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• Methodology

Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

A research design is a strategy for answering your research question  using empirical data. Creating a research design means making decisions about:

• Your overall aims and approach
• The type of research design you’ll use
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research aims and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, frequently asked questions.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities – start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends, and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analysing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study – plants, animals, organisations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region, or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalise your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study, your aim is to deeply understand a specific context, not to generalise to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question.

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviours, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews.

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected – for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are reliable and valid.

Operationalisation

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalisation means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in – for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced , while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method, you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample – by mail, online, by phone, or in person?

If you’re using a probability sampling method, it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method, how will you avoid bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organising and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymise and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

On their own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyse the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarise your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarise your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analysing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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• How it works

How to Write a Research Design – Guide with Examples

Published by Alaxendra Bets at August 14th, 2021 , Revised On October 3, 2023

A research design is a structure that combines different components of research. It involves the use of different data collection and data analysis techniques logically to answer the  research questions .

It would be best to make some decisions about addressing the research questions adequately before starting the research process, which is achieved with the help of the research design.

Below are the key aspects of the decision-making process:

• Data type required for research
• Research resources
• Participants required for research
• Hypothesis based upon research question(s)
• Data analysis  methodologies
• Variables (Independent, dependent, and confounding)
• The location and timescale for conducting the data
• The time period required for research

The research design provides the strategy of investigation for your project. Furthermore, it defines the parameters and criteria to compile the data to evaluate results and conclude.

Your project’s validity depends on the data collection and  interpretation techniques.  A strong research design reflects a strong  dissertation , scientific paper, or research proposal .

Step 1: Establish Priorities for Research Design

Before conducting any research study, you must address an important question: “how to create a research design.”

The research design depends on the researcher’s priorities and choices because every research has different priorities. For a complex research study involving multiple methods, you may choose to have more than one research design.

Multimethodology or multimethod research includes using more than one data collection method or research in a research study or set of related studies.

If one research design is weak in one area, then another research design can cover that weakness. For instance, a  dissertation analyzing different situations or cases will have more than one research design.

For example:

• Experimental research involves experimental investigation and laboratory experience, but it does not accurately investigate the real world.
• Quantitative research is good for the  statistical part of the project, but it may not provide an in-depth understanding of the  topic .
• Also, correlational research will not provide experimental results because it is a technique that assesses the statistical relationship between two variables.

While scientific considerations are a fundamental aspect of the research design, It is equally important that the researcher think practically before deciding on its structure. Here are some questions that you should think of;

• Do you have enough time to gather data and complete the write-up?
• Will you be able to collect the necessary data by interviewing a specific person or visiting a specific location?
• Do you have in-depth knowledge about the  different statistical analysis and data collection techniques to address the research questions  or test the  hypothesis ?

If you think that the chosen research design cannot answer the research questions properly, you can refine your research questions to gain better insight.

Step 2: Data Type you Need for Research

Decide on the type of data you need for your research. The type of data you need to collect depends on your research questions or research hypothesis. Two types of research data can be used to answer the research questions:

Primary Data Vs. Secondary Data

Qualitative vs. quantitative data.

Also, see; Research methods, design, and analysis .

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• Hire an expert from ResearchProspect today!
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Step 3: Data Collection Techniques

Once you have selected the type of research to answer your research question, you need to decide where and how to collect the data.

It is time to determine your research method to address the  research problem . Research methods involve procedures, techniques, materials, and tools used for the study.

For instance, a dissertation research design includes the different resources and data collection techniques and helps establish your  dissertation’s structure .

The following table shows the characteristics of the most popularly employed research methods.

Research Methods

Step 4: Procedure of Data Analysis

Use of the  correct data and statistical analysis technique is necessary for the validity of your research. Therefore, you need to be certain about the data type that would best address the research problem. Choosing an appropriate analysis method is the final step for the research design. It can be split into two main categories;

Quantitative Data Analysis

The quantitative data analysis technique involves analyzing the numerical data with the help of different applications such as; SPSS, STATA, Excel, origin lab, etc.

This data analysis strategy tests different variables such as spectrum, frequencies, averages, and more. The research question and the hypothesis must be established to identify the variables for testing.

Qualitative Data Analysis

Qualitative data analysis of figures, themes, and words allows for flexibility and the researcher’s subjective opinions. This means that the researcher’s primary focus will be interpreting patterns, tendencies, and accounts and understanding the implications and social framework.

You should be clear about your research objectives before starting to analyze the data. For example, you should ask yourself whether you need to explain respondents’ experiences and insights or do you also need to evaluate their responses with reference to a certain social framework.

Step 5: Write your Research Proposal

The research design is an important component of a research proposal because it plans the project’s execution. You can share it with the supervisor, who would evaluate the feasibility and capacity of the results  and  conclusion .

Read our guidelines to write a research proposal  if you have already formulated your research design. The research proposal is written in the future tense because you are writing your proposal before conducting research.

The  research methodology  or research design, on the other hand, is generally written in the past tense.

How to Write a Research Design – Conclusion

A research design is the plan, structure, strategy of investigation conceived to answer the research question and test the hypothesis. The dissertation research design can be classified based on the type of data and the type of analysis.

Above mentioned five steps are the answer to how to write a research design. So, follow these steps to  formulate the perfect research design for your dissertation .

ResearchProspect writers have years of experience creating research designs that align with the dissertation’s aim and objectives. If you are struggling with your dissertation methodology chapter, you might want to look at our dissertation part-writing service.

Our dissertation writers can also help you with the full dissertation paper . No matter how urgent or complex your need may be, ResearchProspect can help. We also offer PhD level research paper writing services.

Frequently Asked Questions

What is research design.

Research design is a systematic plan that guides the research process, outlining the methodology and procedures for collecting and analysing data. It determines the structure of the study, ensuring the research question is answered effectively, reliably, and validly. It serves as the blueprint for the entire research project.

How to write a research design?

To write a research design, define your research question, identify the research method (qualitative, quantitative, or mixed), choose data collection techniques (e.g., surveys, interviews), determine the sample size and sampling method, outline data analysis procedures, and highlight potential limitations and ethical considerations for the study.

How to write the design section of a research paper?

In the design section of a research paper, describe the research methodology chosen and justify its selection. Outline the data collection methods, participants or samples, instruments used, and procedures followed. Detail any experimental controls, if applicable. Ensure clarity and precision to enable replication of the study by other researchers.

How to write a research design in methodology?

To write a research design in methodology, clearly outline the research strategy (e.g., experimental, survey, case study). Describe the sampling technique, participants, and data collection methods. Detail the procedures for data collection and analysis. Justify choices by linking them to research objectives, addressing reliability and validity.

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Repository of ten perfect research question examples will provide you a better perspective about how to create research questions.

Find how to write research questions with the mentioned steps required for a perfect research question. Choose an interesting topic and begin your research.

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How To Write A Research Paper

Step-By-Step Tutorial With Examples + FREE Template

By: Derek Jansen (MBA) | Expert Reviewer: Dr Eunice Rautenbach | March 2024

For many students, crafting a strong research paper from scratch can feel like a daunting task – and rightly so! In this post, we’ll unpack what a research paper is, what it needs to do , and how to write one – in three easy steps. 🙂 

Overview: Writing A Research Paper

What (exactly) is a research paper.

• How to write a research paper
• Stage 1 : Topic & literature search
• Stage 2 : Structure & outline
• Stage 3 : Iterative writing
• Key takeaways

Let’s start by asking the most important question, “ What is a research paper? ”.

Simply put, a research paper is a scholarly written work where the writer (that’s you!) answers a specific question (this is called a research question ) through evidence-based arguments . Evidence-based is the keyword here. In other words, a research paper is different from an essay or other writing assignments that draw from the writer’s personal opinions or experiences. With a research paper, it’s all about building your arguments based on evidence (we’ll talk more about that evidence a little later).

Now, it’s worth noting that there are many different types of research papers , including analytical papers (the type I just described), argumentative papers, and interpretative papers. Here, we’ll focus on analytical papers , as these are some of the most common – but if you’re keen to learn about other types of research papers, be sure to check out the rest of the blog .

With that basic foundation laid, let’s get down to business and look at how to write a research paper .

Overview: The 3-Stage Process

While there are, of course, many potential approaches you can take to write a research paper, there are typically three stages to the writing process. So, in this tutorial, we’ll present a straightforward three-step process that we use when working with students at Grad Coach.

These three steps are:

• Finding a research topic and reviewing the existing literature
• Developing a provisional structure and outline for your paper, and
• Writing up your initial draft and then refining it iteratively

Let’s dig into each of these.

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Step 1: Find a topic and review the literature

As we mentioned earlier, in a research paper, you, as the researcher, will try to answer a question . More specifically, that’s called a research question , and it sets the direction of your entire paper. What’s important to understand though is that you’ll need to answer that research question with the help of high-quality sources – for example, journal articles, government reports, case studies, and so on. We’ll circle back to this in a minute.

The first stage of the research process is deciding on what your research question will be and then reviewing the existing literature (in other words, past studies and papers) to see what they say about that specific research question. In some cases, your professor may provide you with a predetermined research question (or set of questions). However, in many cases, you’ll need to find your own research question within a certain topic area.

Finding a strong research question hinges on identifying a meaningful research gap – in other words, an area that’s lacking in existing research. There’s a lot to unpack here, so if you wanna learn more, check out the plain-language explainer video below.

Once you’ve figured out which question (or questions) you’ll attempt to answer in your research paper, you’ll need to do a deep dive into the existing literature – this is called a “ literature search ”. Again, there are many ways to go about this, but your most likely starting point will be Google Scholar .

If you’re new to Google Scholar, think of it as Google for the academic world. You can start by simply entering a few different keywords that are relevant to your research question and it will then present a host of articles for you to review. What you want to pay close attention to here is the number of citations for each paper – the more citations a paper has, the more credible it is (generally speaking – there are some exceptions, of course).

Ideally, what you’re looking for are well-cited papers that are highly relevant to your topic. That said, keep in mind that citations are a cumulative metric , so older papers will often have more citations than newer papers – just because they’ve been around for longer. So, don’t fixate on this metric in isolation – relevance and recency are also very important.

Beyond Google Scholar, you’ll also definitely want to check out academic databases and aggregators such as Science Direct, PubMed, JStor and so on. These will often overlap with the results that you find in Google Scholar, but they can also reveal some hidden gems – so, be sure to check them out.

Once you’ve worked your way through all the literature, you’ll want to catalogue all this information in some sort of spreadsheet so that you can easily recall who said what, when and within what context. If you’d like, we’ve got a free literature spreadsheet that helps you do exactly that.

Step 2: Develop a structure and outline

With your research question pinned down and your literature digested and catalogued, it’s time to move on to planning your actual research paper .

It might sound obvious, but it’s really important to have some sort of rough outline in place before you start writing your paper. So often, we see students eagerly rushing into the writing phase, only to land up with a disjointed research paper that rambles on in multiple

Now, the secret here is to not get caught up in the fine details . Realistically, all you need at this stage is a bullet-point list that describes (in broad strokes) what you’ll discuss and in what order. It’s also useful to remember that you’re not glued to this outline – in all likelihood, you’ll chop and change some sections once you start writing, and that’s perfectly okay. What’s important is that you have some sort of roadmap in place from the start.

At this stage you might be wondering, “ But how should I structure my research paper? ”. Well, there’s no one-size-fits-all solution here, but in general, a research paper will consist of a few relatively standardised components:

• Introduction
• Literature review
• Methodology

Let’s take a look at each of these.

First up is the introduction section . As the name suggests, the purpose of the introduction is to set the scene for your research paper. There are usually (at least) four ingredients that go into this section – these are the background to the topic, the research problem and resultant research question , and the justification or rationale. If you’re interested, the video below unpacks the introduction section in more detail. 

The next section of your research paper will typically be your literature review . Remember all that literature you worked through earlier? Well, this is where you’ll present your interpretation of all that content . You’ll do this by writing about recent trends, developments, and arguments within the literature – but more specifically, those that are relevant to your research question . The literature review can oftentimes seem a little daunting, even to seasoned researchers, so be sure to check out our extensive collection of literature review content here .

With the introduction and lit review out of the way, the next section of your paper is the research methodology . In a nutshell, the methodology section should describe to your reader what you did (beyond just reviewing the existing literature) to answer your research question. For example, what data did you collect, how did you collect that data, how did you analyse that data and so on? For each choice, you’ll also need to justify why you chose to do it that way, and what the strengths and weaknesses of your approach were.

Now, it’s worth mentioning that for some research papers, this aspect of the project may be a lot simpler . For example, you may only need to draw on secondary sources (in other words, existing data sets). In some cases, you may just be asked to draw your conclusions from the literature search itself (in other words, there may be no data analysis at all). But, if you are required to collect and analyse data, you’ll need to pay a lot of attention to the methodology section. The video below provides an example of what the methodology section might look like.

By this stage of your paper, you will have explained what your research question is, what the existing literature has to say about that question, and how you analysed additional data to try to answer your question. So, the natural next step is to present your analysis of that data . This section is usually called the “results” or “analysis” section and this is where you’ll showcase your findings.

Depending on your school’s requirements, you may need to present and interpret the data in one section – or you might split the presentation and the interpretation into two sections. In the latter case, your “results” section will just describe the data, and the “discussion” is where you’ll interpret that data and explicitly link your analysis back to your research question. If you’re not sure which approach to take, check in with your professor or take a look at past papers to see what the norms are for your programme.

Alright – once you’ve presented and discussed your results, it’s time to wrap it up . This usually takes the form of the “ conclusion ” section. In the conclusion, you’ll need to highlight the key takeaways from your study and close the loop by explicitly answering your research question. Again, the exact requirements here will vary depending on your programme (and you may not even need a conclusion section at all) – so be sure to check with your professor if you’re unsure.

Step 3: Write and refine

Finally, it’s time to get writing. All too often though, students hit a brick wall right about here… So, how do you avoid this happening to you?

Well, there’s a lot to be said when it comes to writing a research paper (or any sort of academic piece), but we’ll share three practical tips to help you get started.

First and foremost , it’s essential to approach your writing as an iterative process. In other words, you need to start with a really messy first draft and then polish it over multiple rounds of editing. Don’t waste your time trying to write a perfect research paper in one go. Instead, take the pressure off yourself by adopting an iterative approach.

Secondly , it’s important to always lean towards critical writing , rather than descriptive writing. What does this mean? Well, at the simplest level, descriptive writing focuses on the “ what ”, while critical writing digs into the “ so what ” – in other words, the implications. If you’re not familiar with these two types of writing, don’t worry! You can find a plain-language explanation here.

Last but not least, you’ll need to get your referencing right. Specifically, you’ll need to provide credible, correctly formatted citations for the statements you make. We see students making referencing mistakes all the time and it costs them dearly. The good news is that you can easily avoid this by using a simple reference manager . If you don’t have one, check out our video about Mendeley, an easy (and free) reference management tool that you can start using today.

Recap: Key Takeaways

We’ve covered a lot of ground here. To recap, the three steps to writing a high-quality research paper are:

• To choose a research question and review the literature
• To plan your paper structure and draft an outline
• To take an iterative approach to writing, focusing on critical writing and strong referencing

Remember, this is just a b ig-picture overview of the research paper development process and there’s a lot more nuance to unpack. So, be sure to grab a copy of our free research paper template to learn more about how to write a research paper.

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Home » Research Design – Types, Methods and Examples

Research Design – Types, Methods and Examples

Table of Contents

Research Design

Definition:

Research design refers to the overall strategy or plan for conducting a research study. It outlines the methods and procedures that will be used to collect and analyze data, as well as the goals and objectives of the study. Research design is important because it guides the entire research process and ensures that the study is conducted in a systematic and rigorous manner.

Types of Research Design

Types of Research Design are as follows:

Descriptive Research Design

This type of research design is used to describe a phenomenon or situation. It involves collecting data through surveys, questionnaires, interviews, and observations. The aim of descriptive research is to provide an accurate and detailed portrayal of a particular group, event, or situation. It can be useful in identifying patterns, trends, and relationships in the data.

Correlational Research Design

Correlational research design is used to determine if there is a relationship between two or more variables. This type of research design involves collecting data from participants and analyzing the relationship between the variables using statistical methods. The aim of correlational research is to identify the strength and direction of the relationship between the variables.

Experimental Research Design

Experimental research design is used to investigate cause-and-effect relationships between variables. This type of research design involves manipulating one variable and measuring the effect on another variable. It usually involves randomly assigning participants to groups and manipulating an independent variable to determine its effect on a dependent variable. The aim of experimental research is to establish causality.

Quasi-experimental Research Design

Quasi-experimental research design is similar to experimental research design, but it lacks one or more of the features of a true experiment. For example, there may not be random assignment to groups or a control group. This type of research design is used when it is not feasible or ethical to conduct a true experiment.

Case Study Research Design

Case study research design is used to investigate a single case or a small number of cases in depth. It involves collecting data through various methods, such as interviews, observations, and document analysis. The aim of case study research is to provide an in-depth understanding of a particular case or situation.

Longitudinal Research Design

Longitudinal research design is used to study changes in a particular phenomenon over time. It involves collecting data at multiple time points and analyzing the changes that occur. The aim of longitudinal research is to provide insights into the development, growth, or decline of a particular phenomenon over time.

Structure of Research Design

The format of a research design typically includes the following sections:

• Introduction : This section provides an overview of the research problem, the research questions, and the importance of the study. It also includes a brief literature review that summarizes previous research on the topic and identifies gaps in the existing knowledge.
• Research Questions or Hypotheses: This section identifies the specific research questions or hypotheses that the study will address. These questions should be clear, specific, and testable.
• Research Methods : This section describes the methods that will be used to collect and analyze data. It includes details about the study design, the sampling strategy, the data collection instruments, and the data analysis techniques.
• Data Collection: This section describes how the data will be collected, including the sample size, data collection procedures, and any ethical considerations.
• Data Analysis: This section describes how the data will be analyzed, including the statistical techniques that will be used to test the research questions or hypotheses.
• Results : This section presents the findings of the study, including descriptive statistics and statistical tests.
• Discussion and Conclusion : This section summarizes the key findings of the study, interprets the results, and discusses the implications of the findings. It also includes recommendations for future research.
• References : This section lists the sources cited in the research design.

Example of Research Design

An Example of Research Design could be:

Research question: Does the use of social media affect the academic performance of high school students?

Research design:

• Research approach : The research approach will be quantitative as it involves collecting numerical data to test the hypothesis.
• Research design : The research design will be a quasi-experimental design, with a pretest-posttest control group design.
• Sample : The sample will be 200 high school students from two schools, with 100 students in the experimental group and 100 students in the control group.
• Data collection : The data will be collected through surveys administered to the students at the beginning and end of the academic year. The surveys will include questions about their social media usage and academic performance.
• Data analysis : The data collected will be analyzed using statistical software. The mean scores of the experimental and control groups will be compared to determine whether there is a significant difference in academic performance between the two groups.
• Limitations : The limitations of the study will be acknowledged, including the fact that social media usage can vary greatly among individuals, and the study only focuses on two schools, which may not be representative of the entire population.
• Ethical considerations: Ethical considerations will be taken into account, such as obtaining informed consent from the participants and ensuring their anonymity and confidentiality.

How to Write Research Design

Writing a research design involves planning and outlining the methodology and approach that will be used to answer a research question or hypothesis. Here are some steps to help you write a research design:

• Define the research question or hypothesis : Before beginning your research design, you should clearly define your research question or hypothesis. This will guide your research design and help you select appropriate methods.
• Select a research design: There are many different research designs to choose from, including experimental, survey, case study, and qualitative designs. Choose a design that best fits your research question and objectives.
• Develop a sampling plan : If your research involves collecting data from a sample, you will need to develop a sampling plan. This should outline how you will select participants and how many participants you will include.
• Define variables: Clearly define the variables you will be measuring or manipulating in your study. This will help ensure that your results are meaningful and relevant to your research question.
• Choose data collection methods : Decide on the data collection methods you will use to gather information. This may include surveys, interviews, observations, experiments, or secondary data sources.
• Create a data analysis plan: Develop a plan for analyzing your data, including the statistical or qualitative techniques you will use.
• Consider ethical concerns : Finally, be sure to consider any ethical concerns related to your research, such as participant confidentiality or potential harm.

When to Write Research Design

Research design should be written before conducting any research study. It is an important planning phase that outlines the research methodology, data collection methods, and data analysis techniques that will be used to investigate a research question or problem. The research design helps to ensure that the research is conducted in a systematic and logical manner, and that the data collected is relevant and reliable.

Ideally, the research design should be developed as early as possible in the research process, before any data is collected. This allows the researcher to carefully consider the research question, identify the most appropriate research methodology, and plan the data collection and analysis procedures in advance. By doing so, the research can be conducted in a more efficient and effective manner, and the results are more likely to be valid and reliable.

Purpose of Research Design

The purpose of research design is to plan and structure a research study in a way that enables the researcher to achieve the desired research goals with accuracy, validity, and reliability. Research design is the blueprint or the framework for conducting a study that outlines the methods, procedures, techniques, and tools for data collection and analysis.

Some of the key purposes of research design include:

• Providing a clear and concise plan of action for the research study.
• Ensuring that the research is conducted ethically and with rigor.
• Maximizing the accuracy and reliability of the research findings.
• Minimizing the possibility of errors, biases, or confounding variables.
• Ensuring that the research is feasible, practical, and cost-effective.
• Determining the appropriate research methodology to answer the research question(s).
• Identifying the sample size, sampling method, and data collection techniques.
• Determining the data analysis method and statistical tests to be used.
• Facilitating the replication of the study by other researchers.
• Enhancing the validity and generalizability of the research findings.

Applications of Research Design

There are numerous applications of research design in various fields, some of which are:

• Social sciences: In fields such as psychology, sociology, and anthropology, research design is used to investigate human behavior and social phenomena. Researchers use various research designs, such as experimental, quasi-experimental, and correlational designs, to study different aspects of social behavior.
• Education : Research design is essential in the field of education to investigate the effectiveness of different teaching methods and learning strategies. Researchers use various designs such as experimental, quasi-experimental, and case study designs to understand how students learn and how to improve teaching practices.
• Health sciences : In the health sciences, research design is used to investigate the causes, prevention, and treatment of diseases. Researchers use various designs, such as randomized controlled trials, cohort studies, and case-control studies, to study different aspects of health and healthcare.
• Business : Research design is used in the field of business to investigate consumer behavior, marketing strategies, and the impact of different business practices. Researchers use various designs, such as survey research, experimental research, and case studies, to study different aspects of the business world.
• Engineering : In the field of engineering, research design is used to investigate the development and implementation of new technologies. Researchers use various designs, such as experimental research and case studies, to study the effectiveness of new technologies and to identify areas for improvement.

Advantages of Research Design

Here are some advantages of research design:

• Systematic and organized approach : A well-designed research plan ensures that the research is conducted in a systematic and organized manner, which makes it easier to manage and analyze the data.
• Clear objectives: The research design helps to clarify the objectives of the study, which makes it easier to identify the variables that need to be measured, and the methods that need to be used to collect and analyze data.
• Minimizes bias: A well-designed research plan minimizes the chances of bias, by ensuring that the data is collected and analyzed objectively, and that the results are not influenced by the researcher’s personal biases or preferences.
• Efficient use of resources: A well-designed research plan helps to ensure that the resources (time, money, and personnel) are used efficiently and effectively, by focusing on the most important variables and methods.
• Replicability: A well-designed research plan makes it easier for other researchers to replicate the study, which enhances the credibility and reliability of the findings.
• Validity: A well-designed research plan helps to ensure that the findings are valid, by ensuring that the methods used to collect and analyze data are appropriate for the research question.
• Generalizability : A well-designed research plan helps to ensure that the findings can be generalized to other populations, settings, or situations, which increases the external validity of the study.

Research Design Vs Research Methodology

About the author.

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Illustration by James Round

How to plan a research project

Whether for a paper or a thesis, define your question, review the work of others – and leave yourself open to discovery.

by Brooke Harrington   + BIO

is professor of sociology at Dartmouth College in New Hampshire. Her research has won international awards both for scholarly quality and impact on public life. She has published dozens of articles and three books, most recently the bestseller Capital without Borders (2016), now translated into five languages.

Edited by Sam Haselby

Need to know

‘When curiosity turns to serious matters, it’s called research.’ – From Aphorisms (1880-1905) by Marie von Ebner-Eschenbach

Planning research projects is a time-honoured intellectual exercise: one that requires both creativity and sharp analytical skills. The purpose of this Guide is to make the process systematic and easy to understand. While there is a great deal of freedom and discovery involved – from the topics you choose, to the data and methods you apply – there are also some norms and constraints that obtain, no matter what your academic level or field of study. For those in high school through to doctoral students, and from art history to archaeology, research planning involves broadly similar steps, including: formulating a question, developing an argument or predictions based on previous research, then selecting the information needed to answer your question.

Some of this might sound self-evident but, as you’ll find, research requires a different way of approaching and using information than most of us are accustomed to in everyday life. That is why I include orienting yourself to knowledge-creation as an initial step in the process. This is a crucial and underappreciated phase in education, akin to making the transition from salaried employment to entrepreneurship: suddenly, you’re on your own, and that requires a new way of thinking about your work.

What follows is a distillation of what I’ve learned about this process over 27 years as a professional social scientist. It reflects the skills that my own professors imparted in the sociology doctoral programme at Harvard, as well as what I learned later on as a research supervisor for Ivy League PhD and MA students, and then as the author of award-winning scholarly books and articles. It can be adapted to the demands of both short projects (such as course term papers) and long ones, such as a thesis.

At its simplest, research planning involves the four distinct steps outlined below: orienting yourself to knowledge-creation; defining your research question; reviewing previous research on your question; and then choosing relevant data to formulate your own answers. Because the focus of this Guide is on planning a research project, as opposed to conducting a research project, this section won’t delve into the details of data-collection or analysis; those steps happen after you plan the project. In addition, the topic is vast: year-long doctoral courses are devoted to data and analysis. Instead, the fourth part of this section will outline some basic strategies you could use in planning a data-selection and analysis process appropriate to your research question.

Step 1: Orient yourself

Planning and conducting research requires you to make a transition, from thinking like a consumer of information to thinking like a producer of information. That sounds simple, but it’s actually a complex task. As a practical matter, this means putting aside the mindset of a student, which treats knowledge as something created by other people. As students, we are often passive receivers of knowledge: asked to do a specified set of readings, then graded on how well we reproduce what we’ve read.

Researchers, however, must take on an active role as knowledge producers . Doing research requires more of you than reading and absorbing what other people have written: you have to engage in a dialogue with it. That includes arguing with previous knowledge and perhaps trying to show that ideas we have accepted as given are actually wrong or incomplete. For example, rather than simply taking in the claims of an author you read, you’ll need to draw out the implications of those claims: if what the author is saying is true, what else does that suggest must be true? What predictions could you make based on the author’s claims?

In other words, rather than treating a reading as a source of truth – even if it comes from a revered source, such as Plato or Marie Curie – this orientation step asks you to treat the claims you read as provisional and subject to interrogation. That is one of the great pieces of wisdom that science and philosophy can teach us: that the biggest advances in human understanding have been made not by being correct about trivial things, but by being wrong in an interesting way . For example, Albert Einstein was wrong about quantum mechanics, but his arguments about it with his fellow physicist Niels Bohr have led to some of the biggest breakthroughs in science, even a century later.

Step 2: Define your research question

Students often give this step cursory attention, but experienced researchers know that formulating a good question is sometimes the most difficult part of the research planning process. That is because the precise language of the question frames the rest of the project. It’s therefore important to pose the question carefully, in a way that’s both possible to answer and likely to yield interesting results. Of course, you must choose a question that interests you, but that’s only the beginning of what’s likely to be an iterative process: most researchers come back to this step repeatedly, modifying their questions in light of previous research, resource limitations and other considerations.

Researchers face limits in terms of time and money. They, like everyone else, have to pose research questions that they can plausibly answer given the constraints they face. For example, it would be inadvisable to frame a project around the question ‘What are the roots of the Arab-Israeli conflict?’ if you have only a week to develop an answer and no background on that topic. That’s not to limit your imagination: you can come up with any question you’d like. But it typically does require some creativity to frame a question that you can answer well – that is, by investigating thoroughly and providing new insights – within the limits you face.

In addition to being interesting to you, and feasible within your resource constraints, the third and most important characteristic of a ‘good’ research topic is whether it allows you to create new knowledge. It might turn out that your question has already been asked and answered to your satisfaction: if so, you’ll find out in the next step of this process. On the other hand, you might come up with a research question that hasn’t been addressed previously. Before you get too excited about breaking uncharted ground, consider this: a lot of potentially researchable questions haven’t been studied for good reason ; they might have answers that are trivial or of very limited interest. This could include questions such as ‘Why does the area of a circle equal π r²?’ or ‘Did winter conditions affect Napoleon’s plans to invade Russia?’ Of course, you might be able to make the argument that a seemingly trivial question is actually vitally important, but you must be prepared to back that up with convincing evidence. The exercise in the ‘Learn More’ section below will help you think through some of these issues.

Finally, scholarly research questions must in some way lead to new and distinctive insights. For example, lots of people have studied gender roles in sports teams; what can you ask that hasn’t been asked before? Reinventing the wheel is the number-one no-no in this endeavour. That’s why the next step is so important: reviewing previous research on your topic. Depending on what you find in that step, you might need to revise your research question; iterating between your question and the existing literature is a normal process. But don’t worry: it doesn’t go on forever. In fact, the iterations taper off – and your research question stabilises – as you develop a firm grasp of the current state of knowledge on your topic.

Step 3: Review previous research

In academic research, from articles to books, it’s common to find a section called a ‘literature review’. The purpose of that section is to describe the state of the art in knowledge on the research question that a project has posed. It demonstrates that researchers have thoroughly and systematically reviewed the relevant findings of previous studies on their topic, and that they have something novel to contribute.

Your own research project should include something like this, even if it’s a high-school term paper. In the research planning process, you’ll want to list at least half a dozen bullet points stating the major findings on your topic by other people. In relation to those findings, you should be able to specify where your project could provide new and necessary insights. There are two basic rhetorical positions one can take in framing the novelty-plus-importance argument required of academic research:

• Position 1 requires you to build on or extend a set of existing ideas; that means saying something like: ‘Person A has argued that X is true about gender; this implies Y, which has not yet been tested. My project will test Y, and if I find evidence to support it, that will change the way we understand gender.’
• Position 2 is to argue that there is a gap in existing knowledge, either because previous research has reached conflicting conclusions or has failed to consider something important. For example, one could say that research on middle schoolers and gender has been limited by being conducted primarily in coeducational environments, and that findings might differ dramatically if research were conducted in more schools where the student body was all-male or all-female.

Your overall goal in this step of the process is to show that your research will be part of a larger conversation: that is, how your project flows from what’s already known, and how it advances, extends or challenges that existing body of knowledge. That will be the contribution of your project, and it constitutes the motivation for your research.

Two things are worth mentioning about your search for sources of relevant previous research. First, you needn’t look only at studies on your precise topic. For example, if you want to study gender-identity formation in schools, you shouldn’t restrict yourself to studies of schools; the empirical setting (schools) is secondary to the larger social process that interests you (how people form gender identity). That process occurs in many different settings, so cast a wide net. Second, be sure to use legitimate sources – meaning publications that have been through some sort of vetting process, whether that involves peer review (as with academic journal articles you might find via Google Scholar) or editorial review (as you’d find in well-known mass media publications, such as The Economist or The Washington Post ). What you’ll want to avoid is using unvetted sources such as personal blogs or Wikipedia. Why? Because anybody can write anything in those forums, and there is no way to know – unless you’re already an expert – if the claims you find there are accurate. Often, they’re not.

Step 4: Choose your data and methods

Whatever your research question is, eventually you’ll need to consider which data source and analytical strategy are most likely to provide the answers you’re seeking. One starting point is to consider whether your question would be best addressed by qualitative data (such as interviews, observations or historical records), quantitative data (such as surveys or census records) or some combination of both. Your ideas about data sources will, in turn, suggest options for analytical methods.

You might need to collect your own data, or you might find everything you need readily available in an existing dataset someone else has created. A great place to start is with a research librarian: university libraries always have them and, at public universities, those librarians can work with the public, including people who aren’t affiliated with the university. If you don’t happen to have a public university and its library close at hand, an ordinary public library can still be a good place to start: the librarians are often well versed in accessing data sources that might be relevant to your study, such as the census, or historical archives, or the Survey of Consumer Finances.

Because your task at this point is to plan research, rather than conduct it, the purpose of this step is not to commit you irrevocably to a course of action. Instead, your goal here is to think through a feasible approach to answering your research question. You’ll need to find out, for example, whether the data you want exist; if not, do you have a realistic chance of gathering the data yourself, or would it be better to modify your research question? In terms of analysis, would your strategy require you to apply statistical methods? If so, do you have those skills? If not, do you have time to learn them, or money to hire a research assistant to run the analysis for you?

Please be aware that qualitative methods in particular are not the casual undertaking they might appear to be. Many people make the mistake of thinking that only quantitative data and methods are scientific and systematic, while qualitative methods are just a fancy way of saying: ‘I talked to some people, read some old newspapers, and drew my own conclusions.’ Nothing could be further from the truth. In the final section of this guide, you’ll find some links to resources that will provide more insight on standards and procedures governing qualitative research, but suffice it to say: there are rules about what constitutes legitimate evidence and valid analytical procedure for qualitative data, just as there are for quantitative data.

Circle back and consider revising your initial plans

As you work through these four steps in planning your project, it’s perfectly normal to circle back and revise. Research planning is rarely a linear process. It’s also common for new and unexpected avenues to suggest themselves. As the sociologist Thorstein Veblen wrote in 1908 : ‘The outcome of any serious research can only be to make two questions grow where only one grew before.’ That’s as true of research planning as it is of a completed project. Try to enjoy the horizons that open up for you in this process, rather than becoming overwhelmed; the four steps, along with the two exercises that follow, will help you focus your plan and make it manageable.

Key points – How to plan a research project

• Planning a research project is essential no matter your academic level or field of study. There is no one ‘best’ way to design research, but there are certain guidelines that can be helpfully applied across disciplines.
• Orient yourself to knowledge-creation. Make the shift from being a consumer of information to being a producer of information.
• Define your research question. Your question frames the rest of your project, sets the scope, and determines the kinds of answers you can find.
• Review previous research on your question. Survey the existing body of relevant knowledge to ensure that your research will be part of a larger conversation.
• Choose your data and methods. For instance, will you be collecting qualitative data, via interviews, or numerical data, via surveys?
• Circle back and consider revising your initial plans. Expect your research question in particular to undergo multiple rounds of refinement as you learn more about your topic.

Good research questions tend to beget more questions. This can be frustrating for those who want to get down to business right away. Try to make room for the unexpected: this is usually how knowledge advances. Many of the most significant discoveries in human history have been made by people who were looking for something else entirely. There are ways to structure your research planning process without over-constraining yourself; the two exercises below are a start, and you can find further methods in the Links and Books section.

The following exercise provides a structured process for advancing your research project planning. After completing it, you’ll be able to do the following:

• describe clearly and concisely the question you’ve chosen to study
• summarise the state of the art in knowledge about the question, and where your project could contribute new insight
• identify the best strategy for gathering and analysing relevant data

In other words, the following provides a systematic means to establish the building blocks of your research project.

Exercise 1: Definition of research question and sources

This exercise prompts you to select and clarify your general interest area, develop a research question, and investigate sources of information. The annotated bibliography will also help you refine your research question so that you can begin the second assignment, a description of the phenomenon you wish to study.

Jot down a few bullet points in response to these two questions, with the understanding that you’ll probably go back and modify your answers as you begin reading other studies relevant to your topic:

• What will be the general topic of your paper?
• What will be the specific topic of your paper?

b) Research question(s)

Use the following guidelines to frame a research question – or questions – that will drive your analysis. As with Part 1 above, you’ll probably find it necessary to change or refine your research question(s) as you complete future assignments.

• Your question should be phrased so that it can’t be answered with a simple ‘yes’ or ‘no’.
• Your question should have more than one plausible answer.
• Your question should draw relationships between two or more concepts; framing the question in terms of How? or What? often works better than asking Why ?

c) Annotated bibliography

Most or all of your background information should come from two sources: scholarly books and journals, or reputable mass media sources. You might be able to access journal articles electronically through your library, using search engines such as JSTOR and Google Scholar. This can save you a great deal of time compared with going to the library in person to search periodicals. General news sources, such as those accessible through LexisNexis, are acceptable, but should be cited sparingly, since they don’t carry the same level of credibility as scholarly sources. As discussed above, unvetted sources such as blogs and Wikipedia should be avoided, because the quality of the information they provide is unreliable and often misleading.

To create an annotated bibliography, provide the following information for at least 10 sources relevant to your specific topic, using the format suggested below.

Name of author(s):

Publication date:

Title of book, chapter, or article:

If a chapter or article, title of journal or book where they appear:

Brief description of this work, including main findings and methods ( c 75 words):

Summary of how this work contributes to your project ( c 75 words):

Brief description of the implications of this work ( c 25 words):

Identify any gap or controversy in knowledge this work points up, and how your project could address those problems ( c 50 words):

Exercise 2: Towards an analysis

Develop a short statement ( c 250 words) about the kind of data that would be useful to address your research question, and how you’d analyse it. Some questions to consider in writing this statement include:

• What are the central concepts or variables in your project? Offer a brief definition of each.
• Do any data sources exist on those concepts or variables, or would you need to collect data?
• Of the analytical strategies you could apply to that data, which would be the most appropriate to answer your question? Which would be the most feasible for you? Consider at least two methods, noting their advantages or disadvantages for your project.

Links & books

One of the best texts ever written about planning and executing research comes from a source that might be unexpected: a 60-year-old work on urban planning by a self-trained scholar. The classic book The Death and Life of Great American Cities (1961) by Jane Jacobs (available complete and free of charge via this link ) is worth reading in its entirety just for the pleasure of it. But the final 20 pages – a concluding chapter titled ‘The Kind of Problem a City Is’ – are really about the process of thinking through and investigating a problem. Highly recommended as a window into the craft of research.

Jacobs’s text references an essay on advancing human knowledge by the mathematician Warren Weaver. At the time, Weaver was director of the Rockefeller Foundation, in charge of funding basic research in the natural and medical sciences. Although the essay is titled ‘A Quarter Century in the Natural Sciences’ (1960) and appears at first blush to be merely a summation of one man’s career, it turns out to be something much bigger and more interesting: a meditation on the history of human beings seeking answers to big questions about the world. Weaver goes back to the 17th century to trace the origins of systematic research thinking, with enthusiasm and vivid anecdotes that make the process come alive. The essay is worth reading in its entirety, and is available free of charge via this link .

For those seeking a more in-depth, professional-level discussion of the logic of research design, the political scientist Harvey Starr provides insight in a compact format in the article ‘Cumulation from Proper Specification: Theory, Logic, Research Design, and “Nice” Laws’ (2005). Starr reviews the ‘research triad’, consisting of the interlinked considerations of formulating a question, selecting relevant theories and applying appropriate methods. The full text of the article, published in the scholarly journal Conflict Management and Peace Science , is available, free of charge, via this link .

Finally, the book Getting What You Came For (1992) by Robert Peters is not only an outstanding guide for anyone contemplating graduate school – from the application process onward – but it also includes several excellent chapters on planning and executing research, applicable across a wide variety of subject areas. It was an invaluable resource for me 25 years ago, and it remains in print with good reason; I recommend it to all my students, particularly Chapter 16 (‘The Thesis Topic: Finding It’), Chapter 17 (‘The Thesis Proposal’) and Chapter 18 (‘The Thesis: Writing It’).

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How to Get Started With a Research Project

Last Updated: October 3, 2023 Fact Checked

This article was co-authored by Chris Hadley, PhD . Chris Hadley, PhD is part of the wikiHow team and works on content strategy and data and analytics. Chris Hadley earned his PhD in Cognitive Psychology from UCLA in 2006. Chris' academic research has been published in numerous scientific journals. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 311,996 times.

You'll be required to undertake and complete research projects throughout your academic career and even, in many cases, as a member of the workforce. Don't worry if you feel stuck or intimidated by the idea of a research project, with care and dedication, you can get the project done well before the deadline!

Development and Foundation

• Don't hesitate while writing down ideas. You'll end up with some mental noise on the paper – silly or nonsensical phrases that your brain just pushes out. That's fine. Think of it as sweeping the cobwebs out of your attic. After a minute or two, better ideas will begin to form (and you might have a nice little laugh at your own expense in the meantime).

• Some instructors will even provide samples of previously successful topics if you ask for them. Just be careful that you don't end up stuck with an idea you want to do, but are afraid to do because you know someone else did it before.

• For example, if your research topic is “urban poverty,” you could look at that topic across ethnic or sexual lines, but you could also look into corporate wages, minimum wage laws, the cost of medical benefits, the loss of unskilled jobs in the urban core, and on and on. You could also try comparing and contrasting urban poverty with suburban or rural poverty, and examine things that might be different about both areas, such as diet and exercise levels, or air pollution.

• Think in terms of questions you want answered. A good research project should collect information for the purpose of answering (or at least attempting to answer) a question. As you review and interconnect topics, you'll think of questions that don't seem to have clear answers yet. These questions are your research topics.

• Don't limit yourself to libraries and online databases. Think in terms of outside resources as well: primary sources, government agencies, even educational TV programs. If you want to know about differences in animal population between public land and an Indian reservation, call the reservation and see if you can speak to their department of fish and wildlife.
• If you're planning to go ahead with original research, that's great – but those techniques aren't covered in this article. Instead, speak with qualified advisors and work with them to set up a thorough, controlled, repeatable process for gathering information.

• If your plan comes down to “researching the topic,” and there aren't any more specific things you can say about it, write down the types of sources you plan to use instead: books (library or private?), magazines (which ones?), interviews, and so on. Your preliminary research should have given you a solid idea of where to begin.

Expanding Your Idea with Research

• It's generally considered more convincing to source one item from three different authors who all agree on it than it is to rely too heavily on one book. Go for quantity at least as much as quality. Be sure to check citations, endnotes, and bibliographies to get more potential sources (and see whether or not all your authors are just quoting the same, older author).
• Writing down your sources and any other relevant details (such as context) around your pieces of information right now will save you lots of trouble in the future.

• Use many different queries to get the database results you want. If one phrasing or a particular set of words doesn't yield useful results, try rephrasing it or using synonymous terms. Online academic databases tend to be dumber than the sum of their parts, so you'll have to use tangentially related terms and inventive language to get all the results you want.

• If it's sensible, consider heading out into the field and speaking to ordinary people for their opinions. This isn't always appropriate (or welcomed) in a research project, but in some cases, it can provide you with some excellent perspective for your research.
• Review cultural artifacts as well. In many areas of study, there's useful information on attitudes, hopes, and/or concerns of people in a particular time and place contained within the art, music, and writing they produced. One has only to look at the woodblock prints of the later German Expressionists, for example, to understand that they lived in a world they felt was often dark, grotesque, and hopeless. Song lyrics and poetry can likewise express strong popular attitudes.

Expert Q&A

• Start early. The foundation of a great research project is the research, which takes time and patience to gather even if you aren't performing any original research of your own. Set aside time for it whenever you can, at least until your initial gathering phase is complete. Past that point, the project should practically come together on its own. Thanks Helpful 1 Not Helpful 0
• When in doubt, write more, rather than less. It's easier to pare down and reorganize an overabundance of information than it is to puff up a flimsy core of facts and anecdotes. Thanks Helpful 1 Not Helpful 0

• Respect the wishes of others. Unless you're a research journalist, it's vital that you yield to the wishes and requests of others before engaging in original research, even if it's technically ethical. Many older American Indians, for instance, harbor a great deal of cultural resentment towards social scientists who visit reservations for research, even those invited by tribal governments for important reasons such as language revitalization. Always tread softly whenever you're out of your element, and only work with those who want to work with you. Thanks Helpful 8 Not Helpful 2
• Be mindful of ethical concerns. Especially if you plan to use original research, there are very stringent ethical guidelines that must be followed for any credible academic body to accept it. Speak to an advisor (such as a professor) about what you plan to do and what steps you should take to verify that it will be ethical. Thanks Helpful 6 Not Helpful 2

You Might Also Like

• ↑ http://www.butte.edu/departments/cas/tipsheets/research/research_paper.html
• ↑ https://www.nhcc.edu/academics/library/doing-library-research/basic-steps-research-process
• ↑ https://library.sacredheart.edu/c.php?g=29803&p=185905
• ↑ https://owl.purdue.edu/owl/general_writing/common_writing_assignments/research_papers/choosing_a_topic.html
• ↑ https://www.unr.edu/writing-speaking-center/student-resources/writing-speaking-resources/using-an-interview-in-a-research-paper
• ↑ https://www.science.org/content/article/how-review-paper

About This Article

The easiest way to get started with a research project is to use your notes and other materials to come up with topics that interest you. Research your favorite topic to see if it can be developed, and then refine it into a research question. Begin thoroughly researching, and collect notes and sources. To learn more about finding reliable and helpful sources while you're researching, continue reading! Did this summary help you? Yes No

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Capstone Components

12 Research Design

The story continues….

“So, how do we go about answering our research questions?” asked Harry.

Physicus explained that they will have to analyze their questions to see what types of answers are required. Knowing this will guide their decisions about how to design the needs assessment to answer their questions.

“There are two basic types of answers to research questions, quantitative and qualitative. The types of answers the questions require tell us what type of research design we need,” said Physicus.

“I guess if I ask how we decide which type of research design we should choose, you will say, ‘It depends?'” uttered Harry.

Physicus’ face brightened as he blurted out, “Absolutely not! Negative!” Physicus continued, “If the research questions are stated well, there will only be two ways in which they can be answered. The research questions are king; they make all the decisions.”

“How come?” Harry appeared confused.

“Well, let us see. Think about our first question. How many mice will Pickles attack at one time? What type of answer does this question require? It requires a numeric answer, correct?” Physicus asked.

“Yes, that is correct,” Harry said.

Physicus continued, “Good. So, does our second question also require a numeric answer?”

“The second question is also answered with a number,” replied Harry

Physicus blurted, “Correct! This means we need to use a quantitative research design!”

Physicus continued, “Now if we had research questions that could not be answered with numbers, we would need to use a qualitative research design to answer our questions with words or phrases instead.”

Harry now appeared relieved, “I get it. So in designing a research project, we simply look for a way to answer the research questions. That’s easy!”

“Well, it depends,” answered Physicus smiling.

Interpreting the Story

There are qualitative, quantitative, mixed methods, and applied research designs. Based on the research questions, the research design will be obvious. Physicus led Harry in determining their investigation would need a quantitative design, because they only needed numerical data to answer their research questions. If Harry’s questions could only be answered with words or phrases, then a qualitative design would be needed. If the friends had questions needing to be answered with numbers and phrases, then either a mixed methods or an applied research design would have been the choice.

Research Design

The Research Design explains what type of research is being conducted in the needs assessment. The writing in this heading also explains why this type of research is needed to obtain the answers to the research or guiding questions for the project. The design provides a blueprint for the methodology. Articulating the nature of the research design is critical for explaining the Methodology (see the next chapter).

There are four categories of research designs used in educational research and a variety of specific research designs in each category. The first step in determining which category to use is to identify what type of data will answer the research questions. As in our story, Harry and Physicus had research questions that required quantitative answers, so the category of their research design is quantitative.

The next step in finding the specific research design is to consider the purpose (goal) of the research project. The research design must support the purpose. In our story, Harry and Physicus need a quantitative research design that supports their goal of determining the effect of the number of mice Pickles encounters at one time on his behavior.  A causal-comparative or quasi-experimental research design is the best choice for the friends because these are specific quantitative designs used to find a cause-and-effect relationship.

Quantitative Research Designs

Quantitative research designs seek results based on statistical analyses of the collected numerical data. The primary quantitative designs used in educational research include descriptive, correlational, causal-comparative, and quasi-experimental designs. Numerical data are collected and analyzed using statistical calculations appropriate for the design. For example, analyses like mean, median, mode, range, etc. are used to describe or explain a phenomenon observed in a descriptive research design. A correlational research design uses statistics, such as correlation coefficient or regression analyses to explain how two phenomena are related. Causal-comparative and quasi-experimental designs use analyses needed to establish causal relationships, such as pre-post testing, or behavior change (like in our story).

The use of numerical data guides both the methodology and the analysis protocols. The design also guides and limits how the results are interpreted. Examples of quantitative data found in educational research include test scores, grade point averages, and dropout rates.

Qualitative Research Designs

Qualitative research designs involve obtaining verbal, perspective, and/or visual results using code-based analyses of collected data. Typical qualitative designs used in educational research include the case study, phenomenological, grounded theory, and ethnography. These designs involve exploring behaviors, perceptions/feelings, and social/cultural phenomena found in educational settings.

Qualitative designs result in a written description of the findings. Data collection strategies include observations, interviews, focus groups, surveys, and documentation reviews. The data are recorded as words, phrases, sentences, and paragraphs. Data are then grouped together to form themes. The process of grouping data to form themes is called coding. The labeled themes become the “code” used to interpret the data. The coding can be determined ahead of time before data are collected, or the coding emerges from the collected data. Data collection strategies often include media such as video and audio recordings. These recordings are transcribed into words to allow for the coding analysis.

The use of qualitative data guides both the methodology and the analysis protocols. The “squishy” nature of qualitative data (words vs. numbers) and the data coding analysis limits the interpretation and conclusions made from the results. It is important to explain the coding analysis used to provide clear reasoning for the themes and how these relate to the research questions.

Mixed Method Designs

Mixed Methods research designs are used when the research questions must be answered with results that are both quantitative and qualitative. These designs integrate the data results to arrive at conclusions. A mixed method design is used when there are greater benefits to using multiple data types, sources, and analyses. Examples of typical mixed methods design approaches in education include convergent, explanatory, exploratory, and embedded designs. Using mixed methods approaches in educational research allows the researcher to triangulate, complement, or expand understanding using multiple types of data.

The use of mixed methods data guides the methodology, analysis, and interpretation of the results. Using both qualitative (quant) and quantitative (qual) data analyses provides a clearer or more balanced picture of the results. Data are analyzed sequentially or concurrently depending on the design. While the quantitative and qualitative data are analyzed independently, the results are interpreted integratively. The findings are a synthesis of the quantitative and qualitative analyses.

Applied Research Designs

Applied research designs seek both quantitative and qualitative results to address issues of educational practice. Applied research designs include evaluation, design and development, and action research. The purposes of applied research are to identify best practices, to innovate or improve current practices or policies, to test pedagogy, and to evaluate effectiveness. The results of applied research designs provide practical solutions to problems in educational practice.

Applied designs use both theoretical and empirical data. Theoretical data are collected from published theories or other research. Empirical data are obtained by conducting a needs assessment or other data collection methods. Data analyses include both quantitative and qualitative procedures. The findings are interpreted integratively as in mixed methods approaches, and then “applied” to the problem to form a solution.

Telling the research story

The Research Design in a research project tells the story of what direction the plot of the story will take.  The writing in this heading sets the stage for the rising action of the plot in the research story. The Research Design describes the journey that is about to take place. It functions to guide the reader in understanding the type of path the story will follow. The Research Design is the overall direction of the research story and is determined before deciding on the specific steps to take in obtaining and analyzing the data.

The Research Design heading appears in Chapter 2 of a capstone project. In the capstone project, the Research Design explains the type of design used for conducting the needs assessment.

Capstone Projects in Education: Learning the Research Story Copyright © 2023 by Kimberly Chappell and Greg I. Voykhansky is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

Dissertations and research projects

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Finding the gap

Developing research questions, epistemology, ethical approval, methodology and methods, recruiting participants, planning your analysis, writing your research proposal.

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When starting out on reading for your dissertation, you may feel a little overwhelmed with the amount of research out there related to your topic. This is normal!

Your first job is to start to make sense of this existing research, sketching out a map with your dissertation in the centre. Around you will be various ‘neighbourhoods’ or groups of literature that are connected in some way, perhaps by a shared theme or group of participants. You might also start to identify ‘points of interest’ - key texts, models or theories that need to be acknowledged in order for a reader to understand your approach to your research area. 

In drawing this map, your aim is to identify the research gap or problem - an issue or question that you feel has not been fully addressed by existing studies. Remember, there is no expectation that you will have read absolutely everything on your subject, but you should be able to use the wide range of sources available to you to persuade the reader of the relevance and importance of your chosen topic.

Here are a few common approaches to finding the gap that might provide some inspiration for your own dissertation:

• Chronological , tracing change and development over time. For example, in a study of contemporary attitudes to tattoos, you might start by looking at historical examples of tattooing in other cultures, mapping out a timeline of key trends and shifts in the practice over time.  
• Thematic , mapping out the reading around topics or themes that multiple papers have in common. If you are investigating stress and anxiety in higher education, you might start out by searching for literature on mental health in universities to establish the 'bigger picture' before zooming in on a specific topic.
• Venn diagram , bringing together two otherwise distinct areas to find the literature that is common to both/bridges the gap. You may be working on a topic that is well-researched (stroke patient recovery) but adopting a new angle (from your perspective as a physiotherapist). Start by reading the literature in each area separately, fitting the papers into a Venn diagram that enables you to see where the closest links or overlaps between the two areas occur.
• Context-based , where the literature is split based on which participants are involved or the geographical/cultural environment in which it was carried out. You might be interested in how Kenyan companies address fraud and financial corruption, and start your literature search by identifying examples and case studies from other countries and regions.
• Research methods , where the literature tends to fall into different approaches to the same research problem. I f the focus of your dissertation is to apply and test a new method, such as a machine learning algorithm, you could start by identifying if and where a similar method has been used in existing research (a bottom-up approach to literature searching).

By reading widely in the early stages of your project, you should begin to get a sense of what research has already been conducted in your area, and where you fit into this map of research. For some people, there will be a clear gap or under explored topic in the research that their dissertation will aim to tackle or solve. Other projects may be less radical, focusing more on testing the transferability of an existing concept or study.  By drawing on this existing research, you are justifying the relevance of your own dissertation project, showing how it contributes (even in small way) to research in your field.

Once you have identified a problem or gap in the literature, you need to begin thinking about you will address this in your research. Research questions help to focus your project by highlighting what you want to learn about your topic, as well as providing guidance about how your data will be collected and analysed.

For example:

RQ1: Do media texts improve access to learning for low attaining students? RQ2:   Does exploring poetry through the lens of student interest positively affect motivation?

These research questions are effective as they give a clear indication of the research topic (media texts/student interest), participant group (low attaining students) and research measures (access to learning/motivation and engagement).

Whilst there isn't a perfect formula for writing research questions, here are some top tips:

• Show the relevance of your topic - make it clear what your research is trying to achieve. Is it addressing a gap in the literature? Testing theory with a specific group? Analysing professional practice?
• Demonstrate your project is achievable - whilst your research questions don't need to go into detail about your methods, you should try to show that your project is realistic, given your available time and resources. It is important to consider what types of data you are able to collect/access to answer your research questions.
• Be analytical, not descriptive - a good research question generally guides you to analyse a problem; this means that words like 'How', 'Examine', and 'Evaluate' are more useful than words like 'what' or 'describe'.
• Keep questions clear and focused - ultimately these questions act as guidance for how you will address the problem/gap you have identified

Research questions are not easy to write. They take time and require work: rarely will you stumble upon your research questions with ease. Instead, you start with a problem and refine your ideas until you have a workable way to research your area of interest.

Epistemology concerns the nature of knowledge and how we come to know what we know. It provides a philosophical grounding for considering what knowledge is possible and that how we determine that knowledge is adequate and legitimate. As such there are quite a range of epistemologies. Fortunately, it is unlikely that you will be expected to go into great detail about the epistemology of your research. It is however, important to consider what is accepted as 'knowledge' in your research.

It is likely that the epistemology of your research will either be positivistic or interpretivist , so it's worth considering the differences between them:

The positivist research philosophy understands phenomena through objective measurement , to collect data that can be used to develop generalisations and facts about the world.

By contrast, the interpretivist research philosophy views knowledge as socially constructed and therefore accepts multiple interpretations and subjective meanings.

Though you shouldn't become too worried about understanding this distinction, it is worth having some understanding of your research philosophy as this is likely to influence your chosen methodology, which will in turn affect the methods you use to collect your data ( more on this later!)  

Adapted from Alkhalil (2016)

Securing ethical approval for your project is a key step in the research process and must be in place before you begin collecting data. Research ethics are a set of rules and criteria that your research project must adhere to in order to protect the welfare of your participants and to ensure the integrity of your data and results. Although it is easy to see ethical approval as a barrier to the research process, it is an important process that encourages you to recognise how your research may impact the welfare and privacy of those involved.

Visit the University’s Ethics and Integrity webpages for information and guidance on Sheffield Hallam’s research ethics policy and ethical approval.

As well as securing ethical approval from the University’s ethics committee, you will also need to think about how you will ensure the data you collect remains private and confidential, and that your participants are fully informed and consent to the terms of your research. You can find a series of templates and forms to use during your research on the University’s ethics pages, includ ing participant information sheets, participant consent forms and documents related to risk assessment.

Check with your supervisor which forms are required as some departments have their own versions of the generic forms above. Aim to start the process early – many projects are delayed while researchers wait for ethical approval; the Student Ethics checklist is a good supporting document to use when planning this aspect of your research.

• Methodology vs. Methods
• Choosing your methods
• Planning your procedure

Methodology is the plan of action for your research. Your choice of methodology will guide the methods you choose and provide a rationale for the design of your research.

Methods are the techniques and procedures that you engage in to collect data. It is important to provide comprehensive detail about your chosen methods; this helps to justify your chosen approach and demonstrate how your chosen method of data collection will enable you to answer your research questions.

Here's an example:

It is important to remember that you should demonstrate awareness of the limitations of both your chosen methodology and methods.

Ultimately, your methodology and methods are about demonstrating a clear justification for the overall design of your research and the methods you employed to collect your data. Furthermore, you need to d emonstrate an understanding of the limitations of your choices and the affect this may have upon your findings/conclusions/implications/claims to generalisability. 

Your research methods are the tools that you will use to collect your data. These can either be quantitative, examining numerical data and using statistical tests to establish relationships, or qualitative, examining non-numerical data to seek an in-depth understanding of phenomena. The decision between quantitative and qualitative methods may be influenced by your methodology.

Your choice of methods will also depend on several other factors such as time, resources and knowledge. For example, whilst interviews allow you to collect very rich data, they are very time consuming to transcribe and analyse. Conversely, surveys may allow you to collect a much larger data set, but it is likely to be lacking in detail. It is important to recognise that there are strengths and weaknesses associated with any research method and it is your responsibility to consider how these factors support or inhibit your ability to answer your research questions.

Whilst not an exhaustive list, some of the most frequently used research methods include:

• Interviews (Structured/Semi-structured/Unstructured)
• Focus Groups
• Secondary Data Analysis
• Questionnaires/Surveys
• Observation (Participant/Non-participant)
• Measurement

If you find yourself stuck when it comes to choosing your research methods, reviewing the related literature can often be a helpful place to start. This is because research on topics related to your own project is likely to have been conducted using well-established research protocols, which are appropriate for studying the topic in question. Furthermore, reviewing the methods sections of related literature can often provide you with a handy guide about what to include in your methodology section when you come to writing up your research project.

Choosing your research methods is often about balancing realism and ambition ; don't be afraid of using your research project as an opportunity to learn how to use a new method, just remember that your project must also be completed within a limited timeframe, so it's important to consider if you have the necessary time and resources/support to develop the knowledge you need to successfully collect data using your chosen method.

It's really important to think about how you're  actually  going to collect your data. For example, if you've chosen to do interviews, you still have to decide on the type of interview, the questions you will ask and how long you want the interview to last. Planning this part of your project requires you to complete reading about your chosen method. This is important for two reasons:

• Reading about your chosen method will help to ensure that you build your chosen method in the best way possible. This will look very different for every research project, and will be dependent on your topic, methodology and the problem/gap you are trying to address. Nevertheless, using literature as a guide will help to ensure that your project meets the standard of 'best practice' for whatever your chosen research method(s) is.
• When it comes to writing up your project, it is important that you can demonstrate a theoretical grounding from the wider literature to support your choice of methodology and method(s).

Deciding on your research participants is a topic that is important to discuss with your supervisor in the early stages of your dissertation project , perhaps even in your first supervision meeting. The sooner you identify your research participants, the sooner you can begin to narrow the scope of your literature search and determine which studies will be most relevant to your aims and objectives. 

This will also help you to begin to sketch out the story of your research - why are you interested in your chosen group, what will participating in your research look like for a participant, and how will they be implicated in your findings? It would be impossible for this guide to cover everything on how to identify, recruit and collect data from your research participants, but here are some key points to consider:  

• Start with the existing literature. If you’re undecided on who your participants should be, start by making notes on existing studies. You might aim to build on existing research - exploring a new variable with a well-researched participant group that you will aim to replicate in your own project. Alternatively, you might be drawn to expand existing research into a new pare by considering participants and populations you feel have been previously overlooked.
• Draw on your networks. Be practical, thinking about potential participants that you can easily access and engage with in your project. These might be coursemates, university students, or communities you have worked with on placement. If you already know your participants, or belong to the group yourself, be sure to consider your positionality and think about the potential for research bias.
• Be realistic about ethical approval. For UG and PGT dissertations, it is important to be realistic about who you will be able to involve in your research, and the unlikelihood that you will have the time to gain ethics approval for working with vulnerable communities or involving participants in sensitive topics. However, this is not to say that your research idea does not have potential, but you may need to think of a group of participants - perhaps one step removed from your topic of interest - that could be involved. For example, any direct work with children, unless you are already undertaking a school-based placement, is very unlikely to be approved. However, you could shift your focus onto parents or teachers. Similarly, sensitive topics such as mental health and disability will be difficult to address directly, but you could choose to interview support workers or university staff on the subject, or write an extended literature review that does not require you to generate primary data from working with participants.
• Read up on selection and sampling techniques. Familiarise yourself with the different ways you can recruit participants to ensure a representative sample. For more information on sampling techniques, and their relative advantages and limitations, visit our SAGE Research Methods resource via the library.
• Think about the logistics of recruiting and gathering data from participants . How will you reach out to participants and are you using multiple methods of communication, or relying entirely on online surveys or email interviews? Some communication methods may be easier for your participants to engage with than others - try to build this into your research design. You will also need to think about how you ensure data is anonymised and how you will keep track of the number of participants involved in your project if they are participating remotely.
• Have a contingency plan. Reflect on the possible points of failure in your project and possible solutions for these. If your online survey fails to attract enough participants, can you run a second phase of data collection in person? What is your minimum number of participants needed to meet your research aims?
• Set yourself a goal. Set an ideal sample size as well as a lower limit. Aim for the minimum in the time you have available - any extra participants would then be a bonus!
• Share your findings . You will need to let your participants know how their data will be stored and how they can access the results of your project once it is completed. You can find guidance on this, and wider GDPR considerations, on the university's ethics pages.

It is important to consider how you will analyse the data you have collected. Furthermore, you should start to think about how the interpretation of your data will start to allow you to answer your research questions.

Your choice of analysis will vary greatly depending on your discipline and on whether you are using quantitative or qualitative research methods. In the case of quantitative research, you need to decide what statistical tests you are going to conduct and if there are any adjustments that you will need to make to avoid Type 1 or Type 2 errors. Likewise, if you are doing qualitative research you need to think about how the coding system that you will use to analyse your data and whether or not you will use any computer software to support your analysis.

Either way, you should ensure that you have the skills that you need to complete your chosen type of analysis or determine what reading/training you need to undertake!  

What is a research proposal used for?

Your research proposal is an important step in the dissertation process as it allows you to determine whether there is an evidence base for your project and a need for your research to be conducted. The proposal allows you to identify a specific area or research problem, and to reflect on the practical steps you will need to complete in order to finish the dissertation. Your proposal should therefore make your research project appear achievable with the time and resources you have available. In some departments, the proposal will also be used to match your dissertation to an appropriate supervisor.

What should I include in the proposal?

Your proposal includes many of the same sections as a dissertation, but of course it is read with the understanding that this is a proposed project and that details may change. Remember, the proposal is about demonstrating that you know what the dissertation process will involve and that you have started to reflect on the practicalities of completing such a project. 

Here are the key sections your proposal should include. Be sure to check this against your assessment criteria or module guide:

Working title Your title should outline a clear topic area and your research approach. Some common techniques include using a question (‘For more tips on what makes an effective title, visit this online guide.

Background and research aims Introduce your topic area, including definitions if helpful and appropriate. You should also include a bullet-point list of your research objectives (2-4 is a good number to include) or questions that you will aim to answer. It can also be helpful to include a short paragraph outlining what you hope to achieve and contribute to knowledge with your dissertation.

Literature review You should conduct a short literature review of around 750-1000 word that includes the following three sections:

• Background information on your topic - Define key terms, signpost any issues or debates in the literature, introduce the research problem or question in its broadest terms.
• Trends in the literature - Highlight key trends in existing research – summarise the main theories or concepts in the literature in your area. Situate your project in relation to these.
• Identify a gap or research problem - Provide more detailed information on a focused aspect of the topic that your research will address. Identify the gap or show specifically what your research hopes to contribute – either for your participants, a theoretical development or a new methodological approach.

Methodology This will be a brief outline of your intended methods and procedure for data collection. This should be in the future tense and use cautious language where appropriate. Aim to include:

• your overall methodology (quantitative/qualitative) and research design (case study, pilot study, experimental design);
• your research methods and why they are appropriate for your proposed project ;
• identify a participant group and consider how they will be recruited, along with approach to sampling;
• how you intend to analyse the data and any tools/software required to complete this step;
• acknowledge that you will obtain ethical approval for the study and address any ethical considerations you must take at this stage.

Research schedule (optional – check with your module leader) Outline key milestones in your project and identify short and medium-term deadlines. This could be presented in a table, as a monthly schedule or using a Gantt chart.

Bibliography Make sure you include a list of the references used in your research proposal, in APA format. This will not be included in the word count for the proposal.  

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Welcome to the Biostatistics and Design Program

The BDP is a fee-for-service center that provides study design and statistical analysis support to the OHSU research community. We help researchers select the most appropriate study design to align with their research questions. Learn more about the BDP

The Biostatistics and Design Program (BDP) is a University Shared Resource Core that collaborates with investigators across OHSU and beyond on questions of study design and analysis. We work with investigators through fee-for-service arrangements, and additionally offer advice sessions free of charge. Contact us to discuss your needs – we can make a customized recommendation.

We have close ties with the Biostatistics, Epidemiology, and Research Design (BERD) program, a unit within the Oregon Clinical & Translational Science Institute , OHSU’s CTSA. While these two programs have overlapping goals and common team members, the primary distinction is that BERD facilitates research through training opportunities and mentoring, while BDP assists in carrying out this research through collaborative arrangements.

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BERD sponsors seminars on topics of high need to the research community. We hope to see you at one of our upcoming seminars!

We are experts in study design and encourage researchers to consult with us in the planning phases of research. As the design of a study is linked with the analysis of the data, researchers can benefit greatly from involving a biostatistician early, starting in the design phase of the work.

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May 1, 2024 | Olivia Drake - UConn College of Engineering

Engineering Students Share Yearlong Research Projects During Senior Design Demo Day

Through their Senior Design projects, students work to solve real-world engineering problems while learning valuable skills

More than 240 teams from the College of Engineering participated in Senior Design Demo Day on April 26. (Chris LaRosa / UConn)

While chemical engineers may more commonly be known for working in areas of pharmaceutical development, materials processing, and petroleum industries, Kanisha Desai ’24 (ENG) is brewing up her own innovative idea for putting her chemical engineering degree to use.

Desai, along with engineering classmates Cameron Hubbard ’24 (ENG), Hailey Tam ’24 (ENG), and Ethan Krouskup ’24 (ENG), debuted their project—a non-alcoholic beer brewing process—during Senior Design Demonstration Day on April 26 in an energy-buzzed Gampel Pavilion. ( View the photo gallery online here .)

“We wanted to solve a problem that most people wouldn’t normally classify as an ‘engineering problem,’” Desai says. “Brewing has always been a fascinating topic to us as chemical engineers, and since many people love the taste and creative flavors of craft beers, but don’t want the added alcohol, this project allows us to help small breweries develop a thriving alcoholic and non-alcoholic beer brewing business.”

The team’s project, “ Spirit of Sobriety: Of Non-Alcoholic Brews ,” was among 242 student-led endeavors showcased during the 2024 Senior Design Demo Day. Sponsored by the College of Engineering (CoE) and under the mentorship of Associate Professor in Residence Jennifer Pascal, the project took first place of all senior designs from the Chemical and Biomolecular Engineering Department.

Senior Design is two-semester capstone course where faculty and industry engineers mentor students as they work to solve real-world engineering problems for university and company sponsors. Through the experience, students learn about the principles of design, how ethics affect engineering decisions, and how professionals communicate ideas. In addition, they acquire valuable teamwork skills and professional skills while interacting with industry professionals and other mentors.

“Each year, dozens of leading manufacturing companies, pharmaceutical and medical firms, consulting practices and utilities present the College of Engineering with design challenges or problems they are encountering in their business,” explains CoE Dean Kazem Kazerounian. “For a modest fee, the companies suggest a particular problem and our senior engineering students, under the joint mentorship of engineering faculty and practicing experts from the sponsoring entities, work to properly frame the problem and develop meaningful solutions.”

Senior Design Demo Day provides the soon-to-be UConn graduates an opportunity to share the results of their independent research projects with fellow students, faculty, alumni, and community members.

“For our students, this experience is the culmination of their undergraduate education, and an opportunity to showcase their skills and education as they venture into the next steps of their careers,” says Daniel Burkey, associate dean for undergraduate education and Castleman Term Professor in Engineering Innovation. “Even after Demo Day, some students continue working on their project, especially if they accept a job with their project sponsor.”

While the “Spirit of Sobriety” team also implemented a pasteurization process on a home-brewing scale to ensure the safe drinkability of the non-alcoholic beer, materials science and engineering majors Charlotte Chen ’24 (ENG), Sanjana Nistala ’24 (ENG), Jenna Salvatore ’24 (ENG), and Allison Determan ’24 (ENG) designed a “ Joint-On-A-Chip ” to emulate the in vivo environment of a knee joint affected by osteoarthritis. The chip mimics the immune response and mechanical strain that cells in an affected joint experience in the human body.

Through their Senior Design project, “ Deblurring of Digital Images ,” electrical and computer engineering majors Andrew Feliciano ’24 (ENG) and Colby Powers ’24 (ENG) evaluated blur reduction or removal algorithms that could be implemented on imaging systems found on United States Coast Guard ships and naval vessels.

And Gary Zhu ’24 (ENG), Jack Crocamo ’24 (ENG), Ryka ChandraRaj ’24 (ENG), Alicia Chiu ’24 (ENG), Ryan Mercier ’24 (ENG), and Donny Sauer III ’24 (ENG) completed a systems engineering project titled, “ Data Collection and Analysis for an Autonomous Electric Vehicle System .” With the support of sponsor Pratt & Whitney, the team developed a data analysis framework capable of precisely predicting a self-driving vehicle’s reactions to input directives. The foundation of this initiative rests upon a data-driven control system tailored for electric vehicles, harnessing the power of machine learning algorithms.

Solving Problems Statewide

One of the goals of Senior Design is to help solve problems on a local level.

In Madison, Conn., the Connecticut Department of Transportation wants to expand a rest stop along the heavily traveled Interstate 95. Environmental engineering majors Rory Cavicke ’24 (ENG), Kelsey DiCesare ’24 (ENG), and Alexander Brita ’24 (ENG) worked with industry sponsor CHA Consulting to design a septic system and stormwater infrastructure for an expanded tractor trailer rest stop. The team developed their designs in accordance with the CT Public Health Code 2023 Technical Standards and the CT Stormwater Quality Manual.

And in Woodstock, residents are working to restore and preserve the historic Chamberlin Mill, which produced wood shingles in the 19th and early 20th centuries. For their senior design project, mechanical engineering majors Alexander Guzman ’24 (ENG), Will Goss ’24 (ENG), and Vinicius De Souza ’24 (ENG) conducted a mechanical analysis and working CAD model of the mill’s 1860s shingle machine , which will be used by the mill to teach future STEM students.

Catalyzing Campus

Other projects focused on benefiting UConn itself.

Under the guidance of faculty advisor Shinae Jang, civil engineering majors Joshua Maccione ’24 (ENG), Christian Maignan ’24 (ENG), Connor Behuniak ’24 (ENG), Ryan Baj ’24 (ENG), and Darren Lin ’24 (ENG) designed a multi-story, modernized building to accommodate the expanding engineering programs within the newly designated College of Engineering. The team obtained geotechnical data from past construction projects and identified an optimal new location for this proposed facility on campus. The design incorporated composite and non-composite beams, along with a combination of steel and braced frames. Their project, “ Proposed College of Engineering Building at the University of Connecticut ,” took second place of all civil engineering senior designs.

Also, mechanical engineering majors Christian Bjork ’24 (ENG), Alanna Barzola ’24 (ENG), and Nicholas Trottier ’24 (ENG), along with electrical engineering majors Patrick Place ’24 (ENG) and River Granniss ’24 (ENG), collaborated on the design, development, and analysis of a scaled-down, concentrated photovoltaic/thermal system (CPV/T) that could be integrated into a greenhouse roof at UConn. Photovoltaic and thermal systems are considered conventional green energy methods used to power a greenhouse, however combining them is relatively new concept.  Because photovoltaic systems can become inefficient when they reach high temperatures, for this project, the team proposed cooling the photovoltaic system with a combined thermal system while simultaneously producing thermal energy to heat the greenhouse.

Their project, “ Design and Development of PV/Thermal System for Greenhouses ” was advised by Wajid Chishty, Nathan Lehman, and Ravi Gorthala and sponsored by Sonalysts, Inc. It received first place in systems engineering projects and third place in mechanical engineering project.

For Grannis, the senior design process proved to be challenging, but rewarding. With his electrical engineering knowledge, Grannis was tasked with making the system’s sun tracking device operate correctly, in a minimal amount of time.

“The tracking system design we ended up using was not finalized until about a month into the second semester of senior design. After that, I spent all of my time working on the electronics and software for the tracking system pretty much until Demo Day,” Grannis says. “The biggest thing I learned was coding in C++ for Arduino. In many cases the hardest parts of the project were not the most interesting to present, so learning to show off what is interesting while continuing to work on the hard stuff—while also informing sponsors and advisors about what difficulties there are—is a balance that needs to be found early on. The most important thing Senior Design reinforced is how important interpersonal communication is, even in engineering where things are heavily results-driven.”

A Little Competition …

Demo Day isn’t the only venue students share their novel projects. For Senior Design, Ashley Sciacca ’24 (ENG), Nathan Garala ’24 (ENG), Ryan Maguire ’24 (ENG), and Spencer Alsup ’24 (ENG) fabricated a fully electric-powered, waterproof boat . Along with other members of UConn’s Promoting Electric Propulsion team— Christopher Capozzi, Andrews Marsigliano, Ian Pichs, and Xavier Purandah—the group competed in a five-mile course in Virginia, sponsored by the American Society of Naval Engineers. Students designed the boat using a simulation software and combined this data with test results to determine power requirements.

“This was the first year of competition for the UConn team, and of 39 schools, we finished in the top 10, which is a great accomplishment,” said project advisor Vito Moreno, professor in residence of mechanical engineering.

Similarly, electrical and computer engineering majors Matthew Silverman ’24 (ENG), Spencer Albano ’24 (ENG), and Nicholas Wycoff ’24 (ENG) participated in a Software Defined Radio (SDR) university challenge in Ohio with their Senior Design project, “ Physical Layer Network Slicing .” They created an access point that can establish a network and communicate across both Wi-Fi and Zigbee (a Wi-Fi alternative) devices. The competition, hosted by the Wright Brothers Institute (WBI) and Air Force Research Laboratory, encouraged hands-on skill building and explore experimentation through SDR hardware. UConn’s team was among the top 8 finalists and received the Most Outstanding Project Award. Shengli Zhou, professor of electrical and computer engineering, served as the team’s advisor.

“There are some routers that can communicate over both Wi-Fi and Zigbee but are typically two separate devices bundled in the same enclosure,” Albano explains. “Having one device that communicates across both standards provides ease to a network administrator that can manage devices in both standards. The benefits include efficiency, flexibility, and security.”

And the Winners Are …

Senior Design Demo Day began more than 40 years ago. Today, it features the projects of students majoring in biomedical engineering, chemical and biomolecular engineering; civil and environmental engineering; electrical and computer engineering; environmental engineering; materials science and engineering; systems engineering; management and engineering manufacturing; multidisciplinary engineering; the School of Computing; and the School of Mechanical, Aerospace, and Manufacturing Engineering.

Each CoE department and school awarded prizes for the best poster presentations. The 2024 winners are:

Biomedical Engineering

1st place: “Joint-On-A-Chip Osteoarthritis Disease Modeling for Evaluating Anti-Inflammatory Drug Performance,” by Charlotte Chen (MSE), Sanjana Nistala, Jenna Salvatore, and Allison Determan. Advisor: Syam Nukavarapu. Sponsor: UConn Biomedical Engineering Department.

2nd place: Singular Part 3D-Printed External Prosthetics for Mastectomy Patients Without Reconstruction,” by Yukti Ummaneni, Ashwini Patel, Mia Haynes, and Jamie Trinh. Advisor: Liisa Kuhn. Sponsor: Beekley Lab for Biosymmetrix

3rd place (tie): “Circuit and Sensor Design for Smartphone-Based Electroretinography,” by Rory Harris, Rodrigo Tuesta, and Yuexi Hao. Advisor: Hugo Posada-Quintero. Sponsor: UConn Biomedical Engineering Department.

3rd place (tie): “In Vitro Model for the Study of Traumatic Brain Injury” by Mark Cristino, Rudin Lloga, and Kaiya Pringle. Advisor: Kazunori Hoshino. Sponsor: UConn Biomedical Engineering Department.

Chemical and Biomolecular Engineering 1st place: “Spirit of Sobriety: Of Non-Alcoholic Brews,” by Cameron Hubbard, Kanisha Desai, Hailey Tam, and Ethan Krouskup. Advisor: Jennifer Pascal. Sponsor: UConn College of Engineering.

2nd place: “Design And Optimization Of A Multi-Effect Desalination Unit Integrated With A Gas Turbine Plan,” by Wasif Zaman, Katelyn Honegger, Alanna Smith, and David Gan. Advisor: Burcu Beykal. Sponsor: UConn College of Engineering.

3rd place: “Redefining How to Process Body Wash: Creating A More Efficient and Agile Supply Chain,” by Aadil Shahzad, Samantha Miel, Megan Shiring, and Matthew Silver. Advisor: Anson Ma. Sponsor: Unilever.

Civil Engineering 1st place: “Blue Line Extension,” by Anson Lau, Yuanlong Dai, Helen Pruchniak, Nicholas Vestergaard. Advisor: Wei Zhang. Sponsor: Construction Industries of Massachusetts-Labor Relations Division (CIM-LRD).

2nd place: “Proposed College of Engineering Building at the University of Connecticut,” by Joshua Maccione, Christian Maignan, Connor Behuniak, Ryan Baj, and Darren Lin. Advisor: Shinae Jang. Sponsor: Slam Collaborative.

3rd place (tie): “Design of Pedestrian Walkway For The Gold Star Memorial,” by Shaun McGuire, Kayla Turner, Steven Anderson, Juan Javier Mejia. Advisor: Manish Roy. Sponsor: HNTB Corporation.

3rd place (tie): “Worcester Union Station Center Island Platform Project,” by Conor Murphy, Harley Jeanty, Jakub Patrosz, Benjamin Ragozzine. Advisor: Wei Zhang. Sponsor: HDR, Inc.

Environmental Engineering

1st place: “Remedial Design of a PFAS Contaminated Site in Connecticut,” by Valentine Falsetta, Wilmalis Rodriguez, and Nicola Bacon. Advisor: Alexander Agrios. Sponsor: Amine Dahmani.

2nd place: “Stormwater/Septic Design,” by Rory Cavicke, Kelsey DiCesare, and Alexander Brita. Advisor: Alexander Agrios. Sponsor: CHA Consulting, Inc.

3rd place: “Stones Ranch Road Drainage Upgrades and Erosion Control,” by Grace Carravone, Amanda Jacobson, Sara Makula, and Jason Contreras. Advisor: Manish Roy. Sponsor: Connecticut National Guard.

School of Computing 1st place: “Solubility Data Management,” by John Bogacz, Connor Brush, Maniza Shaikh, Jianhua Zhu, Walson Li, and Peter Filip. Advisor: Qian Yang. Sponsor: Boehringer Ingelheim.

2nd place: “Light Scattering Automation,” by Zachary Hall, Nikolas Anagnostou, Alden Dus, Jacob Montanez, Avaneesh Sathish, Zakarya Zahhal, and Nikolas Kallicharan. Advisor: Qian Yang. Sponsor: UConn School of Computing.

3rd place: “Responsive Multimodal Care Coordinator (MCC) Development,” by Randy Yu, James Frederick, Betul Agirman, Cameron Ky, Quincy Miller, and Mir Zaman. Advisor: Suining He. Sponsor: University of Connecticut and Bastion.

Electrical and Computer Engineering Projects 1st place: “Robotic Perception Sensor Characterization Platform,” by Hritish Bhargava and Samuel Gresh. Advisor: Shan Zuo. Sponsor: Draper Laboratory​.

2nd place: “Air Force Research Laboratory Software Defined Radio (SDR) University Challenge: Physical Layer Network Slicing,” by Spencer Albano, Matthew Silverman, and Nicholas Wycoff Advisor: Shengli Zhou. Sponsor: UConn Electrical and Computer Engineering Department.

3rd place: “Automated Angle Table for AS5,” by Alexander ReCouper and Mitchell Bronson. Advisor: Liang Zhang. Sponsor: OEM Controls.

Materials Science and Engineering 1st place and Student Choice Award (tie): “Joint-On-A-Chip Osteoarthritis Disease Modeling for Evaluating Anti-Inflammatory Drug Performance,” by Charlotte Chen, Sanjana Nistala, Jenna Salvatore, and Allison Determan. Advisor: Fiona Leek. Sponsor: UConn Biomedical Engineering Department.

2nd place and Student Choice Award (tie): “Citric Acid Passivation Process Development,” by Kevin Li and Matthew Maramo. Advisor: Alexander Dupuy. Sponsor: ARKA.

3rd place: “Bio-Based Material Commercial Door Components Footprint,” by Yuexuan Gu and Jaclyn Grace. Advisor: Fiona Leek. Sponsor: ASSA ABLOY.

Management and Engineering for Manufacturing 1st place: “Enhancing Smartfood Popcorn Line Efficiency to Reduce Downtime And Boost Production Performance,” by Anna Lidsky, Valeria Nieto, Isabelle Bunosso, and Lauren Hart. Advisor: Craig Calvert. Sponsor: PepsiCo Frito-Lay.

2nd place: “Modernizing Raw Material Marking and Inventory System To Enhance Traceability,” by Nimai Browning, Quinn Reelitz, Steven Jaret, and Austin Muzzy. Advisors: Craig Calvert and Rajiv Naik. Sponsor: HORST Engineering.

3rd place: “Reliability Testing and Design Risk Assessment to Enhance Product Quality and Business Sustainability,” by Alex Domingo, Madeline Corbett, Brett Pierce, and Alexander Pearl. Advisor: Rajiv Naik. Sponsor: Belimo Americas.

School of Mechanical, Aerospace, and Manufacturing Engineering Professors Award: “Designing and Operating An Experimental Facility To Study Non-Premixed Flames Of Pre-Heated (And Pre-Vaporized) Reactants,” by Al-Yaman Zoghol and Tyler Dickey. Advisor: Francesco Carbone. Sponsor: UConn College of Engineering.

1st place: “Multifunctional Metamaterial to Attenuate Acoustic and Elastic Waves,” by Evan Kluge and Lindsey Japa. Advisor: Osama Bilal. Sponsor: ACC Masters.

2nd place (tie): “Improved Performance of Magnetic Speed Sensor Analyzer,” by Kristen Angeli and Emily Root. Advisor: Farhad Imani. Sponsor: AI-Tek Instruments.

2nd place (tie): “Belt Based Continuously Variable Automatic Transmission Prototype,” by Ajeeth Vellore, Luka Ligouri, Ethan Wicko, and Ryan Zwick. Advisor: David Pierce. Sponsor: Transcend Bicycle LLC.

3rd place: “Design and Development of PV/Thermal System for Greenhouses,” by Christian Bjork, Alanna Barzola, Nicholas Trottier, Patrick Place and River Granniss. Advisors: Wajid Chishty, Nathan Lehman, and Ravi Gorthala. Sponsor: Sonalysts, Inc.

Systems Engineering 1st place (tie): “Robotic Perception Sensor Characterization Platform,” by Isabella Fabrizi, Liam Mohan, Samuel Gresh, Aveline Mills, Gerardo Robles-Luna, and Hritish Bhargava. Advisor: Osama Bilal. Sponsor: Draper.

1st place (tie): “Design and Development of PV/Thermal System for Greenhouses,” by Christian Bjork, Alanna Barzola, Nicholas Trottier, Patrick Place and River Granniss. Advisors: Wajid Chishty, Nathan Lehman, and Ravi Gorthala. Sponsor: Sonalysts, Inc.

Multidisciplinary Engineering In addition to the Demo Day awards, six seniors were honored for being among UConn’s first multidisciplinary engineering majors: Edward Wilkinson, Matthew Koniecko, Sean Tan, Patricio Salomon-Mir, Josephine Luby, and Kelly Russell.

Distinguished Educator Engineering Award (nominated by students) Jasna Jankovic, associate professor of materials science and engineering, and Manish Roy, assistant professor in residence of civil and environmental engineering.

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• University of Wisconsin-Madison

Undergrad’s ambitious research project produces novel haptic glove design

Departments:, focus areas:.

As a high school student in the San Francisco Bay Area during COVID pandemic lockdowns, Ben Levy had a lot of free time on his hands while being stuck at home. To combat his boredom, he decided to try to build a humanoid robot in his family’s garage.

“I had an Arduino kit, which has simple microcontrollers, and a bit of experience using it at a summer camp,” Levy says. “I thought it would be a fun challenge to see what I could build.”

Ultimately, he created a rudimentary gesture device that resembles a robotic hand. His setup involved wearing sensors on one of his hands, allowing the robot hand to mimic his gestures.

Later, as a mechanical engineering freshman at the University of Wisconsin-Madison, he took ME 201: Introduction to Mechanical Engineering , and stopped by Assistant Professor Michael Wehner ’s office hours to discuss an idea related to the course’s hands-on design project. The conversation eventually moved on to Wehner’s research, which is focused on robotics, machine interaction and soft systems.

“With my growing interest in robotics, I found Professor Wehner’s research really exciting,” Levy says. “I showed him a video demo of the humanoid robot I built in high school, and he offered me an opportunity to work in his research lab.”

With Wehner’s mentoring, Levy wanted to build a haptic glove for virtual reality that not only could be used as a controller in a video game, but also allow users to “feel” virtual objects as they played.

Levy teamed up with mechanical engineering graduate student Megh Doshi , a member of Mechanical Engineering Associate Professor Michael Zinn ’s research group, for the project. For their prototype, they focused on developing a “layer jammer” device to serve as the actuator for haptic feedback in the glove. To make it, they stacked sheets of paper and put them inside a plastic bag. Applying a vacuum to the sealed bag compresses the paper and makes it stiff . Removing the vacuum returns the device to its original soft, flexible state.

Levy says the simplicity of their layer jammer makes it far cheaper and more user friendly than the very expensive actuators used in commercial virtual reality gloves, which use complicated designs and control methods.

“The layer jammer offers a very cheap way to transition between high transparency, where it feels like nothing is stopping your finger, to high impedance, where it feels like you’re touching something hard,” Levy says.

To start, Levy and Doshi had to figure out a way to consistently manufacture the layer jammers so they’d operate reliably. Levy says this was a surprisingly complex challenge, which involved trying to find ways to maintain the highest level of vacuum.

Next, they performed thorough characterization of the devices, evaluating key parameters so they could be designed into many different wearables. As a freshman new to engineering, Levy says this characterization work had a big learning curve. “Getting reliable data from testing the devices was a huge challenge and the most difficult engineering problem I faced with this project,” he says.

Levy and Doshi persevered, and once they managed to get reliable data, they focused on building the glove based on the key parameters they identified. Levy took the lead on building the glove, with the goal of integrating the layer jammers so that they would conform well to the hand. To achieve this, he designed a base plate and mounted the jammers on it. Making the glove required some sewing skills as well.

“I called my mom to ask her for some sewing tips and also watched some sewing tutorials online,” Levy says. “Building the glove was a blast, and this was the part of the project that I enjoyed the most.”

Lastly, Levy created a video game environment using Unity software. Wearing the glove, he could control a virtual hand in the game and actually feel and see a virtual ball in a live video game environment .

The duo submitted their work to the IEEE Haptics Symposium 2024, which accepted their paper. Doshi presented the research at the conference.

“Having a paper accepted to a conference is a great accomplishment for any undergraduate, but it was particularly inspiring for a freshman,” Wehner says. “Ben is a very talented student and I’m impressed by his work.”

Levy, who is now a sophomore, says this hands-on research project was a wonderful learning experience that helped deepen his understanding of concepts in his engineering courses. For example, he entered his mechanics of materials course with an already strong understanding of beam deformation due to his work on this project.

“I’m very grateful to Professor Wehner for giving me the opportunity and the flexibility to pursue this project and help guide the creative direction. He has been fantastic to work with,” Levy says. “This experience has definitely confirmed that engineering is what I want to do.”

Featured image caption: Mechanical engineering sophomore Ben Levy makes an adjustment to his haptic glove. Credit: Joel Hallberg .

Layer Jammers in a Simulated Environment Soft Haptic (S.E.S.H.) Glove

Layer jammer demo with weight, layer jammer in curved position demo.

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Roaring creativity: UNI students embellish TC statues for community pride project

You’ll soon begin to see more than two dozen anthropomorphic Panther statues — six feet tall and weighing 65 to 70 pounds each — around the Cedar Valley. These  Panthers on Parade are the result of an effort spearheaded by Cedar Falls Tourism & Visitors Bureau, in partnership with the University of Northern Iowa. Artists with a UNI, Cedar Falls, Cedar Valley or Iowa connection submitted designs to embellish the fiberglass statues of UNI’s mascot TC and paired with local businesses to bring their designs to life. 

UNI students working in the  Public Art Incubator are among the artists behind the TC designs. 

“As someone who wants to work in art and in public art, it seemed like a no-brainer to take advantage of this opportunity, and especially being a Cedar Falls resident and being familiar with the area, it just made sense,” said  Amelia Gotera , a senior pursuing a Bachelor of Fine Arts in Studio Art with an emphasis in sculpture. 

Gotera embellished two sculptures. One is a fully holographic vinyl-covered Panther. 

“I was thinking about how people want something that is Instagrammable that people are going to be curious about, have questions about, that's approachable and people want to take pictures with,” Gotera explained. “So, for me, it made sense to come up with something really eye-catching and beautiful. I think it's aesthetically something that's unique. There aren’t holographic sculptures all over town.”

Before Panthers on Parade, Gotera did not have much experience working with fiberglass or vinyl. She also hadn’t painted much in past projects at the Public Art Incubator. As part of the process, she had to research the materials she was using to ensure they would be UV-friendly and waterproof, as the sculptures will be displayed outside for several months.

“It's been fun to branch out into these other materials and deepen my tool belt,” she said.

Although there were many late nights alone in the Public Art Incubator, Gotera believes the project was well worth it.

“It's meaningful for anyone to be able to leave a visual marker saying, ‘I was here,’” said Gotera. “For me, public art, while it's a job, it's really about imagining the experience of the audience and thinking about what happens after I've left it there.”

From February to April,  Rachel Heine , a UNI senior majoring in graphic design, was also hard at work in the Public Art Incubator, embellishing two TC sculptures of her own. “I was really excited when I found out two of my designs had been chosen,” said Heine. “It felt like a big community project, something that will be seen by a lot of people and just something completely different than what I've worked on before. So I was really excited to learn a bunch and then have something that will be displayed in Cedar Falls.”

Much like Gotera, working on the TCs gave her experience with mediums she does not typically work with such as resin, fiberglass and paint. Through the experience of working on Panthers on Parade, Heine became more comfortable with all of these mediums. She enjoyed that unlike many of her projects with the Public Art Incubator, she had more control over the finished product.

“It was very freeing,” she said. “It makes me feel confident in my abilities as an artist that I was able to come up with the idea and then see it through to the final sculpture.”

With past projects, Heine’s work in the Public Art Incubator has gone all across the state, but it’s especially meaningful for a project to end up in the Cedar Valley, which has been her home during her college years. 

“It really, really motivates me to do my best on it just because I want  people to look at it and be impressed, and I also want to be proud of the work that I do,” she said. “So definitely, that is a big motivating factor.”

To learn more, visit  cedarfallstourism.org/panthers-on-parade/

See the big reveal of Panthers on Parade.

Behind the scenes of Panthers on Parade

Panthers on Parade installation underway

Meet the spring 2024 Panther grads

“Baddest Cats” gives more than $8,300 back to UNI students

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Operations and Programs Manager at Center for Health Design

Operations and Programs Manager – Remote

Do you want to help lead a dynamic, mission-driven team that is passionate about improving the healthcare experience for patients, their families and staff?

For over 30 years the non-profit Center for Health Design has been providing research, education and community-building to improve health, safety and business outcomes through the use of an evidence-based process in the planning, design and construction of healthcare environments.

Were looking for an Operations and Programs Manager who can keep one eye on the present overseeing the day-to-day work of the project management and administrative teams and office operations and another eye on the future, working closely with the CEO and management team to translate and operationalize high-level vision, goals and strategy into actionable plans and measurable results.

At The Center, we thrive on creativity, collaboration and innovation and have created a dynamic work culture where your contributions make a real difference. We seek someone who demonstrates a proactive and uplifting attitude, fosters a positive work environment, and contributes to a collaborative and motivated team culture.

This is a remote position.

Responsibilities

Project Planning, Management, Reporting

The Operations and Programs Manager is responsible for overseeing the planning, implementation, progress tracking, quality control, measuring and reporting of all Center programs and events in coordination with designated project managers.

Specifically, the Operations and Programs Manager will be responsible for

• Defined project scope and objectives, including revenue or other quantifiable goals
• Budget/resource requirements (internal and external)
• Project team members, roles and responsibilities
• Key progress milestones and deadlines
• Quality control measures
• Success metrics
• Setting clear expectations for and driving timely completion, quality execution and goal achievement of all projects, programs and events.
• Managing, supporting and mentoring our project management team for success.
• Providing direction, guidance, assistance, task/work support, and encouragement to project managers in executing their projects, includingwith input and direction from the management teamthe development of annual plans and goals.
• Regularly reviewing project progress in project manager group, project team and individual manager meetings, intervening and assisting as needed to resolve time, budget, resources, staff and other conflicts or issues.
• Creating and maintaining systems, processes, and tools including a master project calendar for achieving project management goals and driving continual process improvement to increase the effectiveness of the project and administrative teams.
• Communicating project management and administrative updates, issues, and needs to the CEO and management team with recommendations for improvement/resolution.

Strategy Translation, Communication and Implementation Management

The Centers CEO and management team are engaged in an ongoing process of defining and refining the organizations vision and strategy in response to the ever-changing healthcare landscape, as well as challenges and opportunities that arise with our many and varied partners, and in the general industry marketplace. The Operations and Programs Manager plays a key role in operationalizing our evolving vision and strategy.

Specifically, in collaboration with the CEO and management team, the Operations and Programs Manager will:

• Assume the responsibilities of project manager to implement and operationalize the strategy, driving tasks, responsibilities and timelines.
• Actively participate in management team strategy planning and discussions, providing feedback and recommendations.
• Translate organizational strategies and goals into actionable plans.
• Ensure strategies are integrated and reflected across the organization and in relevant Center programs, products, events, processes and procedures.
• Communicate strategies, implementation plans and progress to project management and administrative teams.

Operations Management

The Operations and Programs Manager is responsible for a number of operational tasks, including overseeing office operations, human resources, budget planning, and financial reporting.

• Maintaining communication with contractors and vendors for services needed.
• Coordinating with the Office Manager on office procedures and needs.
• Tracking staffing performance and requirements, hiring new employees as needed.
• Overseeing program budgets and variances, ensuring operational activities remain within budget.
• Managing the implementation of partner agreements across programs, ensuring they are completed and match up with financial records.

Basic Qualifications

Experience and Education:

• Minimum of three to five years of experience and a background in strategy, planning, and/or business operations.
• Experience in managing complex, strategic projects.
• Proven track record of managing staff to their best potential, both in-person and remotely.
• Strong organizational and communication skills.
• Preferable background in healthcare or design.
• Bachelors or advanced degree preferred.

Skills and Attributes:

• Demonstrated ability to identify operational issues and develop appropriate action plans from multidisciplinary perspectives.
• Proven leadership skills, including influencing, efficiency, candor, and openness with a focus on results.
• Knowledgeable about project management processes, tools, techniques, and methodologies to lead large-scale efforts.
• Strong interpersonal skills, especially regarding oversight and management.
• Comfortable with presentation skills, with experience presenting to executive-level leaders.
• Skilled in collaboration, conflict resolution, group interaction/dynamics, management, and project management.
• Preferred familiarity with non-profit organizational structure.
• Strong attention to detail.
• Ability to communicate well in writing, strong proofing, editing, and quality control work.
• Candidates with familiarity with eRA Commons, ASSIST, and SAM a plus.
• Medical insurance
• Dental Insurance
• Vision Insurance
• Life insurance
• Paid time off
• 401(k) matching

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Computer Science > Data Structures and Algorithms

Title: teaching algorithm design: a literature review.

Abstract: Algorithm design is a vital skill developed in most undergraduate Computer Science (CS) programs, but few research studies focus on pedagogy related to algorithms coursework. To understand the work that has been done in the area, we present a systematic survey and literature review of CS Education studies. We search for research that is both related to algorithm design and evaluated on undergraduate-level students. Across all papers in the ACM Digital Library prior to August 2023, we only find 94 such papers. We first classify these papers by topic, evaluation metric, evaluation methods, and intervention target. Through our classification, we find a broad sparsity of papers which indicates that many open questions remain about teaching algorithm design, with each algorithm topic only being discussed in between 0 and 10 papers. We also note the need for papers using rigorous research methods, as only 38 out of 88 papers presenting quantitative data use statistical tests, and only 15 out of 45 papers presenting qualitative data use a coding scheme. Only 17 papers report controlled trials. We then synthesize the results of the existing literature to give insights into what the corpus reveals about how we should teach algorithms. Much of the literature explores implementing well-established practices, such as active learning or automated assessment, in the algorithms classroom. However, there are algorithms-specific results as well: a number of papers find that students may under-utilize certain algorithmic design techniques, and studies describe a variety of ways to select algorithms problems that increase student engagement and learning. The results we present, along with the publicly available set of papers collected, provide a detailed representation of the current corpus of CS Education work related to algorithm design and can orient further research in the area.

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