportunities ( Bell, 1995 ; Ladson-Billings, 2009 ). Critical race theorists are also interested in subverting deficit-framing projections by documenting the ways that people of color actively resist and cultivate joy despite racist structures ( Devetak, 2005 ; Harper, 2010 ; Delgado and Stefancic, 2017 ). Relying on critical race theory, QuantCrit theory allows researchers to revise traditional notions of viewing relationships among racial groups as causal, instead seeing them as a reflection of historical and existing structural racism that differentially affects racial and ethnic groups ( Zuberi, 2001 ).

Scholars who use QuantCrit: 1) grapple with the historical and present-day reality of racism; 2) recognize how the practice of naively using statistics can uphold white supremacy (e.g., achievement gaps); 3) interrogate how social categorizations such as race and ethnicity are varied, contested, and fluid over time ( Omi and Winant, 2015 ) and how these shifts can impact analyses and interpretations; 4) integrate the voices of racially marginalized and minoritized individuals through qualitative and mixed-methods approaches to account for limitations in quantitative interpretations; and 5) embrace research methods, including quantitative approaches, to pursue equity goals that align with a social justice liberatory agenda (see Gillborn et al. , 2018 ). Recently, those who employ QuantCrit approaches have begun to extend these tenets beyond focusing solely on racism, incorporating how individuals are impacted by overlapping structural inequities ( Crenshaw, 1989 ; Collins, 2000 ; Jang, 2018 ). Accordingly, using QuantCrit approaches provides researchers with the ability to use statistical practices as an analytical tool for improving the social conditions of marginalized and minoritized populations.

CRITICAL QUESTIONS: INTEGRATING QUANTCRIT APPROACHES IN STEM EQUITY ANALYSES

As STEM equity researchers who were originally trained in a postpositivist paradigm, we understand firsthand that learning how to be a QuantCrit researcher is difficult. As described, STEM fields have a history of pushing out marginalized and minoritized students ( Gholson, 2016 ; Joseph et al. , 2019 ; McGee, 2020a , b ; Cech and Waidzunas, 2021 ; Reinholz and Ridgway, 2021 ) and using harmful statistical approaches that contribute to negative perceptions of students ( Zuberi, 2001 ; Zuberi and Bonilla-Silva, 2008 ). Instead of repeating harm, we as STEM education researchers can revise our paradigm to reflect more equity-centered approaches. Relying on Gutiérrez’s (2013) sociopolitical framework and critical perspectives ( Crenshaw, 1989 ; Bohman, 2005 ; Cooper, 2018 ), we define equity as the process of reckoning with how historical events have shaped and continue to reinforce unequal power imbalances in a given context and actively working to dismantle those power imbalances so that society can restructure itself to better sustain and empower all. Importantly, this definition emphasizes continual adaptation as a goal of equity in order to accommodate changing perspectives of how we understand power, inequality, and injustice in our work.

Gutiérrez (2002) similarly argues that equity is a process, rather than a static goal, reflective of individual, institutional, and societal processes. As institutions and fields evolve through space (i.e., geographic location, institution, and classroom) and time, there will always be a need to reimagine new equitable practices. Therefore, here, we use the structure of questions rather than asserting definitive guidelines to follow, reifying our commitment to equity as a process with no universal, one-size-fits-all approach to equity analyses. These questions can assist researchers in adjusting their methodological approaches to the contexts of the educational environments in their studies as well as in delineating which data are collected and selected for analyses. To this end, imperfection and improvement represent the norm of equity analyses and can provide clarifications with each iteration. As a result, we advise that researchers use the following eight questions (summarized in Table 1 ) as self-reflective tools, rather than as an exhaustive list of questions to consider with every analysis.

Critical questions: A guide to integrating critical approaches in STEM equity quantitative analyses

How Does Lived Experience Affect How One Approaches Research?

The lenses through which researchers view the world are influenced by their lived experiences accumulated through a multitude of interpersonal interactions and exposure to and engagement with different research perspectives, methodologies, and theories. When using quantitative approaches, researchers often implicitly regard themselves as objective observers, with numbers viewed as neutral ( Guba and Lincoln, 1994 ). This practice becomes especially concerning in social and educational research, as scholars have uncovered how numbers and data have been used to reinforce social inequities. For instance, Zuberi and Bonilla-Silva (2008) highlight how “statistical analysis was developed to explain the racial inferiority of colonial and second-class citizens in the new imperial era” (p. 5). These harmful statistical practices still permeate education research today, with researchers studying achievement gaps in higher education without adequate explanation of structural barriers ( Ladson-Billings, 2006 ; Gutiérrez, 2008 ). It is important to realize that researchers are human beings who are situated in societal contexts that privilege some groups over others ( Bohman, 2005 ). As a result, researchers are prone to have conscious and unconscious biases that influence the development of research questions and decision-making practices for measurement and analyses ( Harding, 1992 ).

A common practice in qualitative research is to write positionality statements ( Secules et al. , 2021 ). In these statements, researchers discuss how their backgrounds and experiences impacted their academic trajectories and relationships to research. Harding (1992) argues that being upfront about one’s biases, values, and experiences reflects “strong objectivity,” because it allows the audience to understand how a researcher’s lived experience and personal biases might impact the study. Given that positionality statements are not a common practice in quantitative research, we understand that researchers might be hesitant to include them in their work. However, a core component of being a critical scholar is constantly reflecting on how society influences one’s view of the world and in return how one chooses to do research ( Guba and Lincoln, 1994 ). By grappling with their positionality, researchers can better understand the strengths and limitations of their lenses and thus their work. Before and throughout the research process, we advise that researchers take time to reflect on, and perhaps write about, their positionality. Additionally, researchers should assess whether their lived experiences or academic training prepared them to conduct their research.

What Theoretical Assumptions Are Present in Conceptualizations of Equity Practices?

Before analyzing data, researchers should first assess their definitions of equity. Rodriguez et al. (2012) outlined, for example, three different equity models using the language of parity, fairness, and individuality. Equity models based on parity focus on getting minoritized students to obtain similar levels of academic success as majority groups members, and equity models based on fairness aim to get different groups of students to achieve similar levels of progress on tasks and assignments ( Rodriguez et al. , 2012 ). An inherent problem in these models is the assumption that academic success is contingent upon the behaviors and beliefs of majority groups. The equity of parity model also does not account for the historical trauma and discrimination that has hindered marginalized and minoritized students’ academic success in STEM programs. Individual students have their own sets of privileges and disadvantages that influence their needs and experiences in STEM learning environments. Therefore, STEM equity models should accept that conceptualizations of equity will vary across groups and situations, and not neatly align with cut-and-dried societal hierarchies.

Rodriguez et al. (2012) advocate for researchers to use equity models of individuals in which researchers attend to the factors that have harmed marginalized and minoritized students’ access to STEM fields and develop conceptualizations of success for each individual group. Going further, Gutiérrez (2013) argues that focusing on individual groups is not enough, rather that equitable practices within STEM contexts must contend with the ways that identity and power manifest in our courses and institutions. First, Gutiérrez (2013) describes how equity for an identity group can fluctuate depending on the context and time frame. As a result, researchers should unpack their justifications for focusing on a specific identity group when conceptualizing equity. For example, researchers will explain that they are studying an identity group (e.g., women or students of color) due to their lack of representation in STEM fields. However, each institution, department, and classroom has its own set of historical origins and structural factors that have shaped the present-day experiences for each identity group. Equity models should describe and embrace these variations ( Hancock, 2007 ).

Additionally, Gutiérrez (2013) comments on how STEM skill sets (e.g., quantitative literacy) are perceived as necessary tools for professional and personal development, creating a system in which individuals who fail to adopt these skill sets are rendered less valuable. These ideological assumptions shape STEM learning spaces as sociopolitical institutions wherein marginalized and minoritized students are blamed for their lack of representation without addressing systemic inequities. Thus, when focusing on ways to center equity in STEM analyses, we suggest that researchers avoid using language that solely focuses on marginalized and minoritized students in relation to their academic outcomes and more so on how their educational experiences are shaped by history, power, and context.

What Analytical and Interpretive Choices Can Be Made to Focus on Excellence?

A popular practice in STEM equity research is to observe the achievement gaps existing between majority and marginalized and minoritized students ( Gouvea, 2021 ). A wealth of research explores how students who belong to underserved racial, gender, ability, and socioeconomic groups underperform academically in comparison to their privileged counterparts (e.g., Bastedo and Jaquette, 2011 ; Matz et al. , 2017 ; Whitcomb and Singh, 2021 ). Focusing solely on gaps is harmful, because it centers students’ identities as the reasons behind their academic failures. Additionally, the research on achievement gaps over the years has not substantially improved the experiences of marginalized and minoritized students in STEM; in fact, research has shown that overreliance on the documentation of these gaps has contributed to negative societal constructions of the academic abilities of students from minoritized backgrounds ( Gutiérrez, 2008 ; Martin, 2012 ). Embracing critical approaches in STEM equity research necessitates that researchers use proactive approaches wherein efforts are pushed toward addressing what institutions can do to better support students.

Rather than framing analyses with gaps, those conducting equity analyses should focus on how different factors positively relate to advancements, gains, and excellence of students ( Gutiérrez, 2008 ; Harper, 2010 ). For example, research shows that LGBTQ+ students experience fewer stressors when they attend colleges that have academic studies, policies, and student clubs supportive of LGBTQ+ individuals ( Woodford et al. , 2018 ). By shifting the onus to institutional components, Woodford et al. (2018) showcase how university programs and policies are directly tied to the success of LGBTQ+ students. Practitioners can use these findings to create supportive institutional and classroom environments for LGBTQ+ students.

We further caution against excellence-based approaches that solely center grades or degree attainment. Despite increases in STEM degrees conferred to racially minoritized students, there still exists a lack of representation in STEM fields ( Fry et al. , 2021 ). Furthermore, the financial and psychological burdens that racially marginalized and minoritized students report while enrolled in and after college suggests that “success” postgraduation is not equitable across all groups ( Keels et al ., 2017 ; Davis et al. , 2020 ; McGee, 2020b ). Students of color often conceptualize “success” as tied to their ability to give back to their communities, which is different from traditional conceptualizations of success ( McGee and Martin, 2011 ; Pérez Huber et al. , 2018 ; Lopez, 2020 ; McGee, 2020a ). As a result, we recommend that researchers adopt definitions of excellence within STEM contexts based on the conceptualizations of their population of interest and then use those definitions in analyses ( Pérez Huber et al. , 2018 ; Weatherton and Schussler, 2021 ).

What Theoretical Linkages Exist between the Constructs and Demographic Variables of Interest?

Too often, quantitative STEM equity analyses are conducted with a “kitchen sink” approach in which full combinatorics are used to study intersections of student constructed identities. Including several independent demographic variables without adequately accounting for past research or theoretical linkages among them hinders the interpretation of research findings. How and why these demographic variables are used in analyses impacts conversations about what inequities look like, for whom, and what should be done.

Recently, scholars have begun to discuss the need for a “race re-imaging” wherein commonly used measures such as motivation or institutional support are re-evaluated and adapted to fit the lived experiences of racially marginalized and minoritized experiences historically left out of educational psychology research ( DeCuir-Gunby and Schutz, 2014 ; Lopez, 2020 ; Matthews and López, 2020 ). Research indicates that racially marginalized and minoritized students’ value in STEM is strengthened through their ability to understand how STEM educational skill sets can uplift their communities ( McGee and Bentley, 2017 ; Gray et al. , 2020 ), countering the individualistic culture of STEM learning environments ( Battey and Leyva, 2016 ; Carter, 2017 ). Therefore, STEM utility and motivational measures that ignore social justice and community engagement may miss out on the ways that STEM and racial identities intersect ( McGee, 2020a ; Miller-Cotto and Lewis, 2020 ). As STEM equity researchers, we can apply these ideals to questions of pre-existing assumptions we may hold about the relationships between our constructs of interest and different demographic variables (i.e., gender, socioeconomic status, ability, and sexuality) selected for our studies before running analyses. Then, if deficit-based theoretical linkages emerge, we recommend researchers find outside studies promoting strength-based approaches or adopt qualitative or mixed approaches that can better speak to the associations between the demographic variables and constructs of interest.

What Should Be Considered when Using Standardized Test Scores as a Metric for “Prior Preparation”?

Standardized test scores (ACT/Scholastic Aptitude Test [SAT]) must be incorporated cautiously considering who is and has been most likely to do well on them given structural inequalities that privilege certain families over others ( Rothstein, 2004 ; Soares, 2007 ; Zwick, 2013 ; Carnevale et al. , 2020 ). As researchers focused on equity, we must acknowledge the racist origins of standardized assessments. In the early 1900s, standardized assessments were intentionally used by eugenicists as justifications for racial purity in American educational systems ( Lemann, 2000 ; Harris et al. , 2011 ; Soares, 2007 ). Today, standardized assessments are still used in admissions decisions and placement into undergraduate STEM courses, even though research has shown that they are weak and inadequate predictors of college retention for racially minoritized students ( Sedlacek, 2004 ). Although many institutions have either modified admissions policies to be test optional or completely eliminated standardized tests in admissions review due to the impact of the COVID-19 pandemic, how long institutions will continue with such policies and what possible alternative assessments may be used in place of ACT and SAT test scores remains to be seen. Further, students who come from economically privileged families have access to high schools and test preparation resources that increase their chances of doing well on standardized assessments. The economic privileges continue once these students enter higher education ( Borg et al. , 2012 ; Carnevale et al. , 2020 ). As a result, causal linkages between standardized assessments and degree attainment generally fail to account for wealth as a confounding variable. Therefore, we encourage the use of other metrics to capture the academic preparation of students.

College course grades and high school grade point average (GPA), while also imperfect measures, are stronger predictors for student adjustment and success in college over standardized test scores ( Byrd et al. , 2014 ; Koester et al. , 2016 ; Galla et al. , 2019 ). Unlike standardized assessment scores, a student’s high school course grades and college course work better reflect the level of mastery for a given subject. Additionally, researchers could consider using Advancement Placement (AP) scores. The AP program provides high school students with the chance to engage in college-level curricula ( Kolluri, 2018 ). Research has shown that passing AP tests is related to positive college outcomes across students from different racial and socioeconomic backgrounds ( Dougherty et al. , 2006 ; Fischer et al. , 2021 ). It is important to note that even these metrics are not perfect indicators of academic preparation, given the intersecting inequalities that exist in K–12 educational systems (see Lewis and Diamond, 2015 ). Therefore, researchers should account for the current limitations that exist in how we assess students’ prior academic preparation.

What Measures Capture Structural Inequalities That Exist in STEM Higher Education?

Equity analyses that only use individual-level variables provide great insight into how academic outcomes vary across different social groups. However, interpretations that come from these types of analyses often place sole responsibility on minoritized and marginalized students to persevere through systemic barriers ( McGee, 2020a ). Using complex multilevel models, researchers have assessed the impacts of various structural components on student outcomes, such as campus and classroom climate, policies, and institutional characteristics (e.g., selectivity and public vs. private status; Espinosa, 2011 ; Leath and Chavous, 2018 ; Ohland et al. , 2018). For example, Espinosa (2011) found that women of color who attended private colleges were more likely than their peers enrolled at public institutions to persist in their STEM programs. Espinosa (2011) attributes the positive effect of private institutions to the large amounts of educational resources available that counteract a lack of academic preparation among women of color. Espinosa (2011) further showcases that experiences for women of color vary based on the STEM contexts in which they are situated. In contrast, Leath and Chavous (2018) show that Black women enjoy college less when they feel like they must conceal their racial and ethnic identity. Leath and Chavous (2018) demonstrate how tumultuous racial climates contribute to Black women’s college experiences. These studies allow researchers to gain insight into the underlying mechanisms and structural components (e.g., type of college and racist campus climate) that contribute to student experiences, persistence, and success. Also, these researchers illustrate a story in which the institution is held accountable for variations in student outcomes ( Hancock, 2007 ).

There are, however, limitations to these approaches. For one, institutional climate measures may aggregate students’ perceptions about how well students from different backgrounds get along with one another. Although these measures are reflective of structural components, they still rely on individual-level perceptions and do not generally account for different conceptualizations of climate across social groups. Second, multilevel models require large sample sizes at the individual level to maintain statistical power ( Snijders, 2005 ), but researchers attempting to collect information from a diverse set of participants are often blocked by a lack of financial resources and time ( Hancock, 2007 ). As a result, researchers may be forced to make difficult analytical decisions like aggregating multiple social groups together (e.g., combining non-white students) that gloss over the variation between different groups of students and hinder our understanding of how structural inequalities on campus, and in STEM programs specifically, differentially impact their experiences and outcomes. Additionally, because STEM equity researchers often find themselves working with institutional data, individual variables may be the only ones available, and as we describe in more detail later, may not include documentation about how these data were collected, which can influence modeling strategies and subsequent interpretations.

As a result, we emphasize that models based only on individual-level variables (e.g., race, gender, and ability) can only suggest variations across existing groups; they are not explanations for the underlying mechanisms that influence these variations. Ultimately, much work remains in delineating the best practices for integrating structural features into analyses and appropriately contextualizing them within STEM equity research. In the meantime, we recommend that researchers do their best to incorporate structural components in analyses wherever possible.

How Do Changes in Institutional Categories for Demographic Variables over Time Affect Analyses?

When working with institutional data, researchers may need to track how their institutions’ social categories have changed over time ( Viano and Baker, 2020 ; Byrd, 2021 ). Categorizations like gender, race and ethnicity, income, and parental education are not fixed; these categories fluctuate over time, even if slowly. As a broad example, the race and ethnicity categories on the U.S. census that inform data collection across society have changed with every census administration ( Brown, 2020 ). At one time, for example, Irish immigrants were not viewed as “white” due to a few factors including their socioeconomic position and religious beliefs, but as the Irish gained economic mobility in a deepening Jim Crow era, their ascension to whiteness was solidified in the United States ( Omi and Winant, 2015 ). Here we see that race is not static, but a by-product of social and political change.

In addition to race and ethnicity, gender categorizations in the United States have also evolved, with social surveys moving beyond binary conceptualizations and shifting toward more gender-inclusive (i.e., transgender, gender non-conforming, nonbinary) categories ( Westbrook and Saperstein, 2015 ). Indeed, such variation has always existed ( D’Ignazio and Klein, 2020 ), and it is important to note that individual perceptions of social categorizations are also subject to change ( Freeman et al. , 2011 ). Similarly, sometimes the same information is collected about students in multiple contexts (e.g., when both the financial aid and registrar’s office have information about students’ first- or continuing-generation status). Identifying areas of discordance from different data-collection mechanisms over time can more properly contextualize analyses, particularly when merging multiple data sets for the same students.

Consequently, when working with secondary data sources, we recommend that researchers seek to obtain information about how social categorizations were solicited and defined as well as how they may have changed over time. Including this information in studies, even if only as supplemental material, will help to produce research that is better contextualized. Researchers should also reach out to campus offices that maintain and analyze student-level data for additional student information that may not be included in existing data sets to improve clarity about how groups are constructed and how this might influence analyses and interpretations.

Are Quantitative Analyses the Best Tools for Answering the Proposed Research Questions?

Using qualitative and mixed-methods approaches, scholars have provided in-depth commentary on the ways that systemic inequities have shaped marginalized and minoritized students’ experiences in STEM contexts ( McGee and Bentley, 2017 ; Allaire, 2019 ). At the same time, the rise of big data has encouraged educational systems to examine the experiences of marginalized and minoritized students at the macro level ( Daniel, 2019 ). Although quantitative approaches offer unique benefits, some research questions require alternative approaches to better capture the lived experiences of minoritized students ( Covarrubias, 2011 ). For example, Jack (2019) studied the experiences of low-income students at elite institutions, showing that those who graduated from private high schools were able to navigate elite institutions better than their low-income peers who attended public high schools in their communities. A common practice in educational research tends to clump the experiences of low-income students together when studying inequity. Jack (2019) demonstrates how qualitative research has the power to capture variations within groups not easily noticeable when groups are combined in quantitative analyses. Therefore, before conducting analyses, we recommend that researchers first identify the main goals of a research project and assess whether quantitative analyses are most applicable and viable given the data available or to be collected, regardless of sample size.

Although higher education has contributed to the advancement of society, our institutions have also participated in creating and reproducing systemic inequities ( Patton, 2016 ). Our institutions, as well as the research community, can and should play a role in making the experiences of all students more equitable by first examining, with the students themselves, what those experiences are that can inform campus decision making. The misuse of quantitative data in STEM equity analyses can, even when unintended, reinforce deficit interpretations about marginalized and minoritized students and mask the role of systemic inequities. Integrating critical approaches in STEM equity analyses can provide insight into how institutions bear responsibility for the lack of diversity, representation, and differential experiences in STEM fields reflecting an unequal opportunity structure on our campuses.

In this essay, we aimed to inspire those conducting STEM equity research from a quantitative perspective to commit to an act of revision ( Laymon, 2021 ). As researchers in STEM education, we understand that career success is often dependent upon one’s ability to adopt beliefs that research and numbers are objective. We also know that researchers are encouraged to search for “silver bullets” or universal approaches in their work. In fact, we still fail at upholding all of the recommendations we have offered. However, understanding the value that statistical practices have in equity policy initiatives, we are committed to working through present-day limitations that come with the quantification of human experiences. By being upfront where our work falls short, we get closer to discovering new analytical approaches that can be used for liberatory purposes. Finally, we hope to contribute to a critical discourse and prompt reflection in an effort to make a meaningful impact that ultimately promotes equity and inclusion on our campuses and in STEM fields.

Acknowledgments

We thank Juniar Lucien for organizational contributions and insightful feedback. Additionally, this work was supported by the SEISMIC project (seismicproject.org), which is funded by the Alfred P. Sloan Foundation. SEISMIC is managed at the University of Michigan for the participating institutions, which include Arizona State University, Indiana University, Michigan State University, Purdue University, University of California Davis, University of California Irvine, University of California Santa Barbara, University of Michigan, University of Minnesota, and University of Pittsburgh.

1 For the purposes of this paper, we define minoritized and marginalized students as those who belong to identity groups that have been impacted by structural inequities (e.g., racism, sexism, and ableism) and are less represented in STEM in comparison to the American population ( National Science Foundation, 2021 ).

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23+ Quantitative Research Topics For STEM Students In The Philippines

Post author By Ankit
February 6, 2024

“Did you know only 28% of college graduates in the Philippines get degrees in STEM fields? Finding good research topics is vital to getting more Filipino students curious about quantitative studies.

With limited research money and resources, it can be hard for STEM students to find quantitative projects that are possible, new, and impactful. Often, researchers end up feeling apart from local issues and communities.

This blog post offers a unique collection of quantitative research topics for STEM students in the Philippines. Thus, drawing from current events, social issues, and the country’s needs, these project ideas will feel relevant and help students do research that creates positive change.

Philippines students can find inspiration for quantitative studies that make a difference at home through many examples across science, technology, engineering, and math.

Read Our Blog: 120+ Best Quantitative Research Topics for Nursing Students (2024 Edition)

Table of Contents

30 Great Quantitative Research Topics for STEM Students in The Philippines

Here are the top quantitative research topics for STEM students in the Philippines in 2024

1. Impact of Climate Change on Farming

Analyze how changing weather affects the growth of crops like rice and corn in different parts of the Philippines. Use numbers to find ways and suggest ways farmers can adapt.

2. Using Drones to Watch Nature

See how well drones with special sensors can watch over forests and coasts in the Philippines. Look at the data they gather to figure out how to save these places.

3. Making Solar Panels Work Better

Experiment with various ways to make more power with solar panels in sunny, humid places like the Philippines. Utilize math to guess how well they’ll work.

4. Checking How Pollution Hurts Coral Reefs

Count how much damage pollution does to coral reefs in the Philippines. Try to predict how bad it’ll get if we don’t stop polluting.

5. Watching Traffic to Fix Roads

Look at how cars move in big cities like Manila. Use math to figure out how to make traffic flow better and help people get around faster.

6. at Air and Sick People

Measure how clean the air is in various parts of the Philippines and see if it affects how many people get sick. Find out which areas need help to stay healthy.

7. Guessing When Earthquakes Might Happen

Look at data from sensors all over the Philippines to see if we can tell when earthquakes might come. Try to guess where they’ll occur next.

8. Making Water Pipes Better

Use math tricks to design cheap pipes that bring clean water to small towns in the Philippines. Think about things like hills and how many people need water.

9. Checking If Planting Trees Helps

Measure if planting trees helps stop the shore from washing away during storms. Use photos from far away and math to see if it’s working.

10. Teaching Computers to Find Sickness

Teach computers to look at pictures and records from hospitals to see if people are sick. Check if they’re good at spotting problems in the Philippines.

11. Finding Better Bags That Break Down

Test different materials like banana leaves to see which ones can be made into bags that don’t hurt the environment. Compare them to regular plastic bags.

12. Making Gardens in the City

See if we can grow vegetables in tall buildings in big cities like Manila. Use numbers to figure out if it’s a good idea.

13. Checking If Bugs Spread Easily in Crowded Places

Use computers to see if diseases spread fast in busy places in the Philippines. Look at how people move around to stop diseases from spreading.

14. Storing Energy for Islands Without Power

Think about ways to save power for small islands without electricity. Try out different ways to save energy and see which one works best.

15. Seeing How Much Storms Hurt Farms

Calculate how much damage storms do to farms in the Philippines. Use numbers to see how much money farmers lose.

16. Testing Ways to Stop Dirt from Washing Away

Try out different ways to stop dirt from being washed away when it rains. Use math to see which way works best on hills in the Philippines.

17. Checking How Healthy Local Food Is

Look at the vitamins and minerals in local foods like sweet potatoes and moringa leaves. See if eating them is good for people in the Philippines.

18. Making Cheap Water Cleaners

Build simple machines that clean dirty water in small towns. Notice if they work better than expensive ones.

19. Seeing How Hot Cities Get

Use satellites to see how hot cities like Manila get compared to places with more trees. Think about how this affects people.

20. Thinking About Trash in Cities

Look at how much trash cities in the Philippines make and find ways to deal with it. Consider what people can do to make less trash.

21. Checking If We Can Use Hot Rocks for Power

Look at rocks under the ground to see if we can get power from them. Consider whether it is beneficial for the environment.

22. Counting Animals in the Forest

Use cameras to count how many animals are in forests in the Philippines. Notice which places need the most help to keep animals safe.

23. Making Fishing Fair

Look at how many fish are caught in the Philippines and see if it’s fair. Think about ways to make sure there will always be enough fish to catch.

24. Making Power Lines Smarter

Design power lines that can change how much power they use. Try to make sure power goes where it’s needed most.

25. Looking at Dirty Water

Find out if chopping down trees and building things by rivers makes the water dirty. Think about what this means for people and animals.

26. Thinking About Big Waves

Use computers to see if big waves could hit the Philippines and what might happen. Think about how to keep people safe.

27. Seeing If Parks Help Cities

Ask people if they like having parks in their city and see what animals live there. Think about if parks make cities better.

28. Making Houses That Don’t Break in Storms

Make houses that don’t fall when there are big storms. Try to make them cheap so more people can have them.

29. Stopping Food from Going Bad

Look at how food gets from farms to people’s houses and see if we can stop it from going bad. Think about how to make sure people have enough to eat.

30. Seeing How Hot Cities Get

Put machines around cities to see how hot they get. Consider how this affects people and what we can do to help.

These topics will help you to make a good project that assists you in getting better scores.

Importance Of Quantitative Research For STEM Students

Read why quantitative research matters to Filipino students.

Helps us understand problems more clearly by revealing trends, patterns, and connections in the data
Provides an accurate picture by removing personal biases and opinions
Allows quantitative comparison of results if studies use the same methods
Enables testing hypotheses and theories through experiments that can prove/disprove predictions
Allows replication and verification as other researchers can redo experiments and study methods
Numbers give a more precise, factual understanding compared to qualitative data.
Removes subjectivity through quantitative data rather than opinions
A key part of the scientific process is that data helps confirm or reject proposed explanations.
Overall, collecting and analyzing quantitative data is crucial for gaining insights, testing ideas, ensuring consistency, and reducing bias

It’s time to see what challenges students face with their quantitative research.

Challenge Philippines Students Face With Their Quantitative Research

Here are the common challenges that students face with their quantitative research topics:

Lack of resources and funding

Doing quantitative research needs access to equipment, software , datasets etc, which can be costly. Many students lack funding and access to these resources.

Lack of background in mathematics and statistics

Quantitative research relies heavily on math and statistical skills. However, many students haven’t developed strong enough skills in these areas yet.

Difficulty accessing scholarly databases

Students need access to academic journals and databases for literature reviews. However, these can be costly for people to access.

Language barriers

Many of the academic literature is in English. This can make reading and learning complex statistical concepts more difficult.

Lack of mentorship

Having an experienced mentor to provide guidance is invaluable. However, not all students have access to mentorship in quantitative research.

Managing large datasets

Collecting, cleaning and analyzing large datasets requires advanced technical skills. Students may struggle without proper guidance.

Presenting results clearly

Learning how to visualize and communicate statistical findings effectively is an important skill that takes practice.

Ethical challenges

Ensuring quantitative studies are designed ethically can be difficult for novice researchers.

Writing scientifically

Adopting the formal, precise writing style required in quantitative research is challenging initially.

Maintaining motivation

Quantitative research is complex and time-consuming. Students may lose motivation without a strong support network.

While quantitative research presents many challenges, Philippines STEM students can overcome these through access to proper resources and support. With hard work, mentorship and collaborative opportunities, students can build essential skills and contribute to the quantitative research landscape.

Tips For Conducting Quantitative Research In The Philippines

When conducting research in a new cultural context like the Philippines, it is vital to take time to understand local norms and build trust. Approaching research openly and collaboratively will lead to more meaningful insights.

1. Get Required Approvals

Be sure to get any necessary ethics reviews or approvals from local governing boards before conducting the analysis. It is wise to follow proper protocols and permissions.

2. Hire Local Assistants

Hire local research helpers to help navigate logistics, translation, and cultural sensitivities. This provides jobs and insider insights.

3. Use Multiple Research Methods

Triangulate findings using interviews, focus groups, surveys, participant observation, etc. Multiple methods provide more potent and well-rounded results.

4. Verify Information

Politely verify information collected from interviews before publication. Follow up to ensure accurate representation and context.

5. Share Results

Report back to participants and communities on research findings and next steps. This shows respect and accountability for their contributions.

6. Acknowledge Limitations

Openly acknowledge the limitations of perspective and methods as an outside researcher. Remain humble and keep improving approaches.

Keep in mind, when entering a new community to conduct research, taking an open, patient, and collaborative approach leads to more ethical and meaningful results. Thus, making the effort to understand and work within cultural norms demonstrates respect.

STEM students in the Philippines have many possible research topics using numbers. They could look at renewable energy, sustainability, pollution, environment, disease prevention, farming improvements, preparing for natural disasters, building projects, transportation, and technology access.

By carefully analyzing statistics and creating mathematical models, young Filipino researchers can provide key ideas to guide future policies and programs. Quantitative research allows real observations and suggestions based on evidence to make the country better now and later.

Number-based methods help young researchers in the Philippines give tangible recommendations to improve their communities.

How can I limit my choices and pick the right research topic?

Think about what you enjoy and what you’re skilled at. Consider if your topic is meaningful and if you have the resources to study it. Get advice from teachers or friends to help you decide.

What are some common problems in doing math research in science, technology, engineering, and math?

Problems might include: 1. Finding data. 2. Make sure your measurements are correct. 3. Following rules about ethics. 4. Handling big sets of data.

How can I make sure my research is done well?

Plan your study carefully, use the correct methods and tools, write down everything you do, and think about the strengths and weaknesses of your work.

Tags Quantitative Research Topics For STEM Students In The Philippines
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Curated Funding Opportunities in STEM, including Quantitative Social Sciences

Selected open funding opportunities.

RDO curates this list of open funding opportunities in STEM* to highlight large, collaborative, and/or strategic funding opportunities that may be of particular interest to the Stanford community. Please note that STEM* includes social sciences that utilize quantitative methods.

Summaries of selected funding opportunities have been compiled from Grants.gov, Grants.ca.gov, and other agency announcements below. See our Find Funding Overview for more ways to search funding opportunities in your area of interest. This page will be regularly updated to spotlight new opportunities.

Looking for something you've seen here in the past? Review past opportunities in our archive (SUNet ID required).

Find medical-related funding opportunities at Stanford Medicine's Research Management Group

Find more funding opportunities from the State of California at the California Grants Portal

Foundations

Find more funding opportunities from foundations at Stanford University Corporate and Foundation Relations

Other funding opportunities can also be found on the funding page curated by Stanford's Office of Technology Licensing

Recurring Funding Opportunities by Topic

NSF opportunities in climate and sustainability , last update June 2023
DEIA opportunities , last update June 2023
Federal Instrumentation and Infrastructure grants , last update June 2023
Recurring Limited Submissions Programs
Collaborative Funding Mechanism list compiled by the National Organization of Research Development Professionals
NSF Growing Convergence Research program
NSF Research Coordination Networks meant to foster communication and collaborations in a new or developing area of science or engineering
Life Sciences
Physical Sciences and Engineering
Social and Behavioral Sciences

Funding Opportunities in the Humanities, Arts, and Interpretive Social Sciences

The RDO team also curates a list of funding opportunities for researchers in the Humanities, Arts, and Interpretive Social Sciences .

Created: 09/23/21

Updated: 05/30/24

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Global Quantitative Analytics Summer 2025 Analyst

Learn about our different businesses

Global Risk Management

Charlotte, NC; Atlanta, GA; Chicago, IL; Jersey City, NJ; New York, NY

Apply by October 19, 2024

What you'll do

Global Risk Development Program (QMAP) - 2025

What would you like the power to do?

At Bank of America, we value being a Great Place to Work. We recognize that talented, engaged and satisfied employees are the foundation to help make the financial lives of our customers and clients better.

Bank of America provides a diverse range of banking and nonbanking financial services and products domestically and internationally in more than 35 countries .

Global Quantitative Summer Analyst Program Overview:

The Global Quantitative Summer Analyst Program is a summer internship and precursor for the Global Quantitative Analytics Development Program designed to develop and coach analytical and quantitative talent to be deployed throughout various Bank of America business groups.

As an Intern, you will gain in-depth experience and be provided micro and macro views of risk management for the bank. Interns will complete on-the-desk work with their assigned team and apply quantitative knowledge to specific financial challenges.

Your development is our top priority with on-the-job support, events and mentorship throughout. These opportunities include but are not limited to:

Bank-provided learnings focused on our seven key risk types (Strategic, Credit, Market, Liquidity. Operational, Compliance and Reputational Risk), as well as topics such as Modeling Principles, Software Development Life Cycle, Data Science and Analytics, latest Regulatory developments and more
Intern Mentorship Program
Enterprise Executive Speaker Series
Employee Diversity & Inclusion Networks LEAD for Women, Black Professional Group, LGBT+ Pride, and more
Continuous Educational Speakers and Events
Networking Events

A Day in the Life

Quantitative Analytics internships last 10 weeks and provide participants the opportunity to work on various tasks leveraging programming, data analysis, modeling, and other technical skillsets to understand how the bank makes key decisions. As a Summer Analyst, you will be placed on one team where your primary responsibilities may include but are not limited to:

Developing emerging riskassessments and analyzing credit risk scenarios
Quantitative modeling, including building forecast models, pricing models, and stress test models
Conducting research and analysis to provide a micro view of risk management in a particularbusiness line and a macro view of risk management for the bank as a whole
Assessing market trendsand providing quantitative data for internal partners and ultimately, clients
Applying quantitativeknowledge to specific financial challenges and projects specific to yourbusiness alignment
Implementing solutionsapplying both qualitative and quantitative methods
Networking with risk executives and key stakeholders to cultivate meaningful relationships across various lines of business

Quantitative Analytics Opportunities

The Global Quantitative Summer Analyst Program assigns interns to teams across the enterprise. Internship opportunities include positions supporting various business groups, such as the below:

*Intern team assignments are developed based on business need and aligned to skillset and therefore cannot be guaranteed.

Qualifications

Candidates are required to be pursuing an undergraduate or masters degree from an accredited college or university. Eligible candidates must have a graduation timeframe between November 2025 and August 2026.
GPA of 3.5 or higher is preferred
Common areas of study include but are not limited to:
Candidates should possess a high level of intellectual curiosity, a drive for excellence, and a commitment to achieving sustainable results. Additionally, students should hold strong academic and technical skills as well as show proficiencies in leadership, teamwork, problem solving & analytical skills, verbal and written communication, and professionalism.
Candidates must have advanced programming skills, including but not limited to Python, SQL, R, and/or C++.
Masters candidates should have no more than 2 years of work experience.
Bank of America does not complete third party forms from colleges, universities, or other parties.

Interested in the Global Quantitative Analytics Summer 2025 Analyst Program?

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Active funding opportunity

Nsf 24-578: hispanic serving institutions: equitable transformation in stem education (etse), program solicitation, document information, document history.

Posted: May 24, 2024

Program Solicitation NSF 24-578

Full Proposal Deadline(s) (due by 5 p.m. submitting organization’s local time):

September 11, 2024

August 27, 2025

Last Wednesday in August, Annually Thereafter

Important Information And Revision Notes

The Hispanic Serving Institutions: Equitable Transformation in STEM Education (HSI: ETSE) solicitation is a part of the larger Improving Undergraduate STEM Education (IUSE): Hispanic Serving Institutions (HSI) program at NSF. The IUSE: HSI program funds a breadth of projects across HSIs. Prospective Principal Investigators (PIs) are encouraged to carefully review this solicitation and NSF Hispanic-Serving Institutions: Enriching Learning, Programs and Student Experiences (ELPSE) to determine which opportunity fits a particular proposal.

With this new Equitable Transformation in STEM Education (ETSE) competition, the HSI program is introducing two new tracks, (1) Departmental/Division Transformation Track which centers on the transformation of a single department or division within an institution; and (2) Emerging Faculty Research is a new track that invites proposals from individual investigators at 2- and 4-year Primarily Undergraduate Institutions (PUIs), including community colleges, to engage in STEM research, including undergraduate STEM education or STEM broadening participation research.

The HSI program team will host webinars in which key features and expectations of the HSI program will be discussed. Information regarding the webinars will be posted to the HSI program webpage for this solicitation.

Any proposal submitted in response to this solicitation should be submitted in accordance with the NSF Proposal & Award Policies & Procedures Guide (PAPPG) that is in effect for the relevant due date to which the proposal is being submitted. The NSF PAPPG is regularly revised and it is the responsibility of the proposer to ensure that the proposal meets the requirements specified in this solicitation and the applicable version of the PAPPG. Submitting a proposal prior to a specified deadline does not negate this requirement.

Summary Of Program Requirements

General information.

Program Title:

Hispanic Serving Institutions: Equitable Transformation in STEM Education (ETSE)

Hispanic Serving Institutions (HSI) are an important component of the nation’s higher education ecosystem and play a critical role in realizing the National Science Board Vision Report for a more diverse and capable science and engineering workforce. Aligned with this vision and the NSF Strategic Plan 2022 -2026 the goals of the NSF HSI Program are to: Enhance the quality of undergraduate science, technology, engineering, and mathematics (STEM) education at HSIs. Increase the recruitment, retention, and graduation rates of students pursuing associate’s or baccalaureate degrees in STEM at HSIs. Meeting these goals requires institutions to understand and embrace their students’ strengths, challenges, identities and lived experiences. This can happen in many ways and across many areas of an institution. As such, the IUSE: HSI program provides multiple opportunities to support an institution’s goal to become more student centered, including the Equitable Transformation in STEM Education (ETSE ) competition. This competition includes the following tracks: Departmental/Division Transformation Track (DDTT) - New Institutional Transformation Track (ITT) Emerging Faculty Research Track (EFRT) - New HSI Program Resource Hubs (Hubs) This solicitation will also accept conference proposals and planning proposals, as defined by the PAPPG . The ETSE competition focuses on (1) institutional transformation projects that support HSIs in their effort to achieve equity in STEM education, and (2) the infrastructure—the HSI-Net network of resource hubs—which supports the overall program goals. Institutions are encouraged to consider how their HSI designation, and their organizational mission align to better support STEM success of all students. The ETSE competition welcomes proposals that look to implement and evaluate promising practices and/or conduct research related to broadening participation or improving recruitment, retention, graduation, and other successful outcomes in STEM undergraduate education. The ETSE solicitation supports projects designed to catalyze change and help HSIs meet students where they are, accounting for their assets and the challenges they may face. Identities and experiences are not determined solely by membership in a single monolithic population of students (e.g., Hispanic, first-generation, commuter, etc.). Consequently, institutions are expected to use institutional data to identify equity gaps, identify areas of need, and unpack the factors that shape students’ individual identities and shared experiences. The perspectives gained from this data should be central to the design of the proposed project. Please see below for specific information about each track. While proposals are focused on mechanisms for transforming undergraduate STEM education, projects should also consider student voices and include mechanisms to aggregate and analyze existing student feedback and collect quantitative and qualitative student data throughout the life of the proposed project.

Cognizant Program Officer(s):

Please note that the following information is current at the time of publishing. See program website for any updates to the points of contact.

Sonja Montas-Hunter, telephone: (703) 292-7404, email: [email protected]

Michael J. Ferrara, telephone: (703) 292-2635, email: [email protected]

James Alvarez, telephone: (703) 292-2323, email: [email protected]

Sonal S. Dekhane, telephone: (703) 405-8977, email: [email protected]

Elsa Gonzalez, telephone: (703) 292-4690, email: [email protected]

Julio G. Soto, telephone: (703) 292-2973, email: [email protected]

47.076 --- STEM Education

Award Information

Anticipated Type of Award: Standard Grant or Continuing Grant

This Program anticipates making:

Award Size: Up to $1,000,000
Award Length: For up to five-year-long projects
Award Size: Up to $3,000,000
Award Length: For five-year-long projects
Award Size: Up to $200,000
Award Length: For up to three-year-long projects

Anticipated Funding Amount: $20,000,000

The number of new awards is subject to the availability of funds.

Eligibility Information

Who May Submit Proposals:

Proposals may only be submitted by the following: With the exception of conference proposals, proposals may only be submitted by the following: To be eligible for funding an institution must meet the following criteria: Be an accredited institution of higher education. Offer Undergraduate STEM educational programs that result in certificates or degrees. Satisfy the definition of an HSI as specified in section 502 of the Higher Education Act of 1965 (20 U.S.C. 1101a) and meet the eligibility of an HSI by the U.S. Department of Education definition. Documentation (eligibility letter) from the Department of Education confirming HSI designation must be submitted as a supplemental document. Additional requirements to be eligible for funding in the Emerging Faculty Research Track (EFRT), the institution must meet the four criteria listed above at the time of submission and: Be an eligible Primarily Undergraduate Institution (PUI) [ 1 ]. Eligible PUIs are accredited colleges and universities (including two-year community colleges) that award Associate's degrees, Bachelor's degrees, and/or Master's degrees in NSF-supported fields, but have awarded 20 or fewer Ph.D./D.Sc.. degrees in all NSF-supported fields during the combined previous two academic years.

Who May Serve as PI:

ITT proposals require an upper-level administrator with decision-making authority (i.e. Dean or higher) as PI or co-PI. For DDTT proposals, the unit head, chair, or equivalent should be a PI or co-PI for the duration of the project. No restrictions for Hub and EFRT proposals.

Limit on Number of Proposals per Organization:

DDTT proposals: Eligible institutions with an active Track 3: Institutional Transformation project (ITP) award from NSF 22-611 , NSF 22-545 , or NSF 20-599 or an active ITT award from this solicitation must describe how the proposed DDTT project is compatible with the efforts being undertaken by the active award. ITT proposals: Eligible institutions may submit one proposal and may not have an active Track 3 Institutional Transformation Project (ITP) award from, NSF 22-611 , NSF 22-545 , or NSF 20-599 . Institutions with an active DDTT award from this solicitation must describe how the proposed ITT project is compatible with the departmental/divisional transformation effort being undertaken by the active award. EFRT and Hub proposals: No Restrictions

Limit on Number of Proposals per PI or co-PI:

For DDTT, ITT and EFRT, an individual may be listed as PI or co-PI on only one proposal. An individual may only serve as a PI or co-PI on one Hub proposal or active Hub project at any time.

Proposal Preparation and Submission Instructions

A. proposal preparation instructions.

Letters of Intent: Not required
Preliminary Proposal Submission: Not required

Full Proposals:

Full Proposals submitted via Research.gov: NSF Proposal and Award Policies and Procedures Guide (PAPPG) guidelines apply. The complete text of the PAPPG is available electronically on the NSF website at: https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg .
Full Proposals submitted via Grants.gov: NSF Grants.gov Application Guide: A Guide for the Preparation and Submission of NSF Applications via Grants.gov guidelines apply (Note: The NSF Grants.gov Application Guide is available on the Grants.gov website and on the NSF website at: https://www.nsf.gov/publications/pub_summ.jsp?ods_key=grantsgovguide ).

B. Budgetary Information

Cost Sharing Requirements:

Inclusion of voluntary committed cost sharing is prohibited.

Indirect Cost (F&A) Limitations:

Not Applicable

Other Budgetary Limitations:

Other budgetary limitations apply. Please see the full text of this solicitation for further information.

C. Due Dates

Proposal review information criteria.

Merit Review Criteria:

National Science Board approved criteria. Additional merit review criteria apply. Please see the full text of this solicitation for further information.

Award Administration Information

Award Conditions:

Additional award conditions apply. Please see the full text of this solicitation for further information.

Reporting Requirements:

Standard NSF reporting requirements apply.

I. Introduction

The National Science Foundation’s Improving Undergraduate STEM Education: Hispanic Serving Institutions (HSI) Program is part of a Foundation-wide effort to accelerate improvements in the quality and effectiveness of undergraduate education in all STEM fields including the learning, social, behavioral, and economic sciences. As its name implies, the HSI program specifically supports initiatives to (1) enhance the quality of undergraduate science, technology, engineering, and mathematics (STEM) education and (2) increase the recruitment, retention, and graduation rates of students pursuing associate’s or baccalaureate degrees in STEM at colleges that have been designated as Hispanic Serving Institutions (HSIs). To achieve these goals and with Congressional support , the HSI program aims to build capacity at Hispanic-serving institutions. Building organizational capacity, as encouraged by the explanatory statement of the Consolidated Appropriations Act, 2017 Public Law 115-31, is concerned with creating and implementing flexible systems that support new and old ideas. Building capacity should involve developing structures that foster student and/or faculty growth while meeting the students where they are in their college careers academically, financially, and socially. Institutional structures may also include sociocultural supports and collaborative processes that promote effective learning environments and inclusiveness as well as mechanisms to support students’ personal development and professional learning.

To accomplish these goals, the IUSE HSI program runs multiple competitions annually. One of these is a competition for the Equitable Transformation in STEM Education (ETSE) . Recognizing the diverse nature and context of HSIs, ETSE is designed to support HSIs with varying structures and diverse student populations, including newly designated HSIs, to engage in organizational change efforts to support equitable learning outcomes for all its students.

NSF HSI program seeks to improve efforts aimed at enhancing the preparation, participation, and contributions of groups that have been historically excluded and/or underserved in the STEM enterprise. As such, proposers are encouraged to use an intersectional lens[ 2 ] perspective in designing proposals across all tracks in the HSI program. Intersectionality is an approach that considers the interconnectedness of overlapping social identities and can help shape a project's design and conceptualization of inclusivity to better serve students at HSIs. An intersectional approach to institutional transformation in a student-centered learning environment could significantly support the ability to leverage the full spectrum of diverse talent that society has to offer which helps to increase the diversity of undergraduate STEM degrees awarded and STEM professionals across the nation.

The Equitable Transformation in STEM Education (ETSE) solicitation accepts proposals in four tracks. Additional opportunities for planning and conference proposals are also discussed below.

Departmental/Division Transformation Track (DDTT): This new track focuses on strengthening STEM education through the transformation of academic departments or divisions which are in turn shaped by the personnel, leadership, practices, and disciplinary culture of these distinct and often interconnected units. These projects should provide opportunities for departments and divisions to scrutinize their policies and practices, invest in current and future leaders, and challenge narrow or exclusionary disciplinary norms that can sustainably drive positive student outcomes.
Institutional Transformation Track (ITT) : The Institutional Transformation track should articulate a vision for unifying academic equity research, practice, and policy to strengthen an institutional understanding of student learning outcomes from the context of the diverse community it serves. These projects seek to 1) support the planning and implementation of institutional research infrastructure efforts which results in institution-wide efforts toward broadening participation in STEM and 2) engage students in STEM undergraduate best practices and effectively guide students toward careers in STEM and/or graduate programs.
Emerging Faculty Research Track (EFRT ): The EFRT track is a new track that invites proposals from individual investigators at 2- and 4-year PUIs, including community colleges, to engage in STEM research, including undergraduate STEM education or STEM broadening participation research. The specific objectives of EFRT projects should (1) enhance faculty opportunities at PUIs and two-year colleges to conduct STEM Research, STEM education research and/or Broadening Participation research and (2) improve understanding of factors that advance positive student learning outcomes and effective STEM broadening participation efforts.
HSI Program Resource Hubs (HSI Hubs) : Hub projects should be designed to promote research and support collaboration within the HSI community, including prospective PIs, to build capacity at HSIs. The HSI-Hubs will support initiatives and activities that address any area(s) of need in the HSI community, identified by the proposer and community, and supported by evidence. These should be designed to effectively serve the HSI STEM communities and increase the participation of the full spectrum of diverse talent to include historically underrepresented individuals/communities in STEM.

The ETSE Competition also accepts planning proposals for Departmental/Division Transformation and Institutional Transformation tracks. Please review PAPPG guidelines on how to submit a planning proposal.

II. Program Description

The HSI program is guided by student-centered frameworks that build an intentional and supportive environment for students and reinforce cultural and mindset shifts that support the success of all students at HSIs. Proposals should discuss project designs that are based on data-informed decision-making processes to operationalize an institution’s student-centered approach.

This competition is designed to leverage existing institutional strengths for advancing efforts toward student-centered environments[ 3 ]. Proposals to ETSE should impact the STEM learning landscape, result in equitable undergraduate STEM degree attainment for all students, and position students for successful transition and retention into the STEM workforce or graduate education.

Competition Tracks This competition accepts proposals for four project tracks. Additional opportunities for planning and conference proposals are discussed later in the document.

Departmental/Division Transformation Track (DDTT) . The Departmental/Division Transformation Track is new to the HSI program and focuses on supporting transformation through building STEM research capacity and infrastructure at the departmental, divisional- or college level. It is intended to provide opportunities for an end-to-end self-study of a discipline(s)’s culture, students’ experiences, and more granular academic outcomes. Proposals should prioritize “building people capacity” as a foundational element for institutional transformation and consider the collective needs of all stakeholders.

These projects should: (1) strengthen academic capacities, including investing in STEM leaders at the college, departmental, or division level; (2) develop and enhance sociocultural academic support to broaden participation in STEM education; (3) support the design and implementation of an organizational self-assessment to collect and analyze data to identify STEM inequities in a specific discipline or connected disciplines in a department, unit or college; and (4) develop a project design that takes into consideration a student-centered framework, such as “Servingness,[ 4 ]” “Intersectionality” or “Growth-Mindset[ 5 ]” to promote a learning environment that intentionally positions the student at the center of the academic experience to ensure that all students have meaningful opportunities to realize their fullest potential and as a result, strengthens the ability of academic programs to attract, retain, and graduate students in the STEM disciplines of focus.

The specific objectives of DDTT projects must: (1) increase student engagement in evidence-based practices that result in positive STEM student learning outcomes; and (2) develop and engage all members of the focal academic department or division, as well as administrators, staff, and both full-time and part-time faculty as appropriate.

The unit head, chair, or equivalent must be a PI or co-PI for the duration of the project, and the role of this individual should be central to the proposed project and clearly described in the project narrative. Proposals are also encouraged to devote funds towards a project coordinator who can help support data collection and analysis, organize project activities, and attend to the multifaceted requirements for STEM transformation.

An emphasis of this track is to also enable institutions with limited or no research capacity, including PUIs, two-year institutions, including community colleges, to expand and build STEM capacity. Proposals from PUIs and community colleges are encouraged to propose meaningful partnerships with external organizations to grow programs in workforce development, research and development (R&D), and/or the translation of research to practice in emerging technology fields.

Institutions whose goal is to advance from one research classification to another (e.g., achieving R2 Carnegie classification ) are also encouraged to submit to this track.

The project description for successful proposals to the DDTT are strongly encouraged to:

Establish a direct connection to the long-term strategic plan of the host department(s).
Discuss the adaptation/replication of known evidence-based strategies and/or design and implementation of new strategies that will impact the STEM discipline(s) that are the focus of the project. The approaches taken to improve undergraduate STEM education should clearly align with the data narrative and baseline data should inform the development of clear goals highlighting how the proposed change effort might close equity gaps or otherwise measurably improve student engagement, experiences, and outcomes.
Include formal and informal leadership development activities for individuals across the unit (e.g., faculty, unit chairs or heads, staff members, leads for multi-section courses). Projects are encouraged to consider how the unit will identify and prepare future leaders and how equitable, engaged mentoring, advising, and other practices can serve as loci of leadership development and drivers of positive change.
Discuss a plan for the assessment of division/department-level and institutional factors, including how the institutional designation as an HSI intertwines with its climate, culture, practices, and outcomes. Proposals are encouraged to leverage qualitative and quantitative data streams spanning all stakeholders as institutional research data alone cannot fully capture the breadth of the students’ lived experiences within an institution.

The inclusion of student voice and feedback is critical to DDTT, and proposals must include mechanisms to aggregate and analyze existing student feedback and collect quantitative and qualitative student data throughout the life of the proposed project. Proposals are encouraged to include student members as part of the project leadership team or advisory boards to serve as liaisons with their peers and ensure that their viewpoints are clear and understood. Student leaders should be appropriately compensated for their time and effort.

Institutional Transformation Track (ITT). Proposals to the Institutional Transformation track should articulate a vision for unifying academic equity research, practice, and policy to strengthen an institutional understanding of student learning outcomes from the context of the diverse community it serves. All institution types are encouraged to apply, especially PUIs (including community colleges). Proposals are encouraged to consider moving efforts from enrollment-driven strategies to student-centered principles. These projects seek to support the planning and implementation of institutional research infrastructure efforts which results in institutional-wide efforts toward broadening participation in STEM while engaging students in STEM undergraduate best practices to effectively guide students toward careers in STEM and/or graduate programs.

While ITT proposals do not need to carry out the proposed activities in all STEM disciplines at the institution, a substantial subset of those disciplines should be integrated into the transformation effort across the proposed project period. This should go substantively beyond an effort to transform undergraduate STEM education within a single department, division, school, or college. Furthermore, the sustainability plan presented should clearly discuss how the institution will implement successful practices into departments and disciplines that are not fully engaged in the proposed work during the project period.

ITT proposals should incorporate a theory of change that informs the overall project design and should further be grounded in STEM education research and broadening participation research to enhance student outcomes in STEM. The project design should lead to institutional infrastructure and policy changes to support long-term institutional changes that encourage and support faculty to implement evidence-based practices that enhance student outcomes in STEM.

ITT projects may include a plan to conduct research that advances understanding of institutional culture and identity on students' learning outcomes in undergraduate STEM education. Such research should result in a strategic understanding of the complex characteristics of students at HSIs and how multi-faceted strategies work synchronously to advance equity in STEM education. This may be achieved through posing one or more research questions that will be answered through the course of the study or through evaluation of project activities, impacts, or outcomes. Projects should include a well-designed plan to gather data and should specify methods of analysis that will be employed to address questions posed and mechanisms to evaluate the success of the project. Projects should also specify strategies for generating and using formative and summative assessments of project processes, outputs, and/or outcomes. Proposals that include a research plan must include a plan that discusses dissemination and must also discuss how the research will generate knowledge to make an impact on how HSIs can transform STEM education.

Project Descriptions for successful proposals to the Institutional Transformation Track (ITT) are strongly encouraged to:

Discuss the proposal’s alignment with the institutional strategic plan to improve the enrollment, retention, and graduation of STEM associates and baccalaureate degrees.
Discuss how the proposed ITT project will leverage and/or complement existing programs and initiatives to help the institution move towards a more student-centered undergraduate STEM ecosystem.
Articulate the creation of institution-wide strategies to transform their policies or practices to foster inclusive STEM learning environments that promote equitable student learning and engagement in all STEM disciplines at the proposing HSI.
Comprise a multidisciplinary team with the expertise and experience needed to implement the proposed project. The PI team may have members from other institutions or non-profit organizations to augment the team's expertise, which should be explained in the project description and management plan. (For more information on the project management plan see required components for all proposals in the Proposal Preparation section of the Competition.) The project team should include an upper-level administrator with institution-wide responsibility and authority over STEM education at the institution (i.e. Provost, VP of Academic Affairs or equivalent).
Provide evidence of institutional commitment to the proposed work as part of the proposal.

Proposers should be aware that ITT projects will be formally reviewed via a formal Reverse Site Visit prior to the conclusion of the project's third year. If necessary, this may be followed by a formal site visit. Continued funding of ITT project will be contingent on the results of the reverse site visit and/or site visit review.

Common Expectations for proposals to DDTT and ITT Tracks

The sections must be included in the project description:

An institutional data narrative to determine baselines, set goals, and evaluate impact. The institutional data should contextualize the institution's need and ability to provide undergraduate STEM education promoting a more competitive, diverse, and capable STEM workforce. The institutional data narrative should serve as a foundation for the adoption of an intersectional lens to the project design.
A discussion on how the project design applies an intersectional lens that supports the context from which the institution proposes to address academic equity gaps in STEM. Intersectional perspectives are important for identifying academic equity challenges and solutions for underrepresented populations in STEM. Intersectional perspectives are also important for identifying factors that need attention to effectively support those populations whose social identities, in addition to gender, race, and ethnicity, such as age, disability; economic status (e.g., Pell recipients), and first-generation status impact the learning environment. As a result, an intersectional lens provides an opportunity to intentionally engage in strategies that leverage the full spectrum of diverse talent.
A discussion on a theory of change[ 6 ] that supports the project in taking actionable steps to transform policies, practices, relationships, approaches, and/or mindsets, to make the STEM environment more inclusive, advance equity, and broadening participation in STEM at HSIs.
A project evaluation plan that is based on S.M.A.R.T. (Specific, Measurable, Attainable, Realistic, and Time-bound) goals . Evaluation plans should include a logic model as a supplementary document. In addition to quantitative and/or qualitative methodologies, it is encouraged that evaluation plans include measures of success for non-academic outcomes (i.e. STEM identity, academic self-concept, graduate aspirations). Project evaluator(s) should be independent to the project and named in the Project Description section of the proposal. Proposals should: (1) describe the expertise of the evaluator(s); (2) explain how that expertise relates to the goals and objectives of the proposal; and (3) specify how the PI will report and use the results of the project's external review process and incorporate the recommendations to improve the project. The biosketch(es) of the external evaluator(s) should be uploaded as a supplementary document.
Describe a dissemination plan that includes activities beyond conferences and journal articles to reach interested disciplinary communities, leaders, and scholars. While conferences and journals may be an integral part of a dissemination plan, PIs should consider how they will assemble and reach an audience that could benefit from their project’s findings.
Describe a sustainability plan that demonstrates how activities and practices are being integrated into an institution’s overall undergraduate STEM culture and are transforming how institutions support and develop activities for enrollment in, and completion of a STEM degree. Proposals should include preliminary sustainability plans for the continuation of a project’s goals and efforts to achieve desired outcomes beyond the funding period.
If hiring undergraduate students, a student mentoring plan is required. This solicitation specific required plan is separate and distinct from the mentoring plan required by the PAPPG of proposals that request funding to support postdoctoral scholars or graduate students and should be included as a supplementary document.
Include a discussion that outlines a strategy for leveraging previous awards from the HSI program from NSF 22-611 , NSF 22-545 , or NSF 20-599 , if applicable.

Emerging Faculty Research Track (EFRT). The EFRT track is a new track that invites proposals from individual investigators at two-year institutions, including community colleges and primarily undergraduate institutions (PUIs) to engage in STEM research, including undergraduate STEM education Research or STEM broadening participation research. Proposals from individuals looking to develop a new scholarly program or have an established record of scholarship in these areas are equally welcome.

Awards through this track are intended to strengthen the community of teacher-scholars at these institutions, allow investigators to strengthen existing scholarly endeavors or explore new opportunities, have a positive impact on faculty and student development, and/or develop inclusive environments in STEM.

EFRT projects are expected to increase research activity at primarily undergraduate institutions, including community colleges. As result, EFRT projects should increase knowledge about effective STEM education practices on engaged student learning and broadening participation at HSIs. The specific objectives of proposed EFRT projects should (1) improve understanding of what leads to positive student learning outcomes and effective broadening participation efforts and (2) strengthen the community of undergraduate STEM education or broadening participation researchers at PUIs and two-year colleges.

Proposals to EFRT will support single-investigators' research in all disciplines supported by NSF. These include: (1) theoretical or applied STEM research that is inter-, multi-, or trans-disciplinary, (2) discipline-based STEM education research, and/or (3) STEM broadening participation research. Regardless of focus, research should support the overarching goals of the HSI program which seeks to improve and enhance undergraduate STEM education, including undergraduate student research experiences. Proposals should discuss alignment with the long-term plans of the investigator’s department, division, school/college, or institution. This includes the institutional mission and plans for expanding institutional research capacity and increasing the production of STEM baccalaureate degrees.

Engaging undergraduate researchers in authentic research experiences is an established high-impact practice. Proposals that include opportunities for undergraduates in any NSF-supported discipline to engage in STEM research, including the core education or broadening participation research are encouraged. Proposals which include the support the success of students who have historically not engaged in STEM undergraduate research activities and are impacted by academic inequities are strongly encouraged. Projects that involve undergraduates should include a specific discussion of students’ roles, duties, and training. Proposals should also address the PI’s readiness to engage in supporting undergraduate research and mentoring students of diverse backgrounds. Please note that a student mentoring plan should also be submitted as a supplementary document for any project that involves undergraduates involved in roles other than as study participants.

Interdisciplinary research projects and projects focused on training students in emerging technologies or areas of national interest (i.e. artificial intelligence, environmental change, quantum information systems, advanced manufacturing, etc.), as outlined in the NSF Strategic Plan 2022-2026 , are strongly encouraged.

The Project Description for each EFRT proposal must contain the following elements:

An overview of the PIs overall research, education, and professional goals.
Background and justification for proposed research, supported by the relevant literature, along with appropriate research questions and hypotheses. Theoretical or conceptual frameworks should be incorporated as appropriate for the specific nature of the proposed study.
Information on how the proposed research will contribute to the literature on how to effectively impact broadening participation in STEM and/or advance STEM education research at HSIs.
A discussion of data streams, sampling methods, and methodologies to be employed. Proposals that include the development or adaptation of surveys, rubrics, or other data collection tools should also include a clear plan for validating those items. Please note that the EFRT track does not favor any particular approach, method, or type of data, but rather asks proposers to carefully consider which approaches would be best suited to address the issues and research questions presented.
A detailed timeline that clearly presents data collection points and timeframes for analysis, and other key research activities.
A plan for how the progress of the project will be assessed. Proposals from investigators new to STEM education or broadening participation research are encouraged to include an advisory board or formal, experienced mentor to guide their scholarly journey throughout the project.
A plan for dissemination of project outcomes.
A letter of commitment from the PI's Department Chair or Dean stating that the PI will have institutional support in terms of allowance to utilize project funds for release time, travel for research purposes, or access to existing research facilities, as appropriate. This should be included as a supplementary document.

Budget: Funds requested for EFRT proposals are intended to support investigators’ specific needs and may include, but are not limited to the following: faculty release time; technical support for research; faculty and student professional development; travel to conferences; acquisition or upgrading of research equipment; development of special topics or seminar courses; and collaborative research efforts including travel to collaborating institutions or travel for collaborators to visit the PI at their home institution. The budget may include support for student trainees or post-doctoral fellows. EFRT proposals can be used to support sabbatical activities, including providing salary supplements in cases where the proposing institution does not provide full salary support.

HSI Program Resource Hubs (HSI-Hubs) . Through the ETSE competition the HSI program will continue to support the HSI Hubs, as part of the HSI-Net infrastructure. HSI-Hubs will provide support for specific areas of need and of importance to the HSI community and will serve the HSI community at large, and its stakeholders, including current and potential HSI awardees. The Hub proposal may focus on one or several critical aspects of HSIs such as institutional transformation, capacity building for specific institution types or specific disciplines, and research on broadening participation that may effectively impact STEM degree production.

Possible topics may include institutional transformation, capacity building at HSIs, STEM leadership development of all faculty to include scholars from historically underrepresented groups, research and dissemination, intersectionality and partnerships, effective frameworks designed for HSI; or any other area critical to the HSI community that supports the goals and strategies of the HSI program. This listing of possible thematic areas is not meant to be exclusive. Rather, NSF expects prospective PIs to define the need, cite evidence establishing the needs at HSIs, and offer a clear recommended plan with activities and measurable objectives and solutions. PIs are encouraged to put forward critical areas and ideas that are important to the HSI community and its unique and diverse ecosystem. All HSI- Hubs must propose and budget for activities related to the hub's critical areas.

The project description must:

Provide a description for the development and implementation of a resource hub that would provide services, resources, and/or knowledge generation pertaining to specific areas of need in the HSI community.
Articulate a discussion on how the hub identifies, develops, and promotes promising innovative research or initiatives and successful practices and frameworks that generate valuable new knowledge and systemic change for STEM education at HSIs.
Develop a plan to provide intellectual infrastructure for collaborations with the potential to expand the knowledge base about HSIs.
Discuss mechanisms for the dissemination of successful practices at HSIs, the context in which they work, and research results.
Include a discussion to ensure that the HSI-Hub's activities are inclusive of the broad collection of institutions within the HSI typology (which includes 2-year colleges, rural colleges, PUIs, comprehensive public institutions, universities in Puerto Rico, private institutions, and research-intensive universities).
Include a timeline of when activities would occur and who is responsible for key activities.
Describe a sustainability plan that demonstrates the continuation of the Hub’s goals and efforts to achieve desired outcomes beyond the funding period.
Include a project evaluation plan that is based on S.M.A.R.T. (Specific, Measurable, Attainable, Realistic, and Time-bound) goals. Evaluation plans should include a logic model as a supplementary document. In addition to quantitative and/or qualitative methodologies, it is encouraged that evaluation plans include measures of success for non-academic outcomes (i.e. STEM identity, academic self-concept, graduate aspirations.

It should also include a strategy to adapt successful existing frameworks for effectively diversifying the STEM enterprise and for student success at HSIs.

Proposers should be aware that Hub projects may be formally reviewed by NSF via a Site Visit or Reverse Site Visit during their second year to determine whether satisfactory progress has been made. Continued funding contingent on the result of the second-year review.

Additional Opportunities

Planning Proposals. The ETSE competition welcomes planning proposals for DDTT and ITT to develop, organize, and/or strengthen key data, human, and educational resources. Proposers should refer to Chapter II.F.1 of the NSF PAPPG for specific budget and proposal preparation guidelines relating to planning proposals and should note the target dates provided for this mechanism. As detailed in the PAPPG, PIs must contact a program director on the ETSE Competition to discuss their proposal idea and determine if a planning grant is appropriate. Furthermore, written permission to submit a planning proposal must be obtained from an HSI program director and uploaded at the time of submission.

Planning proposals can focus on the development of a future submission to the DDTT or ITT tracks. Examples of planning proposals include, but are not limited to the following:

Identifying or developing models, frameworks, research or evaluation designs central to the development of a strong future submission to the DDTT or ITT Tracks.
Developing or revising strategic plans for STEM education that leverage student-centered frameworks and practices.
Strengthening collaborations among faculty, administration, and staff in STEM departments, divisions, schools, colleges.
Strengthening collaborations among institutions of higher education, including two-year colleges and rural institutions.
Establishing partnerships with industry and/or community organizations.
Piloting systems and approaches to collect, organize, and analyze student data.

Workshops and Conferences. Proposals for workshops and conferences addressing topics that contribute to the goals of the HSI Program may be submitted at any time following consultation with an HSI Program Officer. Proposals for conferences addressing critical challenges in undergraduate STEM education and broadening STEM participation at HSIs may be submitted at any time following consultation with an HSI program officer.

III. Award Information

Estimated program budget, number of awards and average award size/duration are subject to the availability of funds.

IV. Eligibility Information

Proposals may only be submitted by the following: With the exception of conference proposals, proposals may only be submitted by the following: To be eligible for funding an institution must meet the following criteria: Be an accredited institution of higher education. Offer Undergraduate STEM educational programs that result in certificates or degrees. Satisfy the definition of an HSI as specified in section 502 of the Higher Education Act of 1965 (20 U.S.C. 1101a) and meet the eligibility of an HSI by the U.S. Department of Education definition. Documentation (eligibility letter) from the Department of Education confirming HSI designation must be submitted as a supplemental document. Additional requirements to be eligible for funding in the Emerging Faculty Research Track (EFRT), the institution must meet the four criteria listed above at the time of submission and: Be an eligible Primarily Undergraduate Institution (PUI)[ 1 ] . Eligible PUIs are accredited colleges and universities (including two-year community colleges) that award Associate's degrees, Bachelor's degrees, and/or Master's degrees in NSF-supported fields, but have awarded 20 or fewer Ph.D./D.Sc.. degrees in all NSF-supported fields during the combined previous two academic years.

Additional Eligibility Info:

With the exception of conference proposals, proposals may only be submitted by the following: To be eligible for funding an institution must meet the following criteria: Be an accredited institution of higher education. Offer Undergraduate STEM educational programs that result in certificates or degrees. Satisfy the definition of an HSI as specified in section 502 of the Higher Education Act of 1965 (20 U.S.C. 1101a) and meet the eligibility of an HSI by the U.S. Department of Education definition. Documentation (eligibility letter) from the Department of Education confirming HSI designation must be submitted as a supplemental document. Additional requirements to be eligible for funding in the Emerging Faculty Research Track (EFRT), the institution must meet the four criteria listed above at the time of submission and: Be an eligible Primarily Undergraduate Institution (PUI)[ 1 ] . Eligible PUIs are accredited colleges and universities (including two-year community colleges) that award Associate's degrees, Bachelor's degrees, and/or Master's degrees in NSF-supported fields, but have awarded 20 or fewer Ph.D./D.Sc.. degrees in all NSF-supported fields during the combined previous two academic years.

V. Proposal Preparation And Submission Instructions

Full Proposal Preparation Instructions : Proposers may opt to submit proposals in response to this Program Solicitation via Research.gov or Grants.gov.

Full Proposals submitted via Research.gov: Proposals submitted in response to this program solicitation should be prepared and submitted in accordance with the general guidelines contained in the NSF Proposal and Award Policies and Procedures Guide (PAPPG). The complete text of the PAPPG is available electronically on the NSF website at: https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg . Paper copies of the PAPPG may be obtained from the NSF Publications Clearinghouse, telephone (703) 292-8134 or by e-mail from [email protected] . The Prepare New Proposal setup will prompt you for the program solicitation number.
Full proposals submitted via Grants.gov: Proposals submitted in response to this program solicitation via Grants.gov should be prepared and submitted in accordance with the NSF Grants.gov Application Guide: A Guide for the Preparation and Submission of NSF Applications via Grants.gov . The complete text of the NSF Grants.gov Application Guide is available on the Grants.gov website and on the NSF website at: ( https://www.nsf.gov/publications/pub_summ.jsp?ods_key=grantsgovguide ). To obtain copies of the Application Guide and Application Forms Package, click on the Apply tab on the Grants.gov site, then click on the Apply Step 1: Download a Grant Application Package and Application Instructions link and enter the funding opportunity number, (the program solicitation number without the NSF prefix) and press the Download Package button. Paper copies of the Grants.gov Application Guide also may be obtained from the NSF Publications Clearinghouse, telephone (703) 292-8134 or by e-mail from [email protected] .

In determining which method to utilize in the electronic preparation and submission of the proposal, please note the following:

Collaborative Proposals. All collaborative proposals submitted as separate submissions from multiple organizations must be submitted via Research.gov. PAPPG Chapter II.E.3 provides additional information on collaborative proposals.

See PAPPG Chapter II.D.2 for guidance on the required sections of a full research proposal submitted to NSF. Please note that the proposal preparation instructions provided in this program solicitation may deviate from the PAPPG instructions.

Project Data Form : A Project Data Form must be submitted as part of all proposals. The information on this form is used to direct proposals to appropriate reviewers and to determine the characteristics of projects supported by the NSF Division of Undergraduate Education (DUE). In Research.gov, this form will appear as a required section of the proposal only after the ETSE solicitation number has been selected in Step 1 of the Proposal Creation Wizard. Grants.gov users should refer to Section VI.5.2. of the NSF Grants.gov Application Guide for specific instructions on how to submit the DUE Project Data Form.

Project Description: The project description should follow the requirements outlined in the NSF PAPPG and this solicitation. The narrative is limited to 15 single-spaced pages except for Planning proposals, which should adhere to the page limitation presented in the PAPPG. The Project Description must explain the project's motivating rationale, goals, objectives, deliverables, and describe how they address the goals of the HSI program. In addition to the required sections, all proposals to ETSE must include the track specific requirements noted in Section II and below. The following sections must be included in the 15-page project description with a bold heading.

Results from Prior NSF Support : If applicable the Project Description must include a section on results from prior NSF support. This must include support for projects pertaining to the proposed project that the PI or any of the co-PIs have been involved with (including sub-awards from NSF supported projects). This section should be aligned with the requirements given in the NSF PAPPG and contain specific outcomes and results to demonstrate the impact of the project. If the project team has had no prior support pertaining to the new proposal, this should be stated in the proposal. It is not required to have prior support to be successful in the HSI program.

Project Rationale, Significance and Objectives: The proposal should contain specific objectives that address the goals of the HSI program. The project rationale should build a compelling case for the proposed work, its approach, and how the work will advance knowledge regarding STEM education at HSIs. Proposals are expected to build on prior fundamental and/or applied research in STEM education or provide theoretical and empirical justification for the proposed project as needed. Justification may be accomplished through a combination of relevant literature, institutional data, and summaries of results from prior work.

Broader Impacts: Please note that per guidance in Chapter II of the NSF PAPPG, the Project Description must contain a separate section within the narrative labeled "Broader Impacts." This section should provide a discussion of the Broader Impacts of the proposed activities. Proposers may decide where to include this section within the Project Description.

Institutional Data Narrative: All DDTT and ITT proposals must include an Institutional Data Narrative to demonstrate the need for and potential benefits of the project. Proposers are encouraged to make appropriate use of disaggregated data in order to examine the intersectional identities of their students. These data may use any metrics that are appropriate for the project and may be tabular, graphical, or narrative in nature.

Commitment and Sustainability: All proposals must document an institutional commitment to faithfully carry out the project. This may include a discussion of how the institution will allocate existing and new resources to benefit the project. All proposals must demonstrate an institutional commitment to build upon or sustain any successful results of the project beyond the funding period.

Research Plan: All ETSE proposals must clearly describe efforts to generate knowledge through assessment, research, and/or evaluation. Projects must be situated in the existing practice, literature, and theory in the context of STEM education at an HSI and address questions of significance to those who work in and support HSIs. Assessing the impact of efforts as part of knowledge generation may be carried out by the PI and co-PIs or in partnership with an education researcher, evaluator, institutional research offices or other colleagues with measurement expertise.

Project Evaluation: All ETSE proposals must include a section that will describe how the project will assess progress, document outcomes, and evaluate success in achieving the project’s goals.

Guidelines for ETSE Proposals: All ETSE proposals must include a detailed evaluation plan, executed by an experienced and independent evaluator, that will provide both formative and summative feedback on the project’s progress towards its stated goals. Evaluation plans for IEP proposals should: (1) describe the aspects of the proposed project to be evaluated, (2) demonstrate the alignment between project activities and evaluation efforts, and (3) provide the design of the evaluation plan, including mechanisms for formative evaluation. Furthermore, evaluation plans for IEP proposals should include clear evaluation questions, quantitative and/or qualitative data streams beyond baseline institutional research data, specified methods for data analysis, and a mechanism for providing a written evaluation report to the project team at least annually.

The selected project evaluator should be independent from the project team but may be an individual from the same institution who has expertise in evaluation and assessment. Evaluators are expected to adhere to the American Evaluation Association's Guiding Principles for Evaluators ( https://www.eval.org/About/Guiding-Principles ), and project evaluations are expected to be consistent with standards established by the Joint Committee on Standards for Educational Evaluation ( http://www.jcsee.org/program-evaluation-standards-statements ).

If the submitting organization requires external evaluation consultants to be selected through a competitive bid process after an award is made, the proposer should mention the policy and describe the plans to select and collaborate with the evaluator once an award is made. Proposals without a named evaluator due to such a restriction should still include an evaluation plan reflecting the guidance provided above.

Project Management Plan : All proposals should include a project management plan indicating the roles and responsibilities of anyone serving as PI, co-PI, or senior personnel on the proposed project. Multi-institutional proposals including subawards should describe how project management responsibilities will be distributed across institutions as appropriate. The description provided should enable reviewers to assess the alignment of the team's experience and professional capabilities that are relevant to the proposed project. The project management plan may additionally describe other contributors as appropriate for the project, including STEM professionals, collaborators, researchers, advisory board members, evaluators, consultants, and contractors.

Dissemination Plan: All ETSE projects must include a plan to disseminate project outcomes to interested stakeholders and members of the HSI community. Innovative approaches that will strategically engage specific or broad audiences are encouraged.

Facilities, Equipment & Other Resources: See PAPPG Chapter II.D.2.g

Senior Personnel Documents: See PAPPG Chapter II.D.2.h.

Data Management and Sharing Plan: Proposers should provide a detailed data management and sharing plan. Transparency requires that the Federal agencies share how they are maximizing outcomes of Federal STEM investments and activities and ensuring broad benefit to the public. Proposers are highly encouraged to review Directorate-specific data management plan guidance, which can be accessed at https://www.nsf.gov/bfa/dias/policy/dmpdocs/ehr.pdf .

Mentoring Plan (if applicable): Required when funding is requested to support postdoctoral scholars or graduate students. See PAPPG Chapter II for instructions for the preparation of this item.

Special Information and Supplementary Documents : Please refer to the PAPPG Chapter II for additional guidance on Supplementary Documents. There is a distinction between supplementary documents and an appendix. Documents outside of what is described below may be interpreted as an appendix and can result in the proposal being returned without review.

Letters of Collaboration : Proposals are encouraged to include letters of collaboration from internal and external partners and project contributors outside of the project PIs and co-PIs. The format of these letters should closely align with the suggested language provided in the PAPPG.
Letters of Support from Key Administrators : All DDTT, ITT and Hub proposals must include letters of support from upper-level institutional administrators, at the level of Dean or higher, with responsibility for academic affairs and/or undergraduate STEM education in the proposal’s focal unit(s). These letters should outline concrete mechanisms for institutionalization and sustainability of the project activities and should be uploaded as supplemental documents. EFRT proposals should Include a letter of commitment from the PI's Department Chair or Dean stating that the PI will have institutional support in terms of allowance to utilize project-funded for release time, travel for research purposes, and access to existing research facilities. This should be included as a supplementary document.
Biographical Sketch of the External Evaluator: If an evaluator is named in the proposal, then a biographical sketch can be included as a supplementary document. This must follow the NSF format for biosketches and must not be a resume, CV, or quote for services.
Letter of Eligibility : The institution submitting a proposal to the ETSE program for tracks: DTT, ITT and EFRT must be a Hispanic-serving institution as defined by law in Section 502 of the Higher Education Act of 1965 (20 U.S.C. 1101a). A copy of the most recent Letter of Eligibility from the Department of Education must be included as a supplementary document. For collaborative proposals from multiple institutions, each submitting institution must be a Hispanic-serving institution and submit an Eligibility Letter. For collaborative proposals from a single institution, an Eligibility Letter is required only from the lead institution.
Undergraduate Student Mentoring Plan : All ETSE proposals that plan to financially support undergraduate students, for instance as tutors, peer mentors, research assistants, or other trainees must include a student mentoring plan of a maximum of 1 page as a supplementary document. This document should discuss specific strategies that will be utilized to provide academic, professional, and other valuable types of mentoring to these students. A student mentoring plan is not required if a project solely intends to provide incentives to students serving as research subjects without additional training requirements or duties. This solicitation specific required plan is separate and distinct from the mentoring plan required by the PAPPG for proposals that request funding to support postdoctoral scholars or graduate students.

Information regarding the preparation of a Conference Proposal can be found in Section II of this solicitation and in PAPPG Chapter II.F.9.

Information regarding the preparation of a Planning Proposal can be found in Section II of this solicitation and in PAPPG Chapter II.F.1

Cost Sharing:

Other Budgetary Limitations

Funds requested for EFRT proposals are intended to support investigators’ specific needs and may include, but are not limited to the following: faculty release time; technical support for research; faculty and student professional development; travel to conferences; acquisition or upgrading of research equipment; development of special topics or seminar courses; and collaborative research efforts including travel to collaborating institutions or travel for collaborators to visit the PI at their home institution. The budget may include support for student trainees or post-doctoral fellows.

EFRT proposals can be used to support sabbatical activities, including providing salary supplements in cases where the proposing institution does not provide full salary support.

Collaborative Funding for non-HSIs:

Except for the ITT, the ETSE solicitation welcomes collaborative proposals. Collaborative Proposals from Multiple Institutions (PAPPG Chapter II.E.3.b) are encouraged as long as each lead and non-lead Institution is an HSI. If the collaboration involves institution(s) that are not HSIs, these institution(s) must be included as a non-lead subaward (PAPPG Chapter II.E.3.a) from the lead HSI. Collaborative proposals involving non-HSIs may not be submitted as Collaborative Proposals from Multiple Institutions (PAPPG Chapter II.E.3.b)

ETSE project funds may not be used for:

Student scholarships (please see the S-STEM, SFS, or Robert Noyce Teacher Scholarship programs for scholarships for students).
Equipment or instrumentation that does not significantly improve instructional capability, please see the Educational Instrumentation Track in the ELSPE solicitation.
Teaching aids (e.g., films, slides, projectors, "drill and practice" software).
Vehicles, trailers, laboratory furnishings, or general utility items such as office equipment, benches, tables, desks, chairs, storage cases, and routine supplies.
Maintenance equipment and maintenance or service contracts.
Modification, construction, or furnishing of laboratories or other buildings.
Installation of equipment or instrumentation (as distinct from the on-site assembly of multi-component instruments--which is an allowable charge).

In accordance with 2 CFR § 200.413, the salaries of administrative and clerical staff should normally be treated as indirect costs (F&A). Direct charging of these costs may be appropriate only if all the conditions specified in 2 CFR § 200.413 are met.

Budget Preparation Instructions:

In FY 2024, the HSI program expects to fund new awards totaling $20,000,000, subject to the availability of funds.

Budgets and budget justifications submitted to this solicitation should reflect an equitable distribution of funds based on the proposed scope of the project. All budget requests must be consistent with the proposed scope and duration of the project in its track and cannot exceed the maximum permitted in its track. Proposers to the ETSE solicitation should provide a budget for each year of support requested.

D. Research.gov/Grants.gov Requirements

For Proposals Submitted Via Research.gov:

To prepare and submit a proposal via Research.gov, see detailed technical instructions available at: https://www.research.gov/research-portal/appmanager/base/desktop?_nfpb=true&_pageLabel=research_node_display&_nodePath=/researchGov/Service/Desktop/ProposalPreparationandSubmission.html . For Research.gov user support, call the Research.gov Help Desk at 1-800-381-1532 or e-mail [email protected] . The Research.gov Help Desk answers general technical questions related to the use of the Research.gov system. Specific questions related to this program solicitation should be referred to the NSF program staff contact(s) listed in Section VIII of this funding opportunity.

For Proposals Submitted Via Grants.gov:

Before using Grants.gov for the first time, each organization must register to create an institutional profile. Once registered, the applicant's organization can then apply for any federal grant on the Grants.gov website. Comprehensive information about using Grants.gov is available on the Grants.gov Applicant Resources webpage: https://www.grants.gov/applicants . In addition, the NSF Grants.gov Application Guide (see link in Section V.A) provides instructions regarding the technical preparation of proposals via Grants.gov. For Grants.gov user support, contact the Grants.gov Contact Center at 1-800-518-4726 or by email: [email protected] . The Grants.gov Contact Center answers general technical questions related to the use of Grants.gov. Specific questions related to this program solicitation should be referred to the NSF program staff contact(s) listed in Section VIII of this solicitation.

Submitting the Proposal: Once all documents have been completed, the Authorized Organizational Representative (AOR) must submit the application to Grants.gov and verify the desired funding opportunity and agency to which the application is submitted. The AOR must then sign and submit the application to Grants.gov. The completed application will be transferred to Research.gov for further processing.

The NSF Grants.gov Proposal Processing in Research.gov informational page provides submission guidance to applicants and links to helpful resources including the NSF Grants.gov Application Guide , Grants.gov Proposal Processing in Research.gov how-to guide , and Grants.gov Submitted Proposals Frequently Asked Questions . Grants.gov proposals must pass all NSF pre-check and post-check validations in order to be accepted by Research.gov at NSF.

When submitting via Grants.gov, NSF strongly recommends applicants initiate proposal submission at least five business days in advance of a deadline to allow adequate time to address NSF compliance errors and resubmissions by 5:00 p.m. submitting organization's local time on the deadline. Please note that some errors cannot be corrected in Grants.gov. Once a proposal passes pre-checks but fails any post-check, an applicant can only correct and submit the in-progress proposal in Research.gov.

Proposers that submitted via Research.gov may use Research.gov to verify the status of their submission to NSF. For proposers that submitted via Grants.gov, until an application has been received and validated by NSF, the Authorized Organizational Representative may check the status of an application on Grants.gov. After proposers have received an e-mail notification from NSF, Research.gov should be used to check the status of an application.

VI. NSF Proposal Processing And Review Procedures

Proposals received by NSF are assigned to the appropriate NSF program for acknowledgement and, if they meet NSF requirements, for review. All proposals are carefully reviewed by a scientist, engineer, or educator serving as an NSF Program Officer, and usually by three to ten other persons outside NSF either as ad hoc reviewers, panelists, or both, who are experts in the particular fields represented by the proposal. These reviewers are selected by Program Officers charged with oversight of the review process. Proposers are invited to suggest names of persons they believe are especially well qualified to review the proposal and/or persons they would prefer not review the proposal. These suggestions may serve as one source in the reviewer selection process at the Program Officer's discretion. Submission of such names, however, is optional. Care is taken to ensure that reviewers have no conflicts of interest with the proposal. In addition, Program Officers may obtain comments from site visits before recommending final action on proposals. Senior NSF staff further review recommendations for awards. A flowchart that depicts the entire NSF proposal and award process (and associated timeline) is included in PAPPG Exhibit III-1.

A comprehensive description of the Foundation's merit review process is available on the NSF website at: https://www.nsf.gov/bfa/dias/policy/merit_review/ .

Proposers should also be aware of core strategies that are essential to the fulfillment of NSF's mission, as articulated in Leading the World in Discovery and Innovation, STEM Talent Development and the Delivery of Benefits from Research - NSF Strategic Plan for Fiscal Years (FY) 2022 - 2026 . These strategies are integrated in the program planning and implementation process, of which proposal review is one part. NSF's mission is particularly well-implemented through the integration of research and education and broadening participation in NSF programs, projects, and activities.

One of the strategic objectives in support of NSF's mission is to foster integration of research and education through the programs, projects, and activities it supports at academic and research institutions. These institutions must recruit, train, and prepare a diverse STEM workforce to advance the frontiers of science and participate in the U.S. technology-based economy. NSF's contribution to the national innovation ecosystem is to provide cutting-edge research under the guidance of the Nation's most creative scientists and engineers. NSF also supports development of a strong science, technology, engineering, and mathematics (STEM) workforce by investing in building the knowledge that informs improvements in STEM teaching and learning.

NSF's mission calls for the broadening of opportunities and expanding participation of groups, institutions, and geographic regions that are underrepresented in STEM disciplines, which is essential to the health and vitality of science and engineering. NSF is committed to this principle of diversity and deems it central to the programs, projects, and activities it considers and supports.

A. Merit Review Principles and Criteria

The National Science Foundation strives to invest in a robust and diverse portfolio of projects that creates new knowledge and enables breakthroughs in understanding across all areas of science and engineering research and education. To identify which projects to support, NSF relies on a merit review process that incorporates consideration of both the technical aspects of a proposed project and its potential to contribute more broadly to advancing NSF's mission "to promote the progress of science; to advance the national health, prosperity, and welfare; to secure the national defense; and for other purposes." NSF makes every effort to conduct a fair, competitive, transparent merit review process for the selection of projects.

1. Merit Review Principles

These principles are to be given due diligence by PIs and organizations when preparing proposals and managing projects, by reviewers when reading and evaluating proposals, and by NSF program staff when determining whether or not to recommend proposals for funding and while overseeing awards. Given that NSF is the primary federal agency charged with nurturing and supporting excellence in basic research and education, the following three principles apply:

All NSF projects should be of the highest quality and have the potential to advance, if not transform, the frontiers of knowledge.
NSF projects, in the aggregate, should contribute more broadly to achieving societal goals. These "Broader Impacts" may be accomplished through the research itself, through activities that are directly related to specific research projects, or through activities that are supported by, but are complementary to, the project. The project activities may be based on previously established and/or innovative methods and approaches, but in either case must be well justified.
Meaningful assessment and evaluation of NSF funded projects should be based on appropriate metrics, keeping in mind the likely correlation between the effect of broader impacts and the resources provided to implement projects. If the size of the activity is limited, evaluation of that activity in isolation is not likely to be meaningful. Thus, assessing the effectiveness of these activities may best be done at a higher, more aggregated, level than the individual project.

With respect to the third principle, even if assessment of Broader Impacts outcomes for particular projects is done at an aggregated level, PIs are expected to be accountable for carrying out the activities described in the funded project. Thus, individual projects should include clearly stated goals, specific descriptions of the activities that the PI intends to do, and a plan in place to document the outputs of those activities.

These three merit review principles provide the basis for the merit review criteria, as well as a context within which the users of the criteria can better understand their intent.

2. Merit Review Criteria

All NSF proposals are evaluated through use of the two National Science Board approved merit review criteria. In some instances, however, NSF will employ additional criteria as required to highlight the specific objectives of certain programs and activities.

The two merit review criteria are listed below. Both criteria are to be given full consideration during the review and decision-making processes; each criterion is necessary but neither, by itself, is sufficient. Therefore, proposers must fully address both criteria. (PAPPG Chapter II.D.2.d(i). contains additional information for use by proposers in development of the Project Description section of the proposal). Reviewers are strongly encouraged to review the criteria, including PAPPG Chapter II.D.2.d(i), prior to the review of a proposal.

When evaluating NSF proposals, reviewers will be asked to consider what the proposers want to do, why they want to do it, how they plan to do it, how they will know if they succeed, and what benefits could accrue if the project is successful. These issues apply both to the technical aspects of the proposal and the way in which the project may make broader contributions. To that end, reviewers will be asked to evaluate all proposals against two criteria:

Intellectual Merit: The Intellectual Merit criterion encompasses the potential to advance knowledge; and
Broader Impacts: The Broader Impacts criterion encompasses the potential to benefit society and contribute to the achievement of specific, desired societal outcomes.

The following elements should be considered in the review for both criteria:

Advance knowledge and understanding within its own field or across different fields (Intellectual Merit); and
Benefit society or advance desired societal outcomes (Broader Impacts)?
To what extent do the proposed activities suggest and explore creative, original, or potentially transformative concepts?
Is the plan for carrying out the proposed activities well-reasoned, well-organized, and based on a sound rationale? Does the plan incorporate a mechanism to assess success?
How well qualified is the individual, team, or organization to conduct the proposed activities?
Are there adequate resources available to the PI (either at the home organization or through collaborations) to carry out the proposed activities?

Broader impacts may be accomplished through the research itself, through the activities that are directly related to specific research projects, or through activities that are supported by, but are complementary to, the project. NSF values the advancement of scientific knowledge and activities that contribute to achievement of societally relevant outcomes. Such outcomes include, but are not limited to: full participation of women, persons with disabilities, and other underrepresented groups in science, technology, engineering, and mathematics (STEM); improved STEM education and educator development at any level; increased public scientific literacy and public engagement with science and technology; improved well-being of individuals in society; development of a diverse, globally competitive STEM workforce; increased partnerships between academia, industry, and others; improved national security; increased economic competitiveness of the United States; and enhanced infrastructure for research and education.

Proposers are reminded that reviewers will also be asked to review the Data Management and Sharing Plan and the Mentoring Plan, as appropriate.

Additional Solicitation Specific Review Criteria

In addition to the two NSF criteria for Intellectual Merit and Broader Impacts, the additional HSI proposal review criteria for DDTT, ITT and Hub proposals are as follows:

How effectively does the design of project activities (e.g., student supports, evaluation, research, etc.) take into account students’ membership in populations described by demographic characteristics or lived experiences (e.g., low-income, commuter, parenting, first-generation, or veteran status) to reflect the HSI context and the community it serves?

The following criterion is also in effect for ITT and DDTT proposals.

How effectively do the proposed goals, objectives, and activities demonstrate potential to drive institutional or departmental transformation that will result in a more student-centered STEM environment and increase the likelihood of success for students across a diversity of populations?

B. Review and Selection Process

Proposals submitted in response to this program solicitation will be reviewed by Ad hoc Review and/or Panel Review.

Reviewers will be asked to evaluate proposals using two National Science Board approved merit review criteria and, if applicable, additional program specific criteria. A summary rating and accompanying narrative will generally be completed and submitted by each reviewer and/or panel. The Program Officer assigned to manage the proposal's review will consider the advice of reviewers and will formulate a recommendation.

After scientific, technical and programmatic review and consideration of appropriate factors, the NSF Program Officer recommends to the cognizant Division Director whether the proposal should be declined or recommended for award. NSF strives to be able to tell proposers whether their proposals have been declined or recommended for funding within six months. Large or particularly complex proposals or proposals from new recipients may require additional review and processing time. The time interval begins on the deadline or target date, or receipt date, whichever is later. The interval ends when the Division Director acts upon the Program Officer's recommendation.

After programmatic approval has been obtained, the proposals recommended for funding will be forwarded to the Division of Grants and Agreements or the Division of Acquisition and Cooperative Support for review of business, financial, and policy implications. After an administrative review has occurred, Grants and Agreements Officers perform the processing and issuance of a grant or other agreement. Proposers are cautioned that only a Grants and Agreements Officer may make commitments, obligations or awards on behalf of NSF or authorize the expenditure of funds. No commitment on the part of NSF should be inferred from technical or budgetary discussions with a NSF Program Officer. A Principal Investigator or organization that makes financial or personnel commitments in the absence of a grant or cooperative agreement signed by the NSF Grants and Agreements Officer does so at their own risk.

Once an award or declination decision has been made, Principal Investigators are provided feedback about their proposals. In all cases, reviews are treated as confidential documents. Verbatim copies of reviews, excluding the names of the reviewers or any reviewer-identifying information, are sent to the Principal Investigator/Project Director by the Program Officer. In addition, the proposer will receive an explanation of the decision to award or decline funding.

VII. Award Administration Information

A. notification of the award.

Notification of the award is made to the submitting organization by an NSF Grants and Agreements Officer. Organizations whose proposals are declined will be advised as promptly as possible by the cognizant NSF Program administering the program. Verbatim copies of reviews, not including the identity of the reviewer, will be provided automatically to the Principal Investigator. (See Section VI.B. for additional information on the review process.)

B. Award Conditions

An NSF award consists of: (1) the award notice, which includes any special provisions applicable to the award and any numbered amendments thereto; (2) the budget, which indicates the amounts, by categories of expense, on which NSF has based its support (or otherwise communicates any specific approvals or disapprovals of proposed expenditures); (3) the proposal referenced in the award notice; (4) the applicable award conditions, such as Grant General Conditions (GC-1)*; or Research Terms and Conditions* and (5) any announcement or other NSF issuance that may be incorporated by reference in the award notice. Cooperative agreements also are administered in accordance with NSF Cooperative Agreement Financial and Administrative Terms and Conditions (CA-FATC) and the applicable Programmatic Terms and Conditions. NSF awards are electronically signed by an NSF Grants and Agreements Officer and transmitted electronically to the organization via e-mail.

*These documents may be accessed electronically on NSF's Website at https://www.nsf.gov/awards/managing/award_conditions.jsp?org=NSF . Paper copies may be obtained from the NSF Publications Clearinghouse, telephone (703) 292-8134 or by e-mail from [email protected] .

More comprehensive information on NSF Award Conditions and other important information on the administration of NSF awards is contained in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) Chapter VII, available electronically on the NSF Website at https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg .

Administrative and National Policy Requirements

Build America, Buy America

As expressed in Executive Order 14005, Ensuring the Future is Made in All of America by All of America’s Workers (86 FR 7475), it is the policy of the executive branch to use terms and conditions of Federal financial assistance awards to maximize, consistent with law, the use of goods, products, and materials produced in, and services offered in, the United States.

Consistent with the requirements of the Build America, Buy America Act (Pub. L. 117-58, Division G, Title IX, Subtitle A, November 15, 2021), no funding made available through this funding opportunity may be obligated for an award unless all iron, steel, manufactured products, and construction materials used in the project are produced in the United States. For additional information, visit NSF’s Build America, Buy America webpage.

Special Award Conditions:

HSI Program Evaluation: Projects are required to cooperate and participate in additional program efforts to gather data and information to support HSI program monitoring and evaluation. Projects are furthermore required to participate, if asked, in any efforts to synthesize and disseminate program outcomes via current or future HSI-Net Centers.

Open Access to Project Products: Developers of new materials are required to license all work (except for computer software source code, discussed below) created with the support of the grant under either the 3.0 Unported or 3.0 United States version of the Creative Commons Attribution (CC BY), Attribution-ShareAlike (CC BY-SA), or Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license. These licenses allow subsequent users to copy, distribute, transmit, and adapt the copyrighted work and requires such users to attribute the work in the manner specified by the grantee. Notice of the specific license used would be affixed to the work and displayed clearly when the work is made available online. For general information on these Creative Commons licenses, please visit http://creativecommons.org/licenses/ .

It is expected that computer software source code developed or created with NSF funds be released under an intellectual property license that allows others to use and build upon the work. The grantee may release all new source code developed or created with IUSE grant funds under an open license acceptable to the Free Software Foundation ( http://gnu.org/licenses/ ) and/or the Open-Source Initiative ( http://opensource.org/licenses/ ).

C. Reporting Requirements

For all multi-year grants (including both standard and continuing grants), the Principal Investigator must submit an annual project report to the cognizant Program Officer no later than 90 days prior to the end of the current budget period. (Some programs or awards require submission of more frequent project reports). No later than 120 days following expiration of a grant, the PI also is required to submit a final annual project report, and a project outcomes report for the general public.

Failure to provide the required annual or final annual project reports, or the project outcomes report, will delay NSF review and processing of any future funding increments as well as any pending proposals for all identified PIs and co-PIs on a given award. PIs should examine the formats of the required reports in advance to assure availability of required data.

PIs are required to use NSF's electronic project-reporting system, available through Research.gov, for preparation and submission of annual and final annual project reports. Such reports provide information on accomplishments, project participants (individual and organizational), publications, and other specific products and impacts of the project. Submission of the report via Research.gov constitutes certification by the PI that the contents of the report are accurate and complete. The project outcomes report also must be prepared and submitted using Research.gov. This report serves as a brief summary, prepared specifically for the public, of the nature and outcomes of the project. This report will be posted on the NSF website exactly as it is submitted by the PI.

More comprehensive information on NSF Reporting Requirements and other important information on the administration of NSF awards is contained in the NSF Proposal & Award Policies & Procedures Guide (PAPPG) Chapter VII, available electronically on the NSF Website at https://www.nsf.gov/publications/pub_summ.jsp?ods_key=pappg .

VIII. Agency Contacts

Please note that the program contact information is current at the time of publishing. See program website for any updates to the points of contact.

General inquiries regarding this program should be made to:

For questions related to the use of NSF systems contact:

NSF Help Desk: 1-800-381-1532
Research.gov Help Desk e-mail: [email protected]

For questions relating to Grants.gov contact:

Grants.gov Contact Center: If the Authorized Organizational Representatives (AOR) has not received a confirmation message from Grants.gov within 48 hours of submission of application, please contact via telephone: 1-800-518-4726; e-mail: [email protected] .

IX. Other Information

The NSF website provides the most comprehensive source of information on NSF Directorates (including contact information), programs and funding opportunities. Use of this website by potential proposers is strongly encouraged. In addition, "NSF Update" is an information-delivery system designed to keep potential proposers and other interested parties apprised of new NSF funding opportunities and publications, important changes in proposal and award policies and procedures, and upcoming NSF Grants Conferences . Subscribers are informed through e-mail or the user's Web browser each time new publications are issued that match their identified interests. "NSF Update" also is available on NSF's website .

Grants.gov provides an additional electronic capability to search for Federal government-wide grant opportunities. NSF funding opportunities may be accessed via this mechanism. Further information on Grants.gov may be obtained at https://www.grants.gov .

About The National Science Foundation

The National Science Foundation (NSF) is an independent Federal agency created by the National Science Foundation Act of 1950, as amended (42 USC 1861-75). The Act states the purpose of the NSF is "to promote the progress of science; [and] to advance the national health, prosperity, and welfare by supporting research and education in all fields of science and engineering."

NSF funds research and education in most fields of science and engineering. It does this through grants and cooperative agreements to more than 2,000 colleges, universities, K-12 school systems, businesses, informal science organizations and other research organizations throughout the US. The Foundation accounts for about one-fourth of Federal support to academic institutions for basic research.

NSF receives approximately 55,000 proposals each year for research, education and training projects, of which approximately 11,000 are funded. In addition, the Foundation receives several thousand applications for graduate and postdoctoral fellowships. The agency operates no laboratories itself but does support National Research Centers, user facilities, certain oceanographic vessels and Arctic and Antarctic research stations. The Foundation also supports cooperative research between universities and industry, US participation in international scientific and engineering efforts, and educational activities at every academic level.

Facilitation Awards for Scientists and Engineers with Disabilities (FASED) provide funding for special assistance or equipment to enable persons with disabilities to work on NSF-supported projects. See the NSF Proposal & Award Policies & Procedures Guide Chapter II.F.7 for instructions regarding preparation of these types of proposals.

The National Science Foundation has Telephonic Device for the Deaf (TDD) and Federal Information Relay Service (FIRS) capabilities that enable individuals with hearing impairments to communicate with the Foundation about NSF programs, employment or general information. TDD may be accessed at (703) 292-5090 and (800) 281-8749, FIRS at (800) 877-8339.

The National Science Foundation Information Center may be reached at (703) 292-5111.

Privacy Act And Public Burden Statements

The information requested on proposal forms and project reports is solicited under the authority of the National Science Foundation Act of 1950, as amended. The information on proposal forms will be used in connection with the selection of qualified proposals; and project reports submitted by proposers will be used for program evaluation and reporting within the Executive Branch and to Congress. The information requested may be disclosed to qualified reviewers and staff assistants as part of the proposal review process; to proposer institutions/grantees to provide or obtain data regarding the proposal review process, award decisions, or the administration of awards; to government contractors, experts, volunteers and researchers and educators as necessary to complete assigned work; to other government agencies or other entities needing information regarding proposers or nominees as part of a joint application review process, or in order to coordinate programs or policy; and to another Federal agency, court, or party in a court or Federal administrative proceeding if the government is a party. Information about Principal Investigators may be added to the Reviewer file and used to select potential candidates to serve as peer reviewers or advisory committee members. See System of Record Notices , NSF-50 , "Principal Investigator/Proposal File and Associated Records," and NSF-51 , "Reviewer/Proposal File and Associated Records.” Submission of the information is voluntary. Failure to provide full and complete information, however, may reduce the possibility of receiving an award.

An agency may not conduct or sponsor, and a person is not required to respond to, an information collection unless it displays a valid Office of Management and Budget (OMB) control number. The OMB control number for this collection is 3145-0058. Public reporting burden for this collection of information is estimated to average 120 hours per response, including the time for reviewing instructions. Send comments regarding the burden estimate and any other aspect of this collection of information, including suggestions for reducing this burden, to:

Suzanne H. Plimpton Reports Clearance Officer Policy Office, Division of Institution and Award Support Office of Budget, Finance, and Award Management National Science Foundation Alexandria, VA 22314

X. Appendix

References:

1 Definition of PUI: https://carnegieclassifications.acenet.edu/carnegie-classification/classification-methodology/basic-classification/

2 Núñez, A.M., 2014. Advancing an intersectionality framework in higher education: Power and Latino postsecondary opportunity. In Higher education: Handbook of theory and research (pp. 33-92). Springer, Dordrecht.

3 McNair et al. (2022) Becoming a Student-Ready College: A New Culture of Leadership for Student Success. Hoboken, NJ: Josey-Bass.

4 Garcia, Gina A. “Defining “Servingness” at HSIs in Practice at Hispanic-Serving Institutions (HSIs).” Hispanic Serving Institutions (HSIs) in Practice. Charlotte: Information Age Publishing, 2020, xi-xxvi.

5 Dweck, C. S., & Yeager, D. S. (2019). Mindsets: A View From Two Eras. Perspectives on Psychological Science, 14(3), 481-496. https://doi.org/10.1177/1745691618804166

6 Developing a Theory of Change: Practical Theory if Change Guidance, Templates and Examples. https://www.aecf.org/resources/theory-of-change?gad_source=1&gclid=CjwKCAiAjrarBhAWEiwA2qWdCAc_GqSz611wuDm742yvbRLUAJoTe4BdLo4wHiOFAiBOyA8YKYHepxoCESMQAvD_BwE

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Resources for participants at IRSC's 2013 STEM camp. Ideas for a research paper using a science, technology, engineering, or math topic.
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199+ Best Quantitative Research Topics for STEM Students 2024

The Importance of Quantitative Research in STEM

In different STEM areas

How do you choose a research topic in STEM?

Follow Your STEM Heartbeat

Venture into the Unknown

Map Out the Data Terrain

Keep It Practical

Hunt for Research Gaps

Get Inspired

Seek Wisdom from the Wise

Real-World Impact Check

Match Your Skills with Your Quest

Quantitative Research Topics for STEM Students

Engineering

Mathematics

Environment

Environmental Engineering

Data Science

Political Science

Anthropology

What are the best topics for quantitative research for STEM?

Natural Sciences

Technology and Engineering

Consider these tips when choosing

What is the best topic for quantitative research?

Here’s a simple plan

And some examples

How can you apply quantitative research in STEM?

Understanding Nature

Testing Theories

Making Predictions

Enhancing Analysis

Frequently Asked Questions (FAQs)

How can I overcome common pitfalls in quantitative research?

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What Is STEM?

Why STEM Research Is Important?

How to Choose a Topic for STEM Research Paper

Step 1: Identify Your Interests

Step 2: Research Existing Topics

Step 3: Consider Real-World Problems

Step 4: Talk to Teachers and Mentors

Step 5: Narrow Down Your Topic

Qualitative Research Topics for STEM Students:

Easy Experimental Research Topics for STEM Students:

Research Topics for STEM Students in the Philippines:

Read More

Good Research Topics for STEM Students:

Unique Research Topics for STEM Students:

Experimental Research Topics for STEM Students in the Philippines

Capstone Research Topics for STEM Students in the Philippines:

Experimental Quantitative Research Topics for STEM Students:

Descriptive Research Topics for STEM Students

Research Topics for STEM Students in the Pandemic:

Research Topics for STEM Students Middle School

Technology Research Topics for STEM Students

Scientific Research Topics for STEM Students

Interesting Research Topics for STEM Students:

Practical Research Topics for STEM Students

Experimental Research Topics for STEM Students About Plants

Qualitative Research Topics for STEM Students in the Philippines

Science Research Topics for STEM Students

Correlational Research Topics for STEM Students

Quantitative Research Topics for STEM Students in the Philippines

Things That Must Keep In Mind While Writing Quantitative Research Title

1. Be Clear and Precise

2. Use Important Words

3. Avoid Confusing Words

4. Show Your Research Approach

5. Match Your Title with Your Research Questions

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