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One of the hardest parts of writing a research paper can be just finding a good topic to write about. Fortunately we've done the hard work for you and have compiled a list of 113 interesting research paper topics. They've been organized into ten categories and cover a wide range of subjects so you can easily find the best topic for you.

In addition to the list of good research topics, we've included advice on what makes a good research paper topic and how you can use your topic to start writing a great paper.

What Makes a Good Research Paper Topic?

Not all research paper topics are created equal, and you want to make sure you choose a great topic before you start writing. Below are the three most important factors to consider to make sure you choose the best research paper topics.

#1: It's Something You're Interested In

A paper is always easier to write if you're interested in the topic, and you'll be more motivated to do in-depth research and write a paper that really covers the entire subject. Even if a certain research paper topic is getting a lot of buzz right now or other people seem interested in writing about it, don't feel tempted to make it your topic unless you genuinely have some sort of interest in it as well.

#2: There's Enough Information to Write a Paper

Even if you come up with the absolute best research paper topic and you're so excited to write about it, you won't be able to produce a good paper if there isn't enough research about the topic. This can happen for very specific or specialized topics, as well as topics that are too new to have enough research done on them at the moment. Easy research paper topics will always be topics with enough information to write a full-length paper.

Trying to write a research paper on a topic that doesn't have much research on it is incredibly hard, so before you decide on a topic, do a bit of preliminary searching and make sure you'll have all the information you need to write your paper.

#3: It Fits Your Teacher's Guidelines

Don't get so carried away looking at lists of research paper topics that you forget any requirements or restrictions your teacher may have put on research topic ideas. If you're writing a research paper on a health-related topic, deciding to write about the impact of rap on the music scene probably won't be allowed, but there may be some sort of leeway. For example, if you're really interested in current events but your teacher wants you to write a research paper on a history topic, you may be able to choose a topic that fits both categories, like exploring the relationship between the US and North Korea. No matter what, always get your research paper topic approved by your teacher first before you begin writing.

113 Good Research Paper Topics

Below are 113 good research topics to help you get you started on your paper. We've organized them into ten categories to make it easier to find the type of research paper topics you're looking for.

Arts/Culture

• Discuss the main differences in art from the Italian Renaissance and the Northern Renaissance .
• Analyze the impact a famous artist had on the world.
• How is sexism portrayed in different types of media (music, film, video games, etc.)? Has the amount/type of sexism changed over the years?
• How has the music of slaves brought over from Africa shaped modern American music?
• How has rap music evolved in the past decade?
• How has the portrayal of minorities in the media changed?

Current Events

• What have been the impacts of China's one child policy?
• How have the goals of feminists changed over the decades?
• How has the Trump presidency changed international relations?
• Analyze the history of the relationship between the United States and North Korea.
• What factors contributed to the current decline in the rate of unemployment?
• What have been the impacts of states which have increased their minimum wage?
• How do US immigration laws compare to immigration laws of other countries?
• How have the US's immigration laws changed in the past few years/decades?
• How has the Black Lives Matter movement affected discussions and view about racism in the US?
• What impact has the Affordable Care Act had on healthcare in the US?
• What factors contributed to the UK deciding to leave the EU (Brexit)?
• What factors contributed to China becoming an economic power?
• Discuss the history of Bitcoin or other cryptocurrencies  (some of which tokenize the S&P 500 Index on the blockchain) .
• Do students in schools that eliminate grades do better in college and their careers?
• Do students from wealthier backgrounds score higher on standardized tests?
• Do students who receive free meals at school get higher grades compared to when they weren't receiving a free meal?
• Do students who attend charter schools score higher on standardized tests than students in public schools?
• Do students learn better in same-sex classrooms?
• How does giving each student access to an iPad or laptop affect their studies?
• What are the benefits and drawbacks of the Montessori Method ?
• Do children who attend preschool do better in school later on?
• What was the impact of the No Child Left Behind act?
• How does the US education system compare to education systems in other countries?
• What impact does mandatory physical education classes have on students' health?
• Which methods are most effective at reducing bullying in schools?
• Do homeschoolers who attend college do as well as students who attended traditional schools?
• Does offering tenure increase or decrease quality of teaching?
• How does college debt affect future life choices of students?
• Should graduate students be able to form unions?

• What are different ways to lower gun-related deaths in the US?
• How and why have divorce rates changed over time?
• Is affirmative action still necessary in education and/or the workplace?
• Should physician-assisted suicide be legal?
• How has stem cell research impacted the medical field?
• How can human trafficking be reduced in the United States/world?
• Should people be able to donate organs in exchange for money?
• Which types of juvenile punishment have proven most effective at preventing future crimes?
• Has the increase in US airport security made passengers safer?
• Analyze the immigration policies of certain countries and how they are similar and different from one another.
• Several states have legalized recreational marijuana. What positive and negative impacts have they experienced as a result?
• Do tariffs increase the number of domestic jobs?
• Which prison reforms have proven most effective?
• Should governments be able to censor certain information on the internet?
• Which methods/programs have been most effective at reducing teen pregnancy?
• What are the benefits and drawbacks of the Keto diet?
• How effective are different exercise regimes for losing weight and maintaining weight loss?
• How do the healthcare plans of various countries differ from each other?
• What are the most effective ways to treat depression ?
• What are the pros and cons of genetically modified foods?
• Which methods are most effective for improving memory?
• What can be done to lower healthcare costs in the US?
• What factors contributed to the current opioid crisis?
• Analyze the history and impact of the HIV/AIDS epidemic .
• Are low-carbohydrate or low-fat diets more effective for weight loss?
• How much exercise should the average adult be getting each week?
• Which methods are most effective to get parents to vaccinate their children?
• What are the pros and cons of clean needle programs?
• How does stress affect the body?
• Discuss the history of the conflict between Israel and the Palestinians.
• What were the causes and effects of the Salem Witch Trials?
• Who was responsible for the Iran-Contra situation?
• How has New Orleans and the government's response to natural disasters changed since Hurricane Katrina?
• What events led to the fall of the Roman Empire?
• What were the impacts of British rule in India ?
• Was the atomic bombing of Hiroshima and Nagasaki necessary?
• What were the successes and failures of the women's suffrage movement in the United States?
• What were the causes of the Civil War?
• How did Abraham Lincoln's assassination impact the country and reconstruction after the Civil War?
• Which factors contributed to the colonies winning the American Revolution?
• What caused Hitler's rise to power?
• Discuss how a specific invention impacted history.
• What led to Cleopatra's fall as ruler of Egypt?
• How has Japan changed and evolved over the centuries?
• What were the causes of the Rwandan genocide ?

• Why did Martin Luther decide to split with the Catholic Church?
• Analyze the history and impact of a well-known cult (Jonestown, Manson family, etc.)
• How did the sexual abuse scandal impact how people view the Catholic Church?
• How has the Catholic church's power changed over the past decades/centuries?
• What are the causes behind the rise in atheism/ agnosticism in the United States?
• What were the influences in Siddhartha's life resulted in him becoming the Buddha?
• How has media portrayal of Islam/Muslims changed since September 11th?

Science/Environment

• How has the earth's climate changed in the past few decades?
• How has the use and elimination of DDT affected bird populations in the US?
• Analyze how the number and severity of natural disasters have increased in the past few decades.
• Analyze deforestation rates in a certain area or globally over a period of time.
• How have past oil spills changed regulations and cleanup methods?
• How has the Flint water crisis changed water regulation safety?
• What are the pros and cons of fracking?
• What impact has the Paris Climate Agreement had so far?
• What have NASA's biggest successes and failures been?
• How can we improve access to clean water around the world?
• Does ecotourism actually have a positive impact on the environment?
• Should the US rely on nuclear energy more?
• What can be done to save amphibian species currently at risk of extinction?
• What impact has climate change had on coral reefs?
• How are black holes created?
• Are teens who spend more time on social media more likely to suffer anxiety and/or depression?
• How will the loss of net neutrality affect internet users?
• Analyze the history and progress of self-driving vehicles.
• How has the use of drones changed surveillance and warfare methods?
• Has social media made people more or less connected?
• What progress has currently been made with artificial intelligence ?
• Do smartphones increase or decrease workplace productivity?
• What are the most effective ways to use technology in the classroom?
• How is Google search affecting our intelligence?
• When is the best age for a child to begin owning a smartphone?
• Has frequent texting reduced teen literacy rates?

How to Write a Great Research Paper

Even great research paper topics won't give you a great research paper if you don't hone your topic before and during the writing process. Follow these three tips to turn good research paper topics into great papers.

#1: Figure Out Your Thesis Early

Before you start writing a single word of your paper, you first need to know what your thesis will be. Your thesis is a statement that explains what you intend to prove/show in your paper. Every sentence in your research paper will relate back to your thesis, so you don't want to start writing without it!

As some examples, if you're writing a research paper on if students learn better in same-sex classrooms, your thesis might be "Research has shown that elementary-age students in same-sex classrooms score higher on standardized tests and report feeling more comfortable in the classroom."

If you're writing a paper on the causes of the Civil War, your thesis might be "While the dispute between the North and South over slavery is the most well-known cause of the Civil War, other key causes include differences in the economies of the North and South, states' rights, and territorial expansion."

#2: Back Every Statement Up With Research

Remember, this is a research paper you're writing, so you'll need to use lots of research to make your points. Every statement you give must be backed up with research, properly cited the way your teacher requested. You're allowed to include opinions of your own, but they must also be supported by the research you give.

#3: Do Your Research Before You Begin Writing

You don't want to start writing your research paper and then learn that there isn't enough research to back up the points you're making, or, even worse, that the research contradicts the points you're trying to make!

Get most of your research on your good research topics done before you begin writing. Then use the research you've collected to create a rough outline of what your paper will cover and the key points you're going to make. This will help keep your paper clear and organized, and it'll ensure you have enough research to produce a strong paper.

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Christine graduated from Michigan State University with degrees in Environmental Biology and Geography and received her Master's from Duke University. In high school she scored in the 99th percentile on the SAT and was named a National Merit Finalist. She has taught English and biology in several countries.

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Selecting a Research Topic: Overview

• Refine your topic
• Background information & facts
• Writing help

Here are some resources to refer to when selecting a topic and preparing to write a paper:

• MIT Writing and Communication Center "Providing free professional advice about all types of writing and speaking to all members of the MIT community."
• Search Our Collections Find books about writing. Search by subject for: english language grammar; report writing handbooks; technical writing handbooks
• Blue Book of Grammar and Punctuation Online version of the book that provides examples and tips on grammar, punctuation, capitalization, and other writing rules.
• Select a topic

Choosing an interesting research topic is your first challenge. Here are some tips:

• Choose a topic that you are interested in! The research process is more relevant if you care about your topic.
• If your topic is too broad, you will find too much information and not be able to focus.
• Background reading can help you choose and limit the scope of your topic. 
• Review the guidelines on topic selection outlined in your assignment.  Ask your professor or TA for suggestions.
• Refer to lecture notes and required texts to refresh your knowledge of the course and assignment.
• Talk about research ideas with a friend.  S/he may be able to help focus your topic by discussing issues that didn't occur to you at first.
• WHY did you choose the topic?  What interests you about it?  Do you have an opinion about the issues involved?
• WHO are the information providers on this topic?  Who might publish information about it?  Who is affected by the topic?  Do you know of organizations or institutions affiliated with the topic?
• WHAT are the major questions for this topic?  Is there a debate about the topic?  Are there a range of issues and viewpoints to consider?
• WHERE is your topic important: at the local, national or international level?  Are there specific places affected by the topic?
• WHEN is/was your topic important?  Is it a current event or an historical issue?  Do you want to compare your topic by time periods?

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• Last Updated: Jul 30, 2021 2:50 PM
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How To Find A High-Quality Research Topic

6 steps to find & evaluate high-quality dissertation/thesis topics.

By: Caroline Osella (PhD, BA)  and Derek Jansen (MBA) | July 2019

So, you’re finally nearing the end of your degree and it’s now time to find a suitable topic for your dissertation or thesis. Or perhaps you’re just starting out on your PhD research proposal and need to find a suitable area of research for your application proposal.

In this post, we’ll provide a straightforward 6-step process that you can follow to ensure you arrive at a high-quality research topic . Follow these steps and you will formulate a well-suited, well-defined core research question .

There’s a helpful clue already: your research ‘topic’ is best understood as a research question or a problem . Your aim is not to create an encyclopedia entry into your field, but rather to shed light on an acknowledged issue that’s being debated (or needs to be). Think research  questions , not research  topics  (we’ll come back to this later).

Overview: How To Find & Choose A Research Topic

• Get an understanding of the research process
• Review previous dissertations from your university
• Review the academic literature to start the ideation process
• Identify your potential research questions (topics) and shortlist
• Narrow down, then evaluate your research topic shortlist
• Make the decision (and stick with it!)

Step 1: Understand the research process

It may sound horribly obvious, but it’s an extremely common mistake – students skip past the fundamentals straight to the ideation phase (and then pay dearly for it).

Start by looking at whatever handouts and instructions you’ve been given regarding what your university/department expects of a dissertation. For example, the course handbook, online information and verbal in-class instructions. I know it’s tempting to just dive into the ideation process, but it’s essential to start with the prescribed material first.

There are two important reasons for this:

First , you need to have a basic understanding of the research process , research methodologies , fieldwork options and analysis methods before you start the ideation process, or you will simply not be equipped to think about your own research adequately. If you don’t understand the basics of  quantitative , qualitative and mixed methods BEFORE you start ideating, you’re wasting your time.

Second , your university/department will have specific requirements for your research – for example, requirements in terms of topic originality, word count, data requirements, ethical adherence, methodology, etc. If you are not aware of these from the outset, you will again end up wasting a lot of time on irrelevant ideas/topics.

So, the most important first step is to get your head around both the basics of research (especially methodologies), as well as your institution’s specific requirements . Don’t give in to the temptation to jump ahead before you do this. As a starting point, be sure to check out our free dissertation course.

Step 2: Review past dissertations/theses

Unless you’re undertaking a completely new course, there will be many, many students who have gone through the research process before and have produced successful dissertations, which you can use to orient yourself. This is hugely beneficial – imagine being able to see previous students’ assignments and essays when you were doing your coursework!

Take a look at some well-graded (65% and above) past dissertations from your course (ideally more recent ones, as university requirements may change over time). These are usually available in the university’s online library. Past dissertations will act as a helpful model for all kinds of things, from how long a bibliography needs to be, to what a good literature review looks like, through to what kinds of methods you can use – and how to leverage them to support your argument.

As you peruse past dissertations, ask yourself the following questions:

• What kinds of topics did these dissertations cover and how did they turn the topic into questions?
• How broad or narrow were the topics?
• How original were the topics? Were they truly groundbreaking or just a localised twist on well-established theory?
• How well justified were the topics? Did they seem important or just nice to know?
• How much literature did they draw on as a theoretical base? Was the literature more academic or applied in nature?
• What kinds of research methods did they use and what data did they draw on?
• How did they analyse that data and bring it into the discussion of the academic literature?
• Which of the dissertations are most readable to you – why? How were they presented?
• Can you see why these dissertations were successful? Can you relate what they’ve done back to the university’s instructions/brief?

Seeing a variety of dissertations (at least 5, ideally in your area of interest) will also help you understand whether your university has very rigid expectations in terms of structure and format , or whether they expect and allow variety in the number of chapters, chapter headings, order of content, style of presentation and so on.

Some departments accept graphic novels; some are willing to grade free-flow continental-philosophy style arguments; some want a highly rigid, standardised structure.  Many offer a dissertation template , with information on how marks are split between sections. Check right away whether you have been given one of those templates – and if you do, then use it and don’t try to deviate or reinvent the wheel.

Step 3: Review the academic literature

Now that you (1) understand the research process, (2) understand your university’s specific requirements for your dissertation or thesis, and (3) have a feel for what a good dissertation looks like, you can start the ideation process. This is done by reviewing the current literature and looking for opportunities to add something original to the academic conversation.

Kick start the ideation process

So, where should you start your literature hunt? The best starting point is to get back to your modules. Look at your coursework and the assignments you did. Using your coursework is the best theoretical base, as you are assured that (1) the literature is of a high enough calibre for your university and (2) the topics are relevant to your specific course.

Start by identifying the modules that interested you the most and that you understood well (i.e. earned good marks for). What were your strongest assignments, essays or reports? Which areas within these were particularly interesting to you? For example, within a marketing module, you may have found consumer decision making or organisation trust to be interesting. Create a shortlist of those areas that you were both interested in and academically strong at. It’s no use picking an area that does not genuinely interest you – you’ll run out of motivation if you’re not excited by a topic.

Understand the current state of knowledge

Once you’ve done that, you need to get an understanding of the current state of the literature for your chosen interest areas. What you’re aiming to understand is this: what is the academic conversation here and what critical questions are yet unanswered? These unanswered questions are prime opportunities for a unique, meaningful research topic . A quick review of the literature on your favourite topics will help you understand this.

Grab your reading list from the relevant section of the modules, or simply enter the topics into Google Scholar . Skim-read 3-5 journal articles from the past 5 years which have at least 5 citations each (Google Scholar or a citations index will show you how many citations any given article has – i.e., how many other people have referred to it in their own bibliography). Also, check to see if your discipline has an ‘annual review’ type of journal, which gathers together surveys of the state of knowledge on a chosen topic. This can be a great tool for fast-tracking your understanding of the current state of the knowledge in any given area.

Start from your course’s reading list and work outwards. At the end of every journal article, you’ll find a reference list. Scan this reference list for more relevant articles and read those. Then repeat the process (known as snowballing) until you’ve built up a base of 20-30 quality articles per area of interest.

Absorb, don’t hunt

At this stage, your objective is to read and understand the current state of the theory for your area(s) of interest – you don’t need to be in topic-hunting mode yet. Don’t jump the gun and try to identify research topics before you are well familiarised with the literature.

As you read, try to understand what kinds of questions people are asking and how they are trying to answer them. What matters do the researchers agree on, and more importantly, what are they in disagreement about? Disagreements are prime research territory. Can you identify different ‘schools of thought’ or different ‘approaches’? Do you know what your own approach or slant is? What kinds of articles appeal to you and which ones bore you or leave you feeling like you’ve not really grasped them? Which ones interest you and point towards directions you’d like to research and know more about?

Once you understand the fundamental fact that academic knowledge is a conversation, things get easier.

Think of it like a party. There are groups of people in the room, enjoying conversations about various things. Which group do you want to join?  You don’t want to be that person in the corner, talking to themself. And you don’t want to be the hanger-on, laughing at the big-shot’s jokes and repeating everything they say.

Do you want to join a large group and try to make a small contribution to what’s going on, or are you drawn to a smaller group that’s having a more niche conversation, but where you feel you might more easily find something original to contribute? How many conversations can you identify? Which ones feel closer to you and more attractive? Which ones repel you or leave you cold? Are there some that, frankly, you just don’t understand?

Now, choose a couple of groups who are discussing something you feel interested in and where you feel like you might want to contribute. You want to make your entry into this group by asking a question – a question that will make the other people in the group turn around and look at you, listen to you, and think, “That’s interesting”.

Your dissertation will be the process of setting that question and then trying to find at least a partial answer to that question – but don’t worry about that now.  Right now, you need to work out what conversations are going on, whether any of them are related or overlapping, and which ones you might be able to walk into. I’ll explain how you find that question in the next step.

Need a helping hand?

Step 4: Identify potential research questions

Now that you have a decent understanding of the state of the literature in your area(s) of interest, it’s time to start developing your list of possible research topics. There are (at least) three approaches you can follow here, and they are not mutually exclusive:

Approach 1: Leverage the FRIN

Towards the end of most quality journal articles, you will find a section labelled “ further research ” or something similar. Generally, researchers will clearly outline where they feel further research is needed (FRIN), following on from their own research. So, essentially, every journal article presents you with a list of potential research opportunities.

Of course, only a handful of these will be both practical and of interest to you, so it’s not a quick-fix solution to finding a research topic. However, the benefit of going this route is that you will be able to find a genuinely original and meaningful research topic (which is particularly important for PhD-level research).

The upside to this approach is originality, but the downside is that you might not find something that really interests you , or that you have the means to execute. If you do go this route, make sure that you pay attention to the journal article dates, as the FRIN may already have been “solved” by other researchers if the article is old.

Approach 2: Put a context-based spin on an existing topic

The second option is to consider whether a theory which is already well established is relevant within a local or industry-specific context. For example, a theory about the antecedents (drivers) of trust is very well established, but there may be unique or uniquely important drivers within a specific national context or industry (for example, within the financial services industry in an emerging market).

If that industry or national context has not yet been covered by researchers and there is a good reason to believe there may be meaningful differences within that context, then you have an opportunity to take a unique angle on well-established theory, which can make for a great piece of research. It is however imperative that you have a good reason to believe that the existing theory may not be wholly relevant within your chosen context, or your research will not be justified.

The upside to this approach is that you can potentially find a topic that is “closer to home” and more relevant and interesting to you , while still being able to draw on a well-established body of theory. However, the downside is that this approach will likely not produce the level of originality as approach #1.

Approach 3: Uncensored brainstorming

The third option is to skip the FRIN, as well as the local/industry-specific angle and simply engage in a freeform brainstorming or mind-mapping session, using your newfound knowledge of the theory to formulate potential research ideas. What’s important here is that you do not censor yourself . However crazy, unfeasible, or plain stupid your topic appears – write it down. All that matters right now is that you are interested in this thing.

Next, try to turn the topic(s) into a question or problem. For example:

• What is the relationship between X, Y & Z?
• What are the drivers/antecedents of X?
• What are the outcomes of Y?
• What are the key success factors for Z?

Re-word your list of topics or issues into a list of questions .  You might find at this stage that one research topic throws up three questions (which then become sub-topics and even new separate topics in their own right) and in so doing, the list grows. Let it. Don’t hold back or try to start evaluating your ideas yet – just let them flow onto paper.

Once you’ve got a few topics and questions on paper, check the literature again to see whether any of these have been covered by the existing research. Since you came up with these from scratch, there is a possibility that your original literature search did not cover them, so it’s important to revisit that phase to ensure that you’re familiar with the relevant literature for each idea. You may also then find that approach #1 and #2 can be used to build on these ideas.

Try use all three approaches

As mentioned earlier, the three approaches discussed here are not mutually exclusive. In fact, the more, the merrier. Hopefully, you manage to utilise all three, as this will give you the best odds of producing a rich list of ideas, which you can then narrow down and evaluate, which is the next step.

Step 5: Narrow down, then evaluate

By this stage, you should have a healthy list of research topics. Step away from the ideation and thinking for a few days, clear your mind. The key is to get some distance from your ideas, so that you can sit down with your list and review it with a more objective view. The unbridled ideation phase is over and now it’s time to take a reality check .

Look at your list and see if any options can be crossed off right away .  Maybe you don’t want to do that topic anymore. Maybe the topic turned out to be too broad and threw up 20 hard to answer questions. Maybe all the literature you found about it was 30 years old and you suspect it might not be a very engaging contemporary issue . Maybe this topic is so over-researched that you’ll struggle to find anything fresh to say. Also, after stepping back, it’s quite common to notice that 2 or 3 of your topics are really the same one, the same question, which you’ve written down in slightly different ways. You can try to amalgamate these into one succinct topic.

Narrow down to the top 5, then evaluate

Now, take your streamlined list and narrow it down to the ‘top 5’ that interest you the most. Personal interest is your key evaluation criterion at this stage. Got your ‘top 5’?  Great!  Now, with a cool head and your best analytical mind engaged, go systematically through each option and evaluate them against the following criteria:

Research questions – what is the main research question, and what are the supporting sub-questions? It’s critically important that you can define these questions clearly and concisely. If you cannot do this, it means you haven’t thought the topic through sufficiently.

Originality – is the topic sufficiently original, as per your university’s originality requirements? Are you able to add something unique to the existing conversation? As mentioned earlier, originality can come in many forms, and it doesn’t mean that you need to find a completely new, cutting-edge topic. However, your university’s requirements should guide your decision-making here.

Importance – is the topic of real significance, or is it just a “nice to know”? If it’s significant, why? Who will benefit from finding the answer to your desired questions and how will they benefit? Justifying your research will be a key requirement for your research proposal , so it’s really important to develop a convincing argument here.

Literature – is there a contemporary (current) body of academic literature around this issue? Is there enough literature for you to base your investigation on, but not too much that the topic is “overdone”? Will you be able to navigate this literature or is it overwhelming?

Data requirements – What kind of data would you need access to in order to answer your key questions?  Would you need to adopt a qualitative, quantitative or mixed-methods approach to answer your questions? At this stage, you don’t need to be able to map out your exact research design, but you should be able to articulate how you would approach it in high-level terms. Will you use qual, quant or mixed methods? Why?

Feasibility – How feasible would it be to gather the data that would be needed in the time-frame that you have – and do you have the will power and the skills to do it? If you’re not confident with the theory, you don’t want something that’s going to draw you into a debate about the relative importance of epistemology and ontology. If you are shy, you won’t want to be doing ethnographic interviews. If you feel this question calls for a 100-person survey, do you have the time to plan, organise and conduct it and then analyse it? What will you do if you don’t get the response rate you expect? Be very realistic here and also ask advice from your supervisor and other experts – poor response rates are extremely common and can derail even the best research projects.

Personal attraction – On a scale of 1-10, how excited are you about this topic? Will addressing it add value to your life and/or career? Will undertaking the project help you build a skill you’ve previously wanted to work on (for example, interview skills, statistical analysis skills, software skills, etc.)?

The last point is particularly important. You will have to engage with your dissertation in a very sustained and deep way, face challenges and difficulties, and get it to completion. If you don’t start out enthusiastic about it, you’re setting yourself up for problems like ‘writer’s block’ or ‘burnout’ down the line. This is the reason personal interest was the sole evaluation criterion when we chose the top 5. So, don’t underestimate the importance of personal attraction to a topic – at the same time, don’t let personal attraction lead you to choose a topic that is not relevant to your course or feasible given your resources. 

Narrow down to 3, then get human feedback

We’re almost at the finishing line. The next step is to narrow down to 2 or 3 shortlisted topics. No more!  Write a short paragraph about each topic, addressing the following:

Firstly,  WHAT will this study be about? Frame the topic as a question or a problem. Write it as a dissertation title. No more than two clauses and no more than 15 words. Less than 15 is better (go back to good journal articles for inspiration on appropriate title styles).

Secondly, WHY this is interesting (original) and important – as proven by existing academic literature? Are people talking about this and is there an acknowledged problem, debate or gap in the literature?

Lastly,  HOW do you plan to answer the question? What sub-questions will you use? What methods does this call for and how competent and confident are you in those methods? Do you have the time to gather the data this calls for?

Show the shortlist and accompanying paragraphs to a couple of your peers from your course and also to an expert or two if at all possible (you’re welcome to reach out to us ), explaining what you will investigate, why this is original and important and how you will go about investigating it. 

Once you’ve pitched your ideas, ask for the following thoughts :

• Which is most interesting and appealing to them?
• Why do they feel this way?
• What problems do they foresee with the execution of the research?

Take advice and feedback and sit on it for another day. Let it simmer in your mind overnight before you make the final decision.  

Step 6: Make the decision (and stick with it!)

Then, make the commitment. Choose the one that you feel most confident about, having now considered both your opinion and the feedback from others.

Once you’ve made a decision, don’t doubt your judgement, don’t shift.  Don’t be tempted by the ones you left behind. You’ve planned and thought things through, checked feasibility and now you can start.  You have your research topic. Trust your own decision-making process and stick with it now. It’s time to get started on your research proposal!

Let’s recap…

In this post, I’ve proposed a straightforward 6-step plan to finding relevant research topic ideas and then narrowing them down to finally choose one winner. To recap:

• Understand the basics of academic research, as well as your university’s specific requirements for a dissertation, thesis or research project.
• Review previous dissertations for your course to get an idea of both topics and structure.
• Start the ideation process by familiarising yourself with the literature.
• Identify your potential research questions (topics).
• Narrow down your options, then evaluate systematically.
• Make your decision (and don’t look back!)

If you follow these steps, you’ll find that they also set you up for what’s coming next – both the proposal and the first three chapters of your dissertation. But that’s for future posts!

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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23 Comments

I would love to get a topic under teachers performance. I am a student of MSC Monitoring and Evaluations and I need a topic in the line of monitoring and evaluations

I just we put for some full notes that are payable

Thank you very much Dr Caroline

I need a project topics on transfer of learning

m a PhD Student I would like to be assisted inn formulating a title around: Internet of Things for online education in higher education – STEM (Science, technology, engineering and Mathematics, digital divide ) Thank you, would appreciate your guidance

Well structured guide on the topic… Good materials for beginners in research writing…

Hello Iam kindly seeking for help in formulating a researchable topic for masters degree program in line with teaching GRAPHIC ART

I read a thesis about a problem in a particular. Can I use the same topic just referring to my own country? Is that being original? The interview questions will mostly be the same as the other thesis.

Hi, thanks I managed to listen to the video so helpful indeed. I am currently an MBA student looking for a specific topic and I have different ideas that not sure they can be turned to be a study.

I am doing a Master of Theology in Pastoral Care and Counselling and I felt like doing research on Spiritual problem cause by substance abuse among Youth. Can I get help to formulate the Thesis Title in line with it…please

Hello, I am kindly seeking help in formulating a researchable topic for a National diploma program

As a beginner in research, I am very grateful for this well-structured material on research writing.

Hello, I watched the video and its very helpful. I’m a student in Nursing (degree). May you please help me with any research problems (in Namibian society or Nursing) that need to be evaluate or solved?

I have been greatly impacted. Thank you.

more than useful… there will be no justification if someone fails to get a topic for his thesis

I watched the video and its really helpful.

How can i started discovery

Analysing the significance of Integrated reporting in Zimbabwe. A case of institutional investors. this is my topic for PHD Accounting sciences need help with research questions

Excellent session that cleared lots of doubts.

Excellent session that cleared lots of doubts

It was a nice one thank you

Wow, This helped a lot not only with how to find a research topic but inspired me to kick it off from now, I am a final year student of environmental science. And have to complete my project in the coming six months.

I was really stressed and thinking about different topics that I don’t know nothing about and having more than a hundred topics in the baggage, couldn’t make the tradeoff among them, however, reading this scrubbed the fuzzy layer off my head and now it seems like really easy.

Thanks GRADCOACH, you saved me from getting into the rabbit hole.

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Search catalog, critical thinking and academic research: intro.

• Information
• Point of View
• Assumptions
• Implications

Critical Thinking and Academic Research

Academic research focuses on the creation of new ideas, perspectives, and arguments. The researcher seeks relevant information in articles, books, and other sources, then develops an informed point of view within this ongoing "conversation" among researchers.

The research process is not simply collecting data, evidence, or "facts," then piecing together this preexisting information into a paper. Instead, the research process is about inquiry—asking questions and developing answers through serious critical thinking and thoughtful reflection.

As a result, the research process is recursive, meaning that the researcher regularly revisits ideas, seeks new information when necessary, and reconsiders and refines the research question, topic, or approach. In other words, research almost always involves constant reflection and revision.

This guide is designed to help you think through various aspects of the research process. The steps are not sequential, nor are they prescriptive about what steps you should take at particular points in the research process. Instead, the guide should help you consider the larger, interrelated elements of thinking involved in research.

Research Anxiety?

Research is not often easy or straightforward, so it's completely normal to feel anxious, frustrated, or confused. In fact, if you feel anxious, it can be a good sign that you're engaging in the type of critical thinking necessary to research and write a high-quality paper.

Think of the research process not as one giant, impossibly complicated task, but as a series of smaller, interconnected steps. These steps can be messy, and there is not one correct sequence of steps that will work for every researcher. However, thinking about research in small steps can help you be more productive and alleviate anxiety.

Paul-Elder Framework

This guide is based on the "Elements of Reasoning" from the Paul-Elder framework for critical thinking. For more information about the Paul-Elder framework, click the link below.

Some of the content in this guide has been adapted from The Aspiring Thinker's Guide to Critical Thinking (2009) by Linda Elder and Richard Paul.

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Narrowing a Topic

For many students, having to start with a research question is the biggest difference between how they did research in high school and how they are required to carry out their college research projects. It’s a process of working from the outside in: you start with the world of all possible topics (or your assigned topic) and narrow down until you’ve focused your interest enough to be able to tell precisely what you want to find out, instead of only what you want to “write about.”

Process of Narrowing a Topic

Visualize narrowing a topic as starting with all possible topics and choosing narrower and narrower subsets until you have a specific enough topic to form a research question.

All Possible Topics – You’ll need to narrow your topic to do research effectively. Without specific areas of focus, it will be hard to even know where to begin.

Assigned Topics –  Ideas about a narrower topic can come from anywhere. Often, a narrower topic boils down to deciding what’s interesting to you. One way to get ideas is to read background information in a source like Wikipedia.

Topic Narrowed by Initial Exploration –  It’s wise to do some background reading about that narrower topic to a) learn more about it and b) learn specialized terms used by professionals and scholars who study it.

Topic Narrowed to Research Question(s) –  A research question defines exactly what you are trying to find out. It will influence most of the steps you take to conduct the research.

Why Narrow a Topic?

Once you have a need for research—say, an assignment—you may need to prowl around a bit online to explore the topic and figure out what you actually want to find out and write about. For instance, maybe your assignment is to develop a poster about “spring” for an introductory horticulture course. The instructor expects you to narrow that topic to something you are interested in and that is related to your class.

Another way to view a narrowed topic is as a sliver of the whole topic.

Ideas about a narrower topic can come from anywhere. In this case, a narrower topic boils down to deciding what’s interesting to you about “spring” that is related to what you’re learning in your horticulture class and small enough to manage in the time you have. One way to get ideas would be to read about spring in Wikipedia, a reference database such as CREDO, or a subject encyclopedia. Look for things that seem interesting and relevant to your class, and then let one thing lead to another as you keep reading and thinking about likely possibilities that are more narrow than the enormous “spring” topic. Be sure to pay attention to the references at the bottom of most Wikipedia pages and pursue any that look interesting. Your instructor is not likely to let you cite Wikipedia, but those references may be scholarly sources that you could eventually decide to use and cite.

Or, instead, if it is spring at the time you could start by just looking around, admire the blooming trees on campus, and decide you’d like your poster to be about bud development on your favorites, the crabapple trees.

Jada Narrows Her Topic and Works on a Research Question

The Situation: Jada, an undergraduate, has been assigned a research paper on Antarctica. Her professor expects students to narrow the topic to something more specific about Antarctica because they won’t have time to cover that whole topic. Then they are to come up with a research question that their paper will answer.

The professor explained that the research question should be something they are interested in answering and that it must be more complicated than what they could answer with a quick Google search. She also said that research questions often start with either the word “how” or “why.”

Try it out:

• Read what Jada is thinking below as she tries to do the assignment.
• After the reading, answer the questions based on your own approach to research.
• Check your answers with ours.
• Keep this passage in mind the next time you start a research topic and mimic the process that Jada uses.

Jada’s Thoughts

Okay, I have to write—a research paper—about Antarctica. I don’t know anything about that place—and I can’t think of a single thing I’d like to know about Antarctica. Calls for Wikipedia, I guess.

Guess I’ll go here https://en.wikipedia.org/wiki/Antarctica . Just skimming. Pretty boring stuff. Oh, look– Antarctica’s a desert! I guess “desert” doesn’t have to do with heat. That’s interesting. Why is it considered a desert, there’s lots of snow and ice there. Have to think about that—what makes a desert a desert.

It says one to five thousand people live there in research stations. Year-round. And there is no evidence that it was seen by humans until the 19th century. I never thought about whether anybody lived in Antarctica first, before explorers and scientists.

Lots of names—explorers, others. It says Amundsen reached the South pole first. Who’s Amundsen? But wait. It says, “One month later, the doomed Scott Expedition reached the pole.” Doomed? Doomed is always interesting. Where is there more information about the Scott Expedition? There is only one sentence. Why would they have just that one sentence? I’ll have to click on the Scott Expedition link.

Terra Nova…

But it gives me a page called Terra Nova Expedition. What does that have to do with Scott? Who was he and why was his expedition doomed? There he is in a photo before going to Antarctica. Guess he was English. Other photos show him and his team in the snow. Oh, the expedition was named Terra Nova after the ship they sailed this time—in 1911. Scott was also there earlier on another ship.

Lots of info about preparing for the trip. Then stuff about expedition journeys once they were in Antarctica. Not very exciting—nothing about being doomed.

Wait. The last paragraph of the first section says “For many years after his death, Scott’s status as a tragic hero was unchallenged,” but then it says that in the 20th-century people looked closer at the expedition’s management and at whether Scott and some of his team could be personally blamed for the catastrophe. That “remains controversial,” it says. Catastrophe? Personally, blamed? Hmm.

Back to skimming. It all seems horrible to me. They actually planned to kill their ponies for meat. Everything was extremely difficult. And then when they arrived at the South Pole, they found that the explorer Amundsen had beaten them. Must have been a big disappointment.

The homeward march was even worse. The weather was bad. The dog sleds that were supposed to meet them periodically with supplies didn’t show up. Or maybe the Scott group was lost and didn’t go to the right meeting places. Maybe that’s what that earlier statement meant about whether the decisions that were made were good ones. Scott’s diary said the crystallized snow made it seem like they were pushing and pulling the sleds through dry sand .

It says that before things turned really bad, Scott allowed his men to put 30 pounds of rocks with fossils on the sleds they were pushing and dragging. Now was that sensible? But here it says that those rocks are the proof of continental drift. So how did they know those rocks were so important? Was that knowledge worth their lives? Could they have known?

Scott’s diary is quoted about their troubles on the expedition—the relentless cold, frostbite, and the deaths of their dogs. One entry tells of a guy on Scott’s team “now with hands as well as feet pretty well useless” voluntarily leaving the tent and walking to his death. The diary says that the team member’s last words were ”I am just going outside and may be some time.”

They all seem lost and desperate but still have those sleds. Why would you keep pulling and pushing those sleds containing an extra 30 pounds of rock when you are so desperate and every step is life or death?

Then there’s Scott’s last diary entry, on March 29, 1912. “… It seems a pity but I do not think I can write more.”. The diary apparently gave lots of locations of where he thought they were but maybe they were lost. It says they ended up only 11 miles from one of their supply stations.

I’d love to see that diary. Wouldn’t that be cool? Online? I’ll Google it. Yes! it’s at the British Museum. Look at that! I can see Scott’s last entry IN HIS OWN HANDWRITING! And there’s a digital copy too.

I wonder if I should narrow my topic to just the controversy over whether the expedition was doomed because of the bad decisions made by Scott and his crew?  Maybe it’s too big a topic if I consider the decisions of all team members. Maybe I should just consider Scott’s decisions. They should be noted in the diary.

So what research question could come from that? Maybe: how did Scott’s decisions contribute to his team’s deaths in Antarctica? Need to be more focused: How did Scott’s decisions after reaching the South Pole help or hurt the chances of his team getting back safely? There are several of his decisions discussed on the Wikipedia page, and I know there are sources at the bottom of that page.

Really, a desert?

Let me think—what else did I see that was interesting or puzzling about all this? I remember being surprised that Antarctica is a desert. So maybe I could make the desert of Antarctica my topic. My research question could be something like: Why is Antarctica considered a desert? But there has to be a definition of deserts somewhere online, so that doesn’t sound complicated enough. Maybe those rocks with the fossils in them. It’s just so hard to imagine desperate explorers continuing to push those sleds with an extra 30 pounds of rocks on them. Did they somehow know how important they would be? Why didn’t they ditch them? Or maybe they just didn’t realize how close to death they were. Maybe I could narrow my Antarctica topic to those rocks.

Maybe my topic could be something like The rocks that Scott and his crew found in Antarctica that prove continental drift. Maybe my research question could be: How did Scott’s explorers choose the rocks they kept? Or maybe I should stick with why Scott and his crew made bad decisions.

I should ask.

I think my professor is the only one who can tell me whether my question about the rocks has enough to do with Antarctica. Since she’s the one who will be grading my paper. But a librarian can help me figure out the other things. So Dr. Sanders and a librarian are next.

• Was Jada’s choice to start with Wikipedia a good choice? Why or why not?
• Have you ever skimmed resources first and then read more deeply later?
• At what points does Jada think about where to look for information?
• At the end of this session, Jada hasn’t yet settled on a research question. So what did she accomplish? What good was all this searching and thinking?

Our Answers

• Was Jada’s choice to start with Wikipedia a good choice? Although not usually cited in research papers, Wikipedia is a good place to learn more about all kinds of topics.  Information is usually general in nature and you can check out the references at the bottom of the page. Use those links to find additional resources. This may lead you to library based sources like subject dictionaries, encyclopedias, or guides.
• Have you ever skimmed resources first and then read more deeply later? When first exploring your topic you may choose to skim resources. That is a very brief read looking for interesting and useful information. Later when you select a topic and look for resources that provide deeper, more focused information.
• At what points does Jada think about where to look for information? After receiving the core part of the topic (Antarctica), she begins looking for general information and becomes curious about the Scott expedition. As she learns more she thinks about where she can look for additional information, such as the diary mentioned in Wikipedia..
• At the end of this session, Jada hasn’t yet settled on a research question. So what did she accomplish? What good was all this searching and thinking? The background information that Jada looked at helped her to focus on the problems with the Scott Expedition. She slowly narrows down some of the issues and centers on the weight of the rocks.  She considers two different questions (one more narrow than the other) and intends to seek input from the professor and librarian.  Taking the time to explore her topic has given her ideas useful for a solid research question.

Exercise: Determine the Topic Order

Critical Thinking in Academic Research Copyright © 2022 by Cindy Gruwell and Robin Ewing is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

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• Thinking about Research

As you consider research, it is important to know why you want to make this commitment. Do you want to participate more actively in cutting edge science that you have learned about in the classroom? Is there a particular field or topic you would like to learn more about? Do you want to gain specific skills? Do you want to explore research as a potential career, or as a component of a career? Do you want to experience part of the work environment in a medical facility? Do you want to get course credit? Do you want to embark on a project that could evolve into a senior honors thesis?

Think also about the type of research you may find most useful for your individual goal or set of goals. Would you like to help run scientific experiments? Would you like to help design and/or analyze the results of experiments? Would you like to conduct survey research? Would you like to do archival research in a library setting? Would you prefer to be part of a research team or to work alone? Would you like to do research with humans or animals? Would you like to work with a specific species of animal, or a particular population of humans (e.g., children, elderly, persons with a certain disorder)?

It is helpful to consult with others as you think through these questions. Faculty you already know, other faculty including members of the MBB Board of Faculty Advisors [link here, <mbb/advising>], academic advisors (especially in your concentration but also including Shawn Harriman), teaching fellows and resident tutors (who are usually themselves researchers), and fellow students who are already involved in research are all great sounding boards and sources of additional information and perspectives.

Finally, give some thought about what you can offer a research team. This will help you when you come to applying for specific positions. A current resume is always valuable. You may have specific research experience already, or have taken relevant course work. You may be a good team player with a track record of responsibility and accomplishing goals. You do not usually need to have training in the specific techniques used in a laboratory or research program, as most researchers expect to train their undergraduate assistants. Positions that do have specific expectations will note them in their job description.

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What Is Research, and Why Do People Do It?

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• First Online: 03 December 2022

Cite this chapter

You have full access to this open access chapter

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  

Part of the book series: Research in Mathematics Education ((RME))

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Abstractspiepr Abs1

Every day people do research as they gather information to learn about something of interest. In the scientific world, however, research means something different than simply gathering information. Scientific research is characterized by its careful planning and observing, by its relentless efforts to understand and explain, and by its commitment to learn from everyone else seriously engaged in research. We call this kind of research scientific inquiry and define it as “formulating, testing, and revising hypotheses.” By “hypotheses” we do not mean the hypotheses you encounter in statistics courses. We mean predictions about what you expect to find and rationales for why you made these predictions. Throughout this and the remaining chapters we make clear that the process of scientific inquiry applies to all kinds of research studies and data, both qualitative and quantitative.

You have full access to this open access chapter,  Download chapter PDF

Part I. What Is Research?

Have you ever studied something carefully because you wanted to know more about it? Maybe you wanted to know more about your grandmother’s life when she was younger so you asked her to tell you stories from her childhood, or maybe you wanted to know more about a fertilizer you were about to use in your garden so you read the ingredients on the package and looked them up online. According to the dictionary definition, you were doing research.

Recall your high school assignments asking you to “research” a topic. The assignment likely included consulting a variety of sources that discussed the topic, perhaps including some “original” sources. Often, the teacher referred to your product as a “research paper.”

Were you conducting research when you interviewed your grandmother or wrote high school papers reviewing a particular topic? Our view is that you were engaged in part of the research process, but only a small part. In this book, we reserve the word “research” for what it means in the scientific world, that is, for scientific research or, more pointedly, for scientific inquiry .

Exercise 1.1

Before you read any further, write a definition of what you think scientific inquiry is. Keep it short—Two to three sentences. You will periodically update this definition as you read this chapter and the remainder of the book.

This book is about scientific inquiry—what it is and how to do it. For starters, scientific inquiry is a process, a particular way of finding out about something that involves a number of phases. Each phase of the process constitutes one aspect of scientific inquiry. You are doing scientific inquiry as you engage in each phase, but you have not done scientific inquiry until you complete the full process. Each phase is necessary but not sufficient.

In this chapter, we set the stage by defining scientific inquiry—describing what it is and what it is not—and by discussing what it is good for and why people do it. The remaining chapters build directly on the ideas presented in this chapter.

A first thing to know is that scientific inquiry is not all or nothing. “Scientificness” is a continuum. Inquiries can be more scientific or less scientific. What makes an inquiry more scientific? You might be surprised there is no universally agreed upon answer to this question. None of the descriptors we know of are sufficient by themselves to define scientific inquiry. But all of them give you a way of thinking about some aspects of the process of scientific inquiry. Each one gives you different insights.

Exercise 1.2

As you read about each descriptor below, think about what would make an inquiry more or less scientific. If you think a descriptor is important, use it to revise your definition of scientific inquiry.

Creating an Image of Scientific Inquiry

We will present three descriptors of scientific inquiry. Each provides a different perspective and emphasizes a different aspect of scientific inquiry. We will draw on all three descriptors to compose our definition of scientific inquiry.

Descriptor 1. Experience Carefully Planned in Advance

Sir Ronald Fisher, often called the father of modern statistical design, once referred to research as “experience carefully planned in advance” (1935, p. 8). He said that humans are always learning from experience, from interacting with the world around them. Usually, this learning is haphazard rather than the result of a deliberate process carried out over an extended period of time. Research, Fisher said, was learning from experience, but experience carefully planned in advance.

This phrase can be fully appreciated by looking at each word. The fact that scientific inquiry is based on experience means that it is based on interacting with the world. These interactions could be thought of as the stuff of scientific inquiry. In addition, it is not just any experience that counts. The experience must be carefully planned . The interactions with the world must be conducted with an explicit, describable purpose, and steps must be taken to make the intended learning as likely as possible. This planning is an integral part of scientific inquiry; it is not just a preparation phase. It is one of the things that distinguishes scientific inquiry from many everyday learning experiences. Finally, these steps must be taken beforehand and the purpose of the inquiry must be articulated in advance of the experience. Clearly, scientific inquiry does not happen by accident, by just stumbling into something. Stumbling into something unexpected and interesting can happen while engaged in scientific inquiry, but learning does not depend on it and serendipity does not make the inquiry scientific.

Descriptor 2. Observing Something and Trying to Explain Why It Is the Way It Is

When we were writing this chapter and googled “scientific inquiry,” the first entry was: “Scientific inquiry refers to the diverse ways in which scientists study the natural world and propose explanations based on the evidence derived from their work.” The emphasis is on studying, or observing, and then explaining . This descriptor takes the image of scientific inquiry beyond carefully planned experience and includes explaining what was experienced.

According to the Merriam-Webster dictionary, “explain” means “(a) to make known, (b) to make plain or understandable, (c) to give the reason or cause of, and (d) to show the logical development or relations of” (Merriam-Webster, n.d. ). We will use all these definitions. Taken together, they suggest that to explain an observation means to understand it by finding reasons (or causes) for why it is as it is. In this sense of scientific inquiry, the following are synonyms: explaining why, understanding why, and reasoning about causes and effects. Our image of scientific inquiry now includes planning, observing, and explaining why.

We need to add a final note about this descriptor. We have phrased it in a way that suggests “observing something” means you are observing something in real time—observing the way things are or the way things are changing. This is often true. But, observing could mean observing data that already have been collected, maybe by someone else making the original observations (e.g., secondary analysis of NAEP data or analysis of existing video recordings of classroom instruction). We will address secondary analyses more fully in Chap. 4 . For now, what is important is that the process requires explaining why the data look like they do.

We must note that for us, the term “data” is not limited to numerical or quantitative data such as test scores. Data can also take many nonquantitative forms, including written survey responses, interview transcripts, journal entries, video recordings of students, teachers, and classrooms, text messages, and so forth.

Exercise 1.3

What are the implications of the statement that just “observing” is not enough to count as scientific inquiry? Does this mean that a detailed description of a phenomenon is not scientific inquiry?

Find sources that define research in education that differ with our position, that say description alone, without explanation, counts as scientific research. Identify the precise points where the opinions differ. What are the best arguments for each of the positions? Which do you prefer? Why?

Descriptor 3. Updating Everyone’s Thinking in Response to More and Better Information

This descriptor focuses on a third aspect of scientific inquiry: updating and advancing the field’s understanding of phenomena that are investigated. This descriptor foregrounds a powerful characteristic of scientific inquiry: the reliability (or trustworthiness) of what is learned and the ultimate inevitability of this learning to advance human understanding of phenomena. Humans might choose not to learn from scientific inquiry, but history suggests that scientific inquiry always has the potential to advance understanding and that, eventually, humans take advantage of these new understandings.

Before exploring these bold claims a bit further, note that this descriptor uses “information” in the same way the previous two descriptors used “experience” and “observations.” These are the stuff of scientific inquiry and we will use them often, sometimes interchangeably. Frequently, we will use the term “data” to stand for all these terms.

An overriding goal of scientific inquiry is for everyone to learn from what one scientist does. Much of this book is about the methods you need to use so others have faith in what you report and can learn the same things you learned. This aspect of scientific inquiry has many implications.

One implication is that scientific inquiry is not a private practice. It is a public practice available for others to see and learn from. Notice how different this is from everyday learning. When you happen to learn something from your everyday experience, often only you gain from the experience. The fact that research is a public practice means it is also a social one. It is best conducted by interacting with others along the way: soliciting feedback at each phase, taking opportunities to present work-in-progress, and benefitting from the advice of others.

A second implication is that you, as the researcher, must be committed to sharing what you are doing and what you are learning in an open and transparent way. This allows all phases of your work to be scrutinized and critiqued. This is what gives your work credibility. The reliability or trustworthiness of your findings depends on your colleagues recognizing that you have used all appropriate methods to maximize the chances that your claims are justified by the data.

A third implication of viewing scientific inquiry as a collective enterprise is the reverse of the second—you must be committed to receiving comments from others. You must treat your colleagues as fair and honest critics even though it might sometimes feel otherwise. You must appreciate their job, which is to remain skeptical while scrutinizing what you have done in considerable detail. To provide the best help to you, they must remain skeptical about your conclusions (when, for example, the data are difficult for them to interpret) until you offer a convincing logical argument based on the information you share. A rather harsh but good-to-remember statement of the role of your friendly critics was voiced by Karl Popper, a well-known twentieth century philosopher of science: “. . . if you are interested in the problem which I tried to solve by my tentative assertion, you may help me by criticizing it as severely as you can” (Popper, 1968, p. 27).

A final implication of this third descriptor is that, as someone engaged in scientific inquiry, you have no choice but to update your thinking when the data support a different conclusion. This applies to your own data as well as to those of others. When data clearly point to a specific claim, even one that is quite different than you expected, you must reconsider your position. If the outcome is replicated multiple times, you need to adjust your thinking accordingly. Scientific inquiry does not let you pick and choose which data to believe; it mandates that everyone update their thinking when the data warrant an update.

Doing Scientific Inquiry

We define scientific inquiry in an operational sense—what does it mean to do scientific inquiry? What kind of process would satisfy all three descriptors: carefully planning an experience in advance; observing and trying to explain what you see; and, contributing to updating everyone’s thinking about an important phenomenon?

We define scientific inquiry as formulating , testing , and revising hypotheses about phenomena of interest.

Of course, we are not the only ones who define it in this way. The definition for the scientific method posted by the editors of Britannica is: “a researcher develops a hypothesis, tests it through various means, and then modifies the hypothesis on the basis of the outcome of the tests and experiments” (Britannica, n.d. ).

Notice how defining scientific inquiry this way satisfies each of the descriptors. “Carefully planning an experience in advance” is exactly what happens when formulating a hypothesis about a phenomenon of interest and thinking about how to test it. “ Observing a phenomenon” occurs when testing a hypothesis, and “ explaining ” what is found is required when revising a hypothesis based on the data. Finally, “updating everyone’s thinking” comes from comparing publicly the original with the revised hypothesis.

Doing scientific inquiry, as we have defined it, underscores the value of accumulating knowledge rather than generating random bits of knowledge. Formulating, testing, and revising hypotheses is an ongoing process, with each revised hypothesis begging for another test, whether by the same researcher or by new researchers. The editors of Britannica signaled this cyclic process by adding the following phrase to their definition of the scientific method: “The modified hypothesis is then retested, further modified, and tested again.” Scientific inquiry creates a process that encourages each study to build on the studies that have gone before. Through collective engagement in this process of building study on top of study, the scientific community works together to update its thinking.

Before exploring more fully the meaning of “formulating, testing, and revising hypotheses,” we need to acknowledge that this is not the only way researchers define research. Some researchers prefer a less formal definition, one that includes more serendipity, less planning, less explanation. You might have come across more open definitions such as “research is finding out about something.” We prefer the tighter hypothesis formulation, testing, and revision definition because we believe it provides a single, coherent map for conducting research that addresses many of the thorny problems educational researchers encounter. We believe it is the most useful orientation toward research and the most helpful to learn as a beginning researcher.

A final clarification of our definition is that it applies equally to qualitative and quantitative research. This is a familiar distinction in education that has generated much discussion. You might think our definition favors quantitative methods over qualitative methods because the language of hypothesis formulation and testing is often associated with quantitative methods. In fact, we do not favor one method over another. In Chap. 4 , we will illustrate how our definition fits research using a range of quantitative and qualitative methods.

Exercise 1.4

Look for ways to extend what the field knows in an area that has already received attention by other researchers. Specifically, you can search for a program of research carried out by more experienced researchers that has some revised hypotheses that remain untested. Identify a revised hypothesis that you might like to test.

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

To get a full sense of the definition of scientific inquiry we will use throughout this book, it is helpful to spend a little time with each of the key terms.

We first want to make clear that we use the term “hypothesis” as it is defined in most dictionaries and as it used in many scientific fields rather than as it is usually defined in educational statistics courses. By “hypothesis,” we do not mean a null hypothesis that is accepted or rejected by statistical analysis. Rather, we use “hypothesis” in the sense conveyed by the following definitions: “An idea or explanation for something that is based on known facts but has not yet been proved” (Cambridge University Press, n.d. ), and “An unproved theory, proposition, or supposition, tentatively accepted to explain certain facts and to provide a basis for further investigation or argument” (Agnes & Guralnik, 2008 ).

We distinguish two parts to “hypotheses.” Hypotheses consist of predictions and rationales . Predictions are statements about what you expect to find when you inquire about something. Rationales are explanations for why you made the predictions you did, why you believe your predictions are correct. So, for us “formulating hypotheses” means making explicit predictions and developing rationales for the predictions.

“Testing hypotheses” means making observations that allow you to assess in what ways your predictions were correct and in what ways they were incorrect. In education research, it is rarely useful to think of your predictions as either right or wrong. Because of the complexity of most issues you will investigate, most predictions will be right in some ways and wrong in others.

By studying the observations you make (data you collect) to test your hypotheses, you can revise your hypotheses to better align with the observations. This means revising your predictions plus revising your rationales to justify your adjusted predictions. Even though you might not run another test, formulating revised hypotheses is an essential part of conducting a research study. Comparing your original and revised hypotheses informs everyone of what you learned by conducting your study. In addition, a revised hypothesis sets the stage for you or someone else to extend your study and accumulate more knowledge of the phenomenon.

We should note that not everyone makes a clear distinction between predictions and rationales as two aspects of hypotheses. In fact, common, non-scientific uses of the word “hypothesis” may limit it to only a prediction or only an explanation (or rationale). We choose to explicitly include both prediction and rationale in our definition of hypothesis, not because we assert this should be the universal definition, but because we want to foreground the importance of both parts acting in concert. Using “hypothesis” to represent both prediction and rationale could hide the two aspects, but we make them explicit because they provide different kinds of information. It is usually easier to make predictions than develop rationales because predictions can be guesses, hunches, or gut feelings about which you have little confidence. Developing a compelling rationale requires careful thought plus reading what other researchers have found plus talking with your colleagues. Often, while you are developing your rationale you will find good reasons to change your predictions. Developing good rationales is the engine that drives scientific inquiry. Rationales are essentially descriptions of how much you know about the phenomenon you are studying. Throughout this guide, we will elaborate on how developing good rationales drives scientific inquiry. For now, we simply note that it can sharpen your predictions and help you to interpret your data as you test your hypotheses.

Hypotheses in education research take a variety of forms or types. This is because there are a variety of phenomena that can be investigated. Investigating educational phenomena is sometimes best done using qualitative methods, sometimes using quantitative methods, and most often using mixed methods (e.g., Hay, 2016 ; Weis et al. 2019a ; Weisner, 2005 ). This means that, given our definition, hypotheses are equally applicable to qualitative and quantitative investigations.

Hypotheses take different forms when they are used to investigate different kinds of phenomena. Two very different activities in education could be labeled conducting experiments and descriptions. In an experiment, a hypothesis makes a prediction about anticipated changes, say the changes that occur when a treatment or intervention is applied. You might investigate how students’ thinking changes during a particular kind of instruction.

A second type of hypothesis, relevant for descriptive research, makes a prediction about what you will find when you investigate and describe the nature of a situation. The goal is to understand a situation as it exists rather than to understand a change from one situation to another. In this case, your prediction is what you expect to observe. Your rationale is the set of reasons for making this prediction; it is your current explanation for why the situation will look like it does.

You will probably read, if you have not already, that some researchers say you do not need a prediction to conduct a descriptive study. We will discuss this point of view in Chap. 2 . For now, we simply claim that scientific inquiry, as we have defined it, applies to all kinds of research studies. Descriptive studies, like others, not only benefit from formulating, testing, and revising hypotheses, but also need hypothesis formulating, testing, and revising.

One reason we define research as formulating, testing, and revising hypotheses is that if you think of research in this way you are less likely to go wrong. It is a useful guide for the entire process, as we will describe in detail in the chapters ahead. For example, as you build the rationale for your predictions, you are constructing the theoretical framework for your study (Chap. 3 ). As you work out the methods you will use to test your hypothesis, every decision you make will be based on asking, “Will this help me formulate or test or revise my hypothesis?” (Chap. 4 ). As you interpret the results of testing your predictions, you will compare them to what you predicted and examine the differences, focusing on how you must revise your hypotheses (Chap. 5 ). By anchoring the process to formulating, testing, and revising hypotheses, you will make smart decisions that yield a coherent and well-designed study.

Exercise 1.5

Compare the concept of formulating, testing, and revising hypotheses with the descriptions of scientific inquiry contained in Scientific Research in Education (NRC, 2002 ). How are they similar or different?

Exercise 1.6

Provide an example to illustrate and emphasize the differences between everyday learning/thinking and scientific inquiry.

Learning from Doing Scientific Inquiry

We noted earlier that a measure of what you have learned by conducting a research study is found in the differences between your original hypothesis and your revised hypothesis based on the data you collected to test your hypothesis. We will elaborate this statement in later chapters, but we preview our argument here.

Even before collecting data, scientific inquiry requires cycles of making a prediction, developing a rationale, refining your predictions, reading and studying more to strengthen your rationale, refining your predictions again, and so forth. And, even if you have run through several such cycles, you still will likely find that when you test your prediction you will be partly right and partly wrong. The results will support some parts of your predictions but not others, or the results will “kind of” support your predictions. A critical part of scientific inquiry is making sense of your results by interpreting them against your predictions. Carefully describing what aspects of your data supported your predictions, what aspects did not, and what data fell outside of any predictions is not an easy task, but you cannot learn from your study without doing this analysis.

Analyzing the matches and mismatches between your predictions and your data allows you to formulate different rationales that would have accounted for more of the data. The best revised rationale is the one that accounts for the most data. Once you have revised your rationales, you can think about the predictions they best justify or explain. It is by comparing your original rationales to your new rationales that you can sort out what you learned from your study.

Suppose your study was an experiment. Maybe you were investigating the effects of a new instructional intervention on students’ learning. Your original rationale was your explanation for why the intervention would change the learning outcomes in a particular way. Your revised rationale explained why the changes that you observed occurred like they did and why your revised predictions are better. Maybe your original rationale focused on the potential of the activities if they were implemented in ideal ways and your revised rationale included the factors that are likely to affect how teachers implement them. By comparing the before and after rationales, you are describing what you learned—what you can explain now that you could not before. Another way of saying this is that you are describing how much more you understand now than before you conducted your study.

Revised predictions based on carefully planned and collected data usually exhibit some of the following features compared with the originals: more precision, more completeness, and broader scope. Revised rationales have more explanatory power and become more complete, more aligned with the new predictions, sharper, and overall more convincing.

Part II. Why Do Educators Do Research?

Doing scientific inquiry is a lot of work. Each phase of the process takes time, and you will often cycle back to improve earlier phases as you engage in later phases. Because of the significant effort required, you should make sure your study is worth it. So, from the beginning, you should think about the purpose of your study. Why do you want to do it? And, because research is a social practice, you should also think about whether the results of your study are likely to be important and significant to the education community.

If you are doing research in the way we have described—as scientific inquiry—then one purpose of your study is to understand , not just to describe or evaluate or report. As we noted earlier, when you formulate hypotheses, you are developing rationales that explain why things might be like they are. In our view, trying to understand and explain is what separates research from other kinds of activities, like evaluating or describing.

One reason understanding is so important is that it allows researchers to see how or why something works like it does. When you see how something works, you are better able to predict how it might work in other contexts, under other conditions. And, because conditions, or contextual factors, matter a lot in education, gaining insights into applying your findings to other contexts increases the contributions of your work and its importance to the broader education community.

Consequently, the purposes of research studies in education often include the more specific aim of identifying and understanding the conditions under which the phenomena being studied work like the observations suggest. A classic example of this kind of study in mathematics education was reported by William Brownell and Harold Moser in 1949 . They were trying to establish which method of subtracting whole numbers could be taught most effectively—the regrouping method or the equal additions method. However, they realized that effectiveness might depend on the conditions under which the methods were taught—“meaningfully” versus “mechanically.” So, they designed a study that crossed the two instructional approaches with the two different methods (regrouping and equal additions). Among other results, they found that these conditions did matter. The regrouping method was more effective under the meaningful condition than the mechanical condition, but the same was not true for the equal additions algorithm.

What do education researchers want to understand? In our view, the ultimate goal of education is to offer all students the best possible learning opportunities. So, we believe the ultimate purpose of scientific inquiry in education is to develop understanding that supports the improvement of learning opportunities for all students. We say “ultimate” because there are lots of issues that must be understood to improve learning opportunities for all students. Hypotheses about many aspects of education are connected, ultimately, to students’ learning. For example, formulating and testing a hypothesis that preservice teachers need to engage in particular kinds of activities in their coursework in order to teach particular topics well is, ultimately, connected to improving students’ learning opportunities. So is hypothesizing that school districts often devote relatively few resources to instructional leadership training or hypothesizing that positioning mathematics as a tool students can use to combat social injustice can help students see the relevance of mathematics to their lives.

We do not exclude the importance of research on educational issues more removed from improving students’ learning opportunities, but we do think the argument for their importance will be more difficult to make. If there is no way to imagine a connection between your hypothesis and improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Notice that we said the ultimate goal of education is to offer all students the best possible learning opportunities. For too long, educators have been satisfied with a goal of offering rich learning opportunities for lots of students, sometimes even for just the majority of students, but not necessarily for all students. Evaluations of success often are based on outcomes that show high averages. In other words, if many students have learned something, or even a smaller number have learned a lot, educators may have been satisfied. The problem is that there is usually a pattern in the groups of students who receive lower quality opportunities—students of color and students who live in poor areas, urban and rural. This is not acceptable. Consequently, we emphasize the premise that the purpose of education research is to offer rich learning opportunities to all students.

One way to make sure you will be able to convince others of the importance of your study is to consider investigating some aspect of teachers’ shared instructional problems. Historically, researchers in education have set their own research agendas, regardless of the problems teachers are facing in schools. It is increasingly recognized that teachers have had trouble applying to their own classrooms what researchers find. To address this problem, a researcher could partner with a teacher—better yet, a small group of teachers—and talk with them about instructional problems they all share. These discussions can create a rich pool of problems researchers can consider. If researchers pursued one of these problems (preferably alongside teachers), the connection to improving learning opportunities for all students could be direct and immediate. “Grounding a research question in instructional problems that are experienced across multiple teachers’ classrooms helps to ensure that the answer to the question will be of sufficient scope to be relevant and significant beyond the local context” (Cai et al., 2019b , p. 115).

As a beginning researcher, determining the relevance and importance of a research problem is especially challenging. We recommend talking with advisors, other experienced researchers, and peers to test the educational importance of possible research problems and topics of study. You will also learn much more about the issue of research importance when you read Chap. 5 .

Exercise 1.7

Identify a problem in education that is closely connected to improving learning opportunities and a problem that has a less close connection. For each problem, write a brief argument (like a logical sequence of if-then statements) that connects the problem to all students’ learning opportunities.

Part III. Conducting Research as a Practice of Failing Productively

Scientific inquiry involves formulating hypotheses about phenomena that are not fully understood—by you or anyone else. Even if you are able to inform your hypotheses with lots of knowledge that has already been accumulated, you are likely to find that your prediction is not entirely accurate. This is normal. Remember, scientific inquiry is a process of constantly updating your thinking. More and better information means revising your thinking, again, and again, and again. Because you never fully understand a complicated phenomenon and your hypotheses never produce completely accurate predictions, it is easy to believe you are somehow failing.

The trick is to fail upward, to fail to predict accurately in ways that inform your next hypothesis so you can make a better prediction. Some of the best-known researchers in education have been open and honest about the many times their predictions were wrong and, based on the results of their studies and those of others, they continuously updated their thinking and changed their hypotheses.

A striking example of publicly revising (actually reversing) hypotheses due to incorrect predictions is found in the work of Lee J. Cronbach, one of the most distinguished educational psychologists of the twentieth century. In 1955, Cronbach delivered his presidential address to the American Psychological Association. Titling it “Two Disciplines of Scientific Psychology,” Cronbach proposed a rapprochement between two research approaches—correlational studies that focused on individual differences and experimental studies that focused on instructional treatments controlling for individual differences. (We will examine different research approaches in Chap. 4 ). If these approaches could be brought together, reasoned Cronbach ( 1957 ), researchers could find interactions between individual characteristics and treatments (aptitude-treatment interactions or ATIs), fitting the best treatments to different individuals.

In 1975, after years of research by many researchers looking for ATIs, Cronbach acknowledged the evidence for simple, useful ATIs had not been found. Even when trying to find interactions between a few variables that could provide instructional guidance, the analysis, said Cronbach, creates “a hall of mirrors that extends to infinity, tormenting even the boldest investigators and defeating even ambitious designs” (Cronbach, 1975 , p. 119).

As he was reflecting back on his work, Cronbach ( 1986 ) recommended moving away from documenting instructional effects through statistical inference (an approach he had championed for much of his career) and toward approaches that probe the reasons for these effects, approaches that provide a “full account of events in a time, place, and context” (Cronbach, 1986 , p. 104). This is a remarkable change in hypotheses, a change based on data and made fully transparent. Cronbach understood the value of failing productively.

Closer to home, in a less dramatic example, one of us began a line of scientific inquiry into how to prepare elementary preservice teachers to teach early algebra. Teaching early algebra meant engaging elementary students in early forms of algebraic reasoning. Such reasoning should help them transition from arithmetic to algebra. To begin this line of inquiry, a set of activities for preservice teachers were developed. Even though the activities were based on well-supported hypotheses, they largely failed to engage preservice teachers as predicted because of unanticipated challenges the preservice teachers faced. To capitalize on this failure, follow-up studies were conducted, first to better understand elementary preservice teachers’ challenges with preparing to teach early algebra, and then to better support preservice teachers in navigating these challenges. In this example, the initial failure was a necessary step in the researchers’ scientific inquiry and furthered the researchers’ understanding of this issue.

We present another example of failing productively in Chap. 2 . That example emerges from recounting the history of a well-known research program in mathematics education.

Making mistakes is an inherent part of doing scientific research. Conducting a study is rarely a smooth path from beginning to end. We recommend that you keep the following things in mind as you begin a career of conducting research in education.

First, do not get discouraged when you make mistakes; do not fall into the trap of feeling like you are not capable of doing research because you make too many errors.

Second, learn from your mistakes. Do not ignore your mistakes or treat them as errors that you simply need to forget and move past. Mistakes are rich sites for learning—in research just as in other fields of study.

Third, by reflecting on your mistakes, you can learn to make better mistakes, mistakes that inform you about a productive next step. You will not be able to eliminate your mistakes, but you can set a goal of making better and better mistakes.

Exercise 1.8

How does scientific inquiry differ from everyday learning in giving you the tools to fail upward? You may find helpful perspectives on this question in other resources on science and scientific inquiry (e.g., Failure: Why Science is So Successful by Firestein, 2015).

Exercise 1.9

Use what you have learned in this chapter to write a new definition of scientific inquiry. Compare this definition with the one you wrote before reading this chapter. If you are reading this book as part of a course, compare your definition with your colleagues’ definitions. Develop a consensus definition with everyone in the course.

Part IV. Preview of Chap. 2

Now that you have a good idea of what research is, at least of what we believe research is, the next step is to think about how to actually begin doing research. This means how to begin formulating, testing, and revising hypotheses. As for all phases of scientific inquiry, there are lots of things to think about. Because it is critical to start well, we devote Chap. 2 to getting started with formulating hypotheses.

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). What Is Research, and Why Do People Do It?. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_1

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1 Shifting your Mindset: Thinking Like a Researcher

There is a stark difference between being a ‘consumer’ of research and an ‘author’ of research. That is, although a reader may look at a research article and glean insight for application to their own practice, the reader relies upon the integrity of both the author, or authors, as well as in the rigor of the journal such that the information presented is accurate enough to be made public and hopefully, adapted. The critical reader will begin to understand that the ‘process’ of research informs the practice of ‘doing’. The novice researcher will begin to apply those processes to investigation of focused inquiry.

So, as you’ve made it this far, it’s likely safe to say that you’re interested in evolving past a simple consumer of research and are interested in understanding the process further, maybe even design and implement your own research? First thing is first: You’ll need to shift your perspective from, ‘I want answers’ to ‘I have a question’.

Chapter 1: Learning Objectives

As you work to shift your perspective from research consumer to research contributor, you’ll be able to do the following things:

• Identify the steps of the research process
• Describe the difference between a statement of purpose and a problem statement
• Discuss how to articulate a research question
• Describe the basic considerations for selecting a research approach

Understanding the Research Process

What goes into pursuing inquiry? This will depend on YOU and the orientation of your interest. That is, there are several factors which will influence your ability to conduct an investigation. Below is a list of broad steps and goals to consider as you begin to ‘think like a researcher’:

• Determine an area of interest

Chances are that you’re drawn to a specific subject area because of something that you’re currently doing or because of something that has impacted you personally. It may even be a topic that you’re genuinely interested in exploring further. Regardless of the subject matter, it is imperative that you take a systematic approach to your investigation so as not to get lost in the sheer volume of information available to you.

• Identify your orientation of interest

We’ve established that your interest in a subject is rooted to a connection which drives your interest. Next, you’ll need to consider your perspective on the information and discern how your perspective may influence your approach to the research. That is, our biases, either implicit or explicit, have a definite impact on how we approach and utilize the evidence.

• Start digging!

Although a strong and clear interest is important, you do not want to waste time doing work which has already been done. Your goal as an emerging researcher is to ADD to, or build upon, the evidentiary basis of a topic of interest. The best way to narrow the scope of your interest is to thoroughly review the existing literature on your topic of interest to see what has already been discovered and to identify the spot in which your interests align with a gap in the knowledge about the topic.

• Gather information

As you sift through the literature available which pertains to your topic of interest, you will want to have several goals in mind. First, you will want to get a sense for what has already been discovered or is general knowledge about the topic. This foundational reading will serve as the framework for your general understanding about the topic. As you build both a breadth and depth of understanding, you’ll likely begin to notice patterns in the literature.

Goal: Determine a problem . What still needs to be answered in the area you’re interested in? What can you do to address this gap?

As you read through the literature, you’ll likely start to have more questions than answers. This is normal! However, keep in mind your scope of interest. For example, if you are interested in the rates of depression among post-partum mothers of very premature infants, spending time reading about the rates of depression in traveling salesmen isn’t going to be overly helpful and may actually distract you from finding the information you’re looking for. If you’re having a hard time finding information about what you’re looking for… You’ve already found the problem! That is, perhaps there hasn’t been enough work done to establish an understanding about post-partum depression in this particular subgroup of individuals.

The information you gather will help you develop a problem statement, a purpose statement, and articulate a research question.

A problem statement is a literature-based concern that is applicable to a wide audience (e.g. a profession). A problem statement is NOT a situation which comes from personal experience. Problem statements should include:

• The problem itself
• Who will use the information and why it is important?
• How your study will address the problem?

How Should a Problem Statement Be Articulated?

Developing a purpose statement can be a difficult concept. In a nutshell, the purpose statement is your opportunity to tell the audience how your work will address the problem. Typically, the purpose statement follows the problem statement and should include:

• Study design ( HOW ): In very few words, the reader should get a sense of how you are performing this work.
• Intent ( WHY ): T he reader should clearly understand why this work is being done.
• Variables or Phenomenon ( WHAT ): The reader should understand what, specifically, is being studied in relation to why. Here is where you have to separate constructs from variables. Constructs are ideas or concepts which are not always (but may be) directly measurable. Rather than measuring ‘constructs’, we search for proxies; or ways to represent a construct. One way we can do this is by identifying variables which measure the construct. A variable is a measurable representation of a construct. An important concept here is that a variable must vary . That is, there must be at least two levels measured for any one variable. An Independent Variable a variable that may explain another variable (AKA: Impact Variables). When you consider the ‘independence’ of a variable, you must consider how much control can be exerted over the variable. A Dependent Variable is a variable that is explained BY other variables (AKA: Outcome Variables). Other Variables: Mediating variables are variables that are explained by both independent and dependent variables. Moderating variables are variables which influence the relationship between the independent and dependent variables. Control variables are variables which may have an impact on the dependent variable but does not help to explain the dependent variable.
• Participants (WHO): The reader should have a grasp on who this work will pertain to. That is, a  population describes the entirety of the group you want to draw conclusions about whereas a  sample is the specific group that you will actually draw conclusions about.  Therefore, a sample will always be smaller than the population and the goal is that the findings relating to your sample are generalizable to the population.
• The environment in which the investigation will take place
• The access you have to the sample you wish to investigate
• The type of data you will collect
• The institutional-specific requirements of the research process

Developing a Quantitative Purpose Statement (Creswell & Creswel, 2018, p. 119 as cited in Gliner et al. 2017)

The purpose of this _____ (design) study is to ______(test or describe) the theory of ________, which _________(describes, compares, or relates) the ______________(independent variable) with ____________(Dependent variable), Controlling for ___________(name the control variables if appropriate) for________________(Participants) at _________________(Site). The independent variables are generally defined as  ____________(general definition). The dependent variables are generally defined as _____________(General definition). The  control and intervening variables, ______________(identify if appropriate), will be statistically controlled in the study.

Developing a Qualitative Purpose Statement (Creswell & Creswel, 2018, p. 124 as cited in Gliner et al. 2017)

Now, it may seem as though you’ve spelled things out for your reader; however, you’ve still not actually stated the question you have; your research question . The type of question will help identify what information should be articulated in the question as well as help describe what approach you will take to answer the question.

A well-defined research question should:

• Frame the focus of the study: Stating explicitly the ‘what’, ‘who’, ‘why’, ‘how’, and perhaps even ‘where’ the attention of the work will be focused.
• Set the boundaries of the study to establish scope: Using definitive words will help your reader understand how they will be able to generalize your work to their specific interests.
• Point you toward data needed to answer the question : Although not usually explicitly stated within the question, how you phrase your question should allude to the approach that you are taking and therefore, infer the type of data which will be discussed.

Quantitative Research Questions

Quantitative  approaches are those which make comparisons or examine relationships between or among variables. These types of questions include words like ’cause’, ‘relate’, ‘relationship’, or ‘association’

• Is there a relationship between depression scores on the XYZ scale and mothers who have premature infants born at 28 weeks gestation or fewer?

Quantitative approaches are deductive forms of inquiry where variables are measured using using objective statistical methods to either describe or generalize results.

Qualitative Research Questions

Qualitative approaches are those where the intention is to explore, discover, or describe an experience or phenomenon. These types of approaches include words like ‘how’ or ‘what’.

• What is the experience of mothers of infants born at 28 weeks gestation or fewer with depression-like symptoms?

Qualitative approaches are inductive forms of inquiry where variables are measured using more subjective measures that often generate non-numeric data and rely upon educated interpretation for analysis.

Overall, your main goal in developing a problem statement, a purpose statement, and a well described question is to first, define the scope of your work and how it fills the gap in understanding you found while digging through the existing research. In working to fill this gap and defining the scope of your work in the context of your gap, clearly delineating your problem, purpose, and question will help guide your approach.

5. Establish the context

We’ve discussed the need to understand the orientation of your inquiry from your perspective. Another important step is to determine whether there is a theoretical or contextual framework which will guide your work. A theory is a method of explaining some ‘thing’; a behavior, event, or phenomenon. That is, it’s a system of interrelated constructs which explain a phenomenon in a bounded system. Theories provide the logic of an observation by explaining what the key drivers and outcomes of a phenomenon are. Theories also help us make sense of an observation by incorporating empirical evidence and comparing outliers to that evidence and provide the foundation for future research by examining the gaps among the relationships and guiding insight about how to address those gaps. Theory works in parallel with empirical work to reconcile the concept with the evidence

6. Establish the ‘HOW’

Are you planning no observing and describing something objectively? Or, are you planning to be involved with the subjects? Also, something to consider: What is your main goal? That is, are you testing a theory (Positivist)? Or hoping to build a theory (Interpretive)? Are you seeking to test a hypothesis about causal relationships (Experimental)? Or simply describing characteristics or relationships between things (Non-Experimental)? Understanding your end goal will help you to design the best way to answer your research question.

Your approach will become your blueprint for the research process. Identifying ‘WHAT’ you are studying will help to guide the ‘HOW’ of your research. Here is a description of several methods which will help inform ‘HOW’ you pursue an answer to your research question:

• Laboratory experiments
• Survey research
• Action research
• Ethnography

As you work to identify both your ‘what’ and your ‘how’, it is helpful to understand what types of studies are common throughout your field of inquiry. As you review the literature, take a look at the methods by which the authors have generated their results and take note. Can you utilize similar methods? Or, are you wanting to take a completely different approach? As Jhangiani et al, (n.d.) identify, there are three overarching approaches to research:

• Experimental: Researchers who want to test hypotheses about causal relationships between variables (i.e., their goal is to explain) need to use an experimental method. This is because the experimental method is the only method that allows us to determine causal relationships. Using the experimental approach, researchers first manipulate one or more variables while attempting to control extraneous variables, and then they measure how the manipulated variables affect participants’ responses.
• Quasi Experimental: This design is similar to the experimental design; however, participant assignment is not random.
• Non-Experimental: Researchers who are simply interested in describing characteristics of people, describing relationships between variables, and using those relationships to make predictions can use non-experimental research. Using the non-experimental approach, the researcher simply measures variables as they naturally occur, but they do not manipulate them. For instance, if I just measured the number of traffic fatalities in America last year that involved the use of a cell phone but I did not actually manipulate cell phone use then this would be categorized as non-experimental research. Alternatively, if I stood at a busy intersection and recorded drivers’ genders and whether or not they were using a cell phone when they passed through the intersection to see whether men or women are more likely to use a cell phone when driving, then this would be non- experimental research. It is important to point out that non-experimental does not mean nonscientific. Non-experimental research is scientific in nature. It can be used to fulfill two of the three goals of science (to describe and to predict). However, unlike with experimental research, we cannot make causal conclusions using this method; we cannot say that one variable causes another variable using this method.

Understanding your approach will help identify what kind of data you will be collecting and what you will do what that data. As you consider your approach you will need to consider how sound your research approach is. That is, you’ll need to consider how well your study is designed to glean insight that truly represents the behavior, process, or phenomenon that you’re investigating. This is where validity comes into play.  Although the concept of validity is quite extensive, the two primary types of validity you should be concerned with here are internal and external validity.

• Internal Validity :   Refers to the degree to which we can confidently infer a causal relationship between variables. When we conduct an experimental study in a laboratory environment we have very high internal validity because we manipulate one variable while controlling all other outside extraneous variables. When we manipulate an independent variable and observe an effect on a dependent variable and we control for everything else so that the only difference between our experimental groups or conditions is the one manipulated variable then we can be quite confident that it is the independent variable that is causing the change in the dependent variable. In contrast, because field studies are conducted in the real-world, the experimenter typically has less control over the environment and potential extraneous variables, and this decreases internal validity, making it less appropriate to arrive at causal conclusions.
• External Validity : Refers to the degree to which we can generalize the findings to other circumstances or settings, like the real- world environment. When internal validity is high, external validity tends to be low; and when internal validity is low, external validity tends to be high. So laboratory studies are typically low in external validity, while field studies are typically high in external validity. Since field studies are conducted in the real-world environment it is far more appropriate to generalize the findings to that real-world environment than when the research is conducted in the more artificial sterile laboratory.

7. Gather and analyze your data 

Once your study is complete and the observations have been made and recorded, researchers need to analyze the data and draw conclusions. Typically, data are analyzed using both descriptive and inferential statistics. Descriptive statistics are used to summarize the data and inferential statistics are used to generalize the results from the sample to the population. In turn, inferential statistics are used to make conclusions about whether or not a theory has been supported, refuted, or requires modification.

Descriptive Statistics

Descriptive statistics are used to organize or summarize a set of data. Examples include percentages, measures of central tendency (mean, median, mode), measures of dispersion (range, standard deviation, variance), and correlation coefficients.

Measures of central tendency are used to describe the typical, average and center of a distribution of scores. The mode is the most frequently occurring score in a distribution. The median is the midpoint of a distribution of scores. The mean is the average of a distribution of scores.

Measures of dispersion are also considered descriptive statistics. They are used to describe the degree of spread in a set of scores. So are all of the scores similar and clustered around the mean or is there a lot of variability in the scores? The range is a measure of dispersion that measures the distance between the highest and lowest scores in a distribution. The standard deviation is a more sophisticated measure of dispersion that measures the average distance of scores from the mean. The variance is just the standard deviation squared. So it also measures the distance of scores from the mean but in a different unit of measure.

Typically means and standard deviations are computed for experimental research studies in which an independent variable was manipulated to produce two or more groups and a dependent variable was measured quantitatively. The means from each experimental group or condition are calculated separately and are compared to see if they differ.

For non-experimental research, simple percentages may be computed to describe the percentage of people who engaged in some behavior or held some belief. But more commonly non-experimental research involves computing the correlation between two variables. A correlation coefficient describes the strength and direction of the relationship between two variables. The values of a correlation coefficient can range from −1.00 (the strongest possible negative relationship) to +1.00 (the strongest possible positive relationship). A value of 0 means there is no relationship between the two variables. Positive correlation coefficients indicate that as the values of one variable increase, so do the values of the other variable. A good example of a positive correlation is the correlation between height and weight, because as height increases weight also tends to increase. Negative correlation coefficients indicate that as the value of one variable increase, the values of the other variable decrease. An example of a negative correlation is the correlation between stressful life events and happiness; because as stress increases, happiness is likely to decrease.

Inferential Statistics

As you learned in the section of this chapter on sampling, typically researchers sample from a population but ultimately they want to be able to generalize their results from the sample to a broader population. Researchers typically want to infer what the population is like based on the sample they studied. Inferential statistics are used for that purpose. Inferential statistics allow researchers to draw conclusions about a population based on data from a sample. Inferential statistics are crucial because the effects (i.e., the differences in the means or the correlation coefficient) that researchers find in a study may be due simply to random chance variability or they may be due to a real effect (i.e., they may reflect a real relationship between variables or a real effect of an independent variable on a dependent variable).

Researchers use inferential statistics to determine whether their effects are statistically significant. A statistically significant effect is one that is unlikely due to random chance and therefore likely represents a real effect in the population. More specifically results that have less than a 5% chance of being due to random error are typically considered statistically significant. When an effect is statistically significant it is appropriate to generalize the results from the sample to the population. In contrast, if inferential statistics reveal that there is more than a 5% chance that an effect could be due to chance error alone then the researcher must conclude that their result is not statistically significant.

It is important to keep in mind that statistics are probabilistic in nature. They allow researchers to determine whether the chances are low that their results are due to random error, but they don’t provide any absolute certainty. Hopefully, when we conclude that an effect is statistically significant it is a real effect that we would find if we tested the entire population. And hopefully when we conclude that an effect is not statistically significant there really is no effect and if we tested the entire population we would find no effect. And that 5% threshold is set at 5% to ensure that there is a high probability that we make a correct decision and that our determination of statistical significance is an accurate reflection of reality.

But mistakes can always be made. Specifically, two kinds of mistakes can be made. First, researchers can make a Type I error , which is a false positive. This happens when a researcher concludes that their results are statistically significant (there IS an effect in the population) when in reality there is no effect in the population and the results are just due to chance (that is, they are a fluke). When the significance threshold is set to 5%, which is the convention, the boundaries for making a Type I error are 5% chance or less. You might wonder why researchers don’t set it even lower to reduce the chances of making a Type I error. The reason is because when the chances of making a Type I error are reduced, the chances of making a Type II error are increased. A Type II error can be considered a ‘missed opportunity’. This happens when a researcher concludes that their results are not statistically significant when in reality, there IS an effect in the population and they just missed detecting it. Once again, these Type II errors are more likely to occur when the threshold is set too low (e.g., set at 1% instead of 5%) and/or when the sample was too small.

8. Determine how your findings fit into the knowledge base

Since statistics are probabilistic in nature and findings can reflect both Type I or Type II errors, we cannot use the results of a single study to conclude with certainty that a theory is true. Rather theories are supported, refuted, or modified based on the results of research.

If the results are statistically significant and consistent with the hypothesis and the theory that was used to generate the hypothesis, then researchers can conclude that the theory is supported. Not only did the theory make an accurate prediction, but there is now a new phenomenon that the theory accounts for. If a hypothesis is disconfirmed in a systematic empirical study, then the theory has been weakened. It made an inaccurate prediction, and there is now a new phenomenon that it does not account for.

Although this seems straightforward, there are some complications. First, confirming a hypothesis can strengthen a theory but it can never prove a theory. In fact, scientists tend to avoid the word “prove” when talking and writing about theories. One reason for this avoidance is that the result may reflect a type I error. Another reason for this avoidance is that there may be other plausible theories that imply the same hypothesis, which means that confirming the hypothesis strengthens all those theories equally. A third reason is that it is always possible that another test of the hypothesis or a test of a new hypothesis derived from the theory will be disconfirmed. This difficulty is a version of the famous philosophical “problem of induction.” One cannot definitively prove a general principle (e.g., “All swans are white.”) just by observing confirming cases (e.g., white swans)—no matter how many. It is always possible that a disconfirming case (e.g., a black swan) will eventually come along. For these reasons, scientists tend to think of theories—even highly successful ones—as subject to revision based on new and unexpected observations.

A second complication has to do with what it means when a hypothesis is disconfirmed. According to the strictest version of the hypothetico-deductive method, disconfirming a hypothesis disproves the theory it was derived from. In formal logic, the premises “if A then B ” and “not B ” necessarily lead to the conclusion “not A .” If A is the theory and B is the hypothesis (“if A then B ”), then disconfirming the hypothesis (“not B ”) must mean that the theory is incorrect (“not A ”). In practice, however, scientists do not give up on their theories so easily. One reason is that one disconfirmed hypothesis could be a missed opportunity (the result of a type II error) or it could be the result of a faulty research design. Perhaps the researcher did not successfully manipulate the independent variable or measure the dependent variable.

A disconfirmed hypothesis could also mean that some unstated but relatively minor assumption of the theory was not met. For example, if Zanib had failed to find social facilitation in cockroaches, he could have concluded that drive theory is still correct but it applies only to animals with sufficiently complex nervous systems. That is, the evidence from a study can be used to modify a theory. This practice does not mean that researchers are free to ignore disconfirmations of their theories. If they cannot improve their research designs or modify their theories to account for repeated disconfirmations, then they eventually must abandon their theories and replace them with ones that are more successful.

The bottom line here is that because statistics are probabilistic in nature and because all research studies have flaws there is no such thing as scientific proof, there is only scientific evidence.

9. Prepare for dissemination

The final step in the research process involves reporting the results. As described earlier in this chapter, results are typically reported in peer-reviewed journal articles and at conferences.

As Jhangiani et al (n.d.) mention, the most prestigious way to report one’s findings is by writing a manuscript and having it published in a peer-reviewed scientific journal. Manuscripts may be published several different types of journals. Formatting standards of the publication will depend on the professional focus. It is likely that you’ll need to review the formatting guidelines of the journal carefully prior to submitting your manuscript to ensure that you’ve addressed each specification.

Typically, a well-developed manuscript will have the following components:

• Introduction
• Literature review or thematic constructs
• Data analysis
• Limitations

Another way to report findings is by writing a book chapter that is published in an edited book. Preferably the editor of the book puts the chapter through peer review but this is not always the case and some scientists are invited by editors to write book chapters.

A fun way to disseminate findings is to give a presentation at a conference. This can either be done as an oral presentation or a poster presentation. Oral presentations involve getting up in front of an audience of fellow scientists and giving a talk that might last anywhere from 10 minutes to 1 hour (depending on the conference) and then fielding questions from the audience. Alternatively, poster presentations involve summarizing the study on a large poster that provides a brief overview of the purpose, methods, results, and discussion. The presenter stands by their poster for an hour or two and discusses it with people who pass by. Presenting one’s work at a conference is a great way to get feedback from one’s peers before attempting to undergo the more rigorous peer-review process involved in publishing a journal article.

There’s a lot to consider when you enter the world of research. However, as with most things, practice makes perfect, or at least a 95% chance of success (see what I did there?). As you move forward in this book, or simply refer back to this chapter, here are some things to remember:

• Moving from research consumer to research contributor requires a shift in mindset from ‘I want answers’ to ‘I have a question’.
• The process of research is not always linear. Rather, depending on the breadth and depth of your investigation, you may find yourself back at the beginning several times. The process of identifying a research problem, purpose, and question is an iterative process.
• Determining an area of interest
• Determining your orientation to that interest
• Digging through the existing base of literature related to your interest
• A problem statement
• A purpose statement
• A research question
• Establishing the context for your research
• Establishing the ‘HOW’
• Gathering and analyzing your data
• Determining how your findings fit into the base of knowledge
• Preparing to disseminate your work to add to the base of knowledge
• The content in this section is attributed to: Research Methods in Psychology by Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted. ↵
• Some of the content in this section is attributed to: Research Methods in Psychology by Rajiv S. Jhangiani, I-Chant A. Chiang, Carrie Cuttler, & Dana C. Leighton is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License, except where otherwise noted ↵

A literature-based concern that is applicable to a wide-audience (e.g. a profession)

A statement which summarizes how your work will address the problem you've identified

Ideas or concepts which are not directly measurable

A measurable representation of an abstract construct

A variable that can explain another variable. A variable which may be manipulated (active) or describes (attribute) to affect an outcome

The variable which is measured as an outcome and is affected by the independent variable(s)

Variables that are explained by both the independent and dependent variables

A variable which has an impact on the dependent variable, but does not explain the outcome (dependent variable)

The ENTIRE group you wish to study

A smaller subgroup of the population that you want to study. Ideally, the sample selected is representative of the population

The articulation of your inquiry. A focused representation of what you hope to find with your investigation.

An approach which seeks to make comparisons or search for relationships between variables.

An approach that seeks to explore or describe an experience, usually with subjective measurement tools.

An educated method of explaining or rationalizing something

How accurately a method measures what it is intended to measure

The degree to which we can confidently infer a causal relationship between variables

The degree to which the results can be generalized beyond the context of the specific study.

Statistical approaches which summarize or describe the data

Statistical approaches that draw inference from the sample to the population

Most frequently occurring score in a distribution

Midpoint of all scores within a data set

The average of a distribution

Measures the distance between the highest and lowest scores of a distribution

Distance of scores from the mean

Describes the strength and direction of the relationship between two variables

A set threshold at which a result of a statistical test is unlikely to be due to random chance

A false positive result. Identifying a significance when there is NOT significance

Not identifying significance where significance exists

Practical Research: A Basic Guide to Planning, Doing, and Writing Copyright © by megankoster. All Rights Reserved.

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Home Market Research

What is Research: Definition, Methods, Types & Examples

The search for knowledge is closely linked to the object of study; that is, to the reconstruction of the facts that will provide an explanation to an observed event and that at first sight can be considered as a problem. It is very human to seek answers and satisfy our curiosity. Let’s talk about research.

Content Index

What is Research?

What are the characteristics of research.

• Comparative analysis chart

Qualitative methods

Quantitative methods, 8 tips for conducting accurate research.

Research is the careful consideration of study regarding a particular concern or research problem using scientific methods. According to the American sociologist Earl Robert Babbie, “research is a systematic inquiry to describe, explain, predict, and control the observed phenomenon. It involves inductive and deductive methods.”

Inductive methods analyze an observed event, while deductive methods verify the observed event. Inductive approaches are associated with qualitative research , and deductive methods are more commonly associated with quantitative analysis .

Research is conducted with a purpose to:

• Identify potential and new customers
• Understand existing customers
• Set pragmatic goals
• Develop productive market strategies
• Address business challenges
• Put together a business expansion plan
• Identify new business opportunities
• Good research follows a systematic approach to capture accurate data. Researchers need to practice ethics and a code of conduct while making observations or drawing conclusions.
• The analysis is based on logical reasoning and involves both inductive and deductive methods.
• Real-time data and knowledge is derived from actual observations in natural settings.
• There is an in-depth analysis of all data collected so that there are no anomalies associated with it.
• It creates a path for generating new questions. Existing data helps create more research opportunities.
• It is analytical and uses all the available data so that there is no ambiguity in inference.
• Accuracy is one of the most critical aspects of research. The information must be accurate and correct. For example, laboratories provide a controlled environment to collect data. Accuracy is measured in the instruments used, the calibrations of instruments or tools, and the experiment’s final result.

What is the purpose of research?

There are three main purposes:

• Exploratory: As the name suggests, researchers conduct exploratory studies to explore a group of questions. The answers and analytics may not offer a conclusion to the perceived problem. It is undertaken to handle new problem areas that haven’t been explored before. This exploratory data analysis process lays the foundation for more conclusive data collection and analysis.

LEARN ABOUT: Descriptive Analysis

• Descriptive: It focuses on expanding knowledge on current issues through a process of data collection. Descriptive research describe the behavior of a sample population. Only one variable is required to conduct the study. The three primary purposes of descriptive studies are describing, explaining, and validating the findings. For example, a study conducted to know if top-level management leaders in the 21st century possess the moral right to receive a considerable sum of money from the company profit.

LEARN ABOUT: Best Data Collection Tools

• Explanatory: Causal research or explanatory research is conducted to understand the impact of specific changes in existing standard procedures. Running experiments is the most popular form. For example, a study that is conducted to understand the effect of rebranding on customer loyalty.

Here is a comparative analysis chart for a better understanding:

It begins by asking the right questions and choosing an appropriate method to investigate the problem. After collecting answers to your questions, you can analyze the findings or observations to draw reasonable conclusions.

When it comes to customers and market studies, the more thorough your questions, the better the analysis. You get essential insights into brand perception and product needs by thoroughly collecting customer data through surveys and questionnaires . You can use this data to make smart decisions about your marketing strategies to position your business effectively.

To make sense of your study and get insights faster, it helps to use a research repository as a single source of truth in your organization and manage your research data in one centralized data repository .

Types of research methods and Examples

Research methods are broadly classified as Qualitative and Quantitative .

Both methods have distinctive properties and data collection methods .

Qualitative research is a method that collects data using conversational methods, usually open-ended questions . The responses collected are essentially non-numerical. This method helps a researcher understand what participants think and why they think in a particular way.

Types of qualitative methods include:

• One-to-one Interview
• Focus Groups
• Ethnographic studies
• Text Analysis

Quantitative methods deal with numbers and measurable forms . It uses a systematic way of investigating events or data. It answers questions to justify relationships with measurable variables to either explain, predict, or control a phenomenon.

Types of quantitative methods include:

• Survey research
• Descriptive research
• Correlational research

LEARN MORE: Descriptive Research vs Correlational Research

Remember, it is only valuable and useful when it is valid, accurate, and reliable. Incorrect results can lead to customer churn and a decrease in sales.

It is essential to ensure that your data is:

• Valid – founded, logical, rigorous, and impartial.
• Accurate – free of errors and including required details.
• Reliable – other people who investigate in the same way can produce similar results.
• Timely – current and collected within an appropriate time frame.
• Complete – includes all the data you need to support your business decisions.

Gather insights

• Identify the main trends and issues, opportunities, and problems you observe. Write a sentence describing each one.
• Keep track of the frequency with which each of the main findings appears.
• Make a list of your findings from the most common to the least common.
• Evaluate a list of the strengths, weaknesses, opportunities, and threats identified in a SWOT analysis .
• Prepare conclusions and recommendations about your study.
• Act on your strategies
• Look for gaps in the information, and consider doing additional inquiry if necessary
• Plan to review the results and consider efficient methods to analyze and interpret results.

Review your goals before making any conclusions about your study. Remember how the process you have completed and the data you have gathered help answer your questions. Ask yourself if what your analysis revealed facilitates the identification of your conclusions and recommendations.

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What is useful research? The good, the bad, and the stable

David m. ozonoff.

1 Department of Environmental Health, Boston University School of Public Health, Boston, MA USA

Philippe Grandjean

2 Department of Environmental Medicine, University of Southern Denmark, Odense, Denmark

3 Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA USA

Associated Data

A scientific journal like Environmental Health strives to publish research that is useful within the field covered by the journal’s scope, in this case, public health. Useful research is more likely to make a difference. However, in many, if not most cases, the usefulness of an article can be difficult to ascertain until after its publication. Although replication is often thought of as a requirement for research to be considered valid, this criterion is retrospective and has resulted in a tendency toward inertia in environmental health research. An alternative viewpoint is that useful work is “stable”, i.e., not likely to be soon contradicted. We present this alternative view, which still relies on science being consensual, although pointing out that it is not the same as replicability, while not in contradiction. We believe that viewing potential usefulness of research reports through the lens of stability is a valuable perspective.

Good science as a purpose

Any scientific journal wishes to add to the general store of knowledge. For Environmental Health, an additional important goal is also to publish research that is useful for public health. While maximizing scientific validity is an irreducible minimum for any research journal, it does not guarantee that the outcome of a “good” article is useful. Most writing on this subject concerns efficiencies and criteria for generating new and useful research results while avoiding “research waste” [ 1 ]. In this regard, the role of journals is hard to define. Indeed, a usefulness objective depends upon what happens after publication, thus to some extent being out of our control. That said, because of the importance of this issue the Editors have set out to clarify our thinking about what makes published research useful.

First the obvious: properly conducted scientific research may not be useful, or worse, may potentially mislead, confuse or be erroneously interpreted. Journal editors and reviewers can mitigate such regrettable outcomes by being attentive to faulty over- or under-interpretation of properly generated data, and vice versa, ensuring that unrealistic standards don’t prevent publication of a “good” manuscript. In regard to the latter, we believe our journal should not shy away from alternative or novel interpretations that may be counter to established paradigms and have consciously adopted a precautionary orientation [ 2 ]: We believe that it is reasonable to feature risks that may seem remote at the moment because the history of environmental and occupational health is replete with instances of red flags ignored, resulting in horrific later harms that could no longer be mitigated [ 3 , 4 ].

Nonetheless, it has happened that researchers publishing results at odds with vested interests have become targets of unreasonable criticism and intimidation whose aim is to suppress or throw suspicion on unwelcome research information, as in the case of lead [ 3 , 5 ] and many other environmental chemicals [ 6 ]. An alternative counter strategy is generating new results favorable to a preferred view [ 7 , 8 ], with the objective of casting doubt on the uncomfortable research results. Indeed, one trade association involved in supporting such science once described its activities with the slogan, “Doubt is our product” [ 9 ]. Thus, for better or for worse, many people do not separate science, whether good or bad, from its implications [ 10 ].

Further, even without nefarious reasons, it is not uncommon for newly published research to be contradicted by additional results from other scientists. Not surprisingly, the public has become all too aware of findings whose apparent import is later found to be negligible, wrong, or cast into serious doubt, legitimately or otherwise [ 11 ]. This has been damaging to the discipline and its reputation [ 12 ].

Replication as a criterion

A principal reaction to this dilemma has been to demand that results be “replicated” before being put to use. As a result, both funding agencies [ 13 ] and journals [ 14 ] have announced their intention of emphasizing the reproducibility of research, thereby also facilitating replication [ 15 ]. On its face this sounds reasonable, but usual experimental or observational protocols are already based on internal replication. If some form of replication of a study is desired, attempts to duplicate an experimental set-up can easily produce non-identical measurements on repeated samples, and seemingly similar people in a population may yield somewhat different observations. Given an expected variability within and between studies, we need to define more precisely what is to be replicated and how it is to be judged.

That said, in most instances, it seems that what we are really asking for is interpretive replication (i.e., do we think two or more studies mean the same thing), not observational or measurement replication. Uninterpreted evidence is just raw data. The main product of scientific journals like Environmental Health is interpreted evidence. It is interpreted evidence that is actionable and likely to affect practice and policy.

Research stability

This brings us back to the question of what kind of evidence and its accompanying interpretation is likely to be of use? The philosopher Alex Broadbent distinguishes between how results get used and the decision about which results are likely to be used [ 16 ]. Discussions of research translation tend to focus on the former question, while the latter is rarely discussed. Broadbent introduces a new concept into the conversation, the stability of the research results.

He begins by identifying which results are not likely to be used. Broadbent observes that if a practitioner or policy-maker thinks a result might soon be overturned she is unlikely to use it. Since continual revision is a hallmark of science, this presents a dilemma. All results are open to revision as science progresses, so what users and policy makers really want are stable results, ones whose meaning is unlikely to change in ways that make a potential practice or policy quickly obsolete or wrong. What are the features of a stable result?

This is a trickier problem than it first appears. As Broadbent observes it does not seem sufficient to say that a stable a result is one that is not contradicted by subsequent work, an idea closely related to replication. Failure to contradict, like lack of replication, may have many reasons, including lack of interest, lack of funding, active suppression of research in a subject, or external events like social conflict or recession. Moreover, there are many examples of clinical practice, broadly accepted as stable in the non-contradiction sense, that have not been tested for one reason or another. Contrariwise, contradictory results may also be specious or fraudulent, e.g., due to attempts to make an unwelcome result appear unstable and hence unusable [ 6 , 9 ]. In sum, lack of contradiction doesn’t automatically make a result stable, nor does its presence annul the result.

One might plausibly think that the apparent truth of a scientific result would be sufficient to make a result stable. This is also in accordance with Naomi Oreskes’ emphasis of scientific knowledge being fundamentally consensual [ 10 ] and relies on the findings being generalizable [ 15 ]. Our journal, like most, employs conventional techniques like pre-publication peer review and editorial judgment, to maximize scientific validity of published articles; and we require Conflict of Interest declarations to maximize scientific integrity [ 6 , 17 ]. Still, a result may be true but not useful, and science that isn’t true may be very useful. Broadbent’s example of the latter is the most spectacular. Newtonian physics continues to be a paragon of usefulness despite the fact that in the age of Relativity Theory we know it to be false. Examples are also prevalent in environmental health. When John Snow identified contaminated water as a source of epidemic cholera in the mid-nineteenth Century he believed a toxin was the cause, as the germ theory of disease had not yet found purchase. This lack of understanding did not stop practitioners from advocating limiting exposure to sewage-contaminated water. Nonetheless, demands for modes of action or adverse outcome pathways are often used to block the use of new evidence on environmental hazards [ 18 ].

Criteria for stability

Broadbent’s suggestion is that a result likely to be seen as stable by practitioners and policy makers is one that (a) is not contradicted by good scientific evidence; and (b) would not likely be soon contradicted by further good research [ 16 ] (p. 63).

The first requirement, (a), simply says that any research that produces contradictory evidence be methodologically sound and free from bias, i.e., “good scientific evidence.” What constitutes “good” scientific evidence is a well discussed topic, of course, and not a novel requirement [ 1 ], but the stability frame puts existing quality criteria, in a different, perhaps more organized, structure, situating the evidence and its interpretation in relation to stability as a criterion for usefulness.

More novel is requirement (b), the belief that if further research were done it would not likely result in a contradiction. The if clause focuses our attention on examining instances where the indicated research has not yet been done. The criterion is therefore prospective, where the replication demand can only be used in retrospect.

This criterion could usefully be applied to inconclusive or underpowered studies that are often incorrectly labeled “negative” and interpreted to indicate “no risk” [ 18 ]. A U.S. National Research Council committee called attention to the erroneous inference that chemicals are regarded inert or safe, unless proven otherwise [ 19 ]. This “untested-chemical assumption” has resulted in exposure limits for only a small proportion of environmental chemicals, limits often later found to be much too high to adequately protect against adverse health effects [ 20 , 21 ]. For example, some current limits for perfluorinated compounds in drinking water do not protect against the immunotoxic effects in children and may be up to 100-fold too high [ 22 ].

Inertia as a consequence

Journals play an unfortunate part in the dearth of critical information on emerging contaminants, as published articles primarily address chemicals that have already been well studied [ 23 ]. This means that environmental health research suffers from an impoverishing inertia, which may in part be due to desired replications that may be superfluous or worse. The bottom line is that longstanding acceptance in the face of longstanding failure to test a proposition should not be used as a criterion of stability or of usefulness, although this is routinely done.

If non-contradiction, replication or truth are not reliable hallmarks of a potentially useful research result, then what is? Broadbent makes the tentative proposal that a stable interpretation is one which has a satisfactory answer to the question, “Why this interpretation rather than another?” Said another way, are there more likely, almost or equally as likely, or other possible explanations (including methodological error in the work in question)? Sometimes the answer is patently obvious. Such an evaluation is superfluous in instances where the outcomes have such forceful explanations that this exercise would be a waste of time, for example a construction worker falling from the staging. We only need one instance and (hopefully no repetitions) to make the case.

Consensus and stability

Having made the argument for perspicuous interpretation, we must also issue a note of caution. It is quite common to err in the other direction by downplaying conclusions and implications. Researchers frequently choose to hedge their conclusions by repeated use of words such as ‘maybe’, ‘perhaps’, ‘in theory’ and similar terms [ 24 ]. Indeed, we might call the hedge the official flower of epidemiology. To a policy maker, journalist or member of the public not familiar with the traditions of scientific writing, the caveats and reservations may sound like the new results are irredeemably tentative, leaving us with no justification for any intervention. To those with a vested interest, the soft wording can be exploited through selective quotation and by emphasizing real or alleged weaknesses [ 25 ]. This tendency goes beyond one’s own writings and affects peer review and evaluations of manuscripts and applications. Although skepticism is in the nature of science, a malignant form is the one that is veiled and expressed in terms of need for further replication or emphasizing limitations of otherwise stable observations [ 9 ]. By softening the conclusions and avoiding attribution of specific causality and the possible policy implications, researchers protect themselves against critique by appearing well-balanced, unassuming, or even skeptical toward one’s own findings. In seeking consensus, researchers often moderate or underestimate their findings, a tendency that is not in accordance with public health interests.

These are difficult issues, requiring a balancing act. The Editors continue to ponder the question how to inspire, improve and support the best research and its translation. We believe Broadbent’s stability idea is worth considering as an alternative perspective to the replication and research translation paradigms prevalent in discussions of this topic. We also believe in Oreskes’ vision of consensus, though not to a degree that will preclude new interpretations. Meanwhile, we will endeavor to keep the Journal’s standards high while encouraging work that will make a difference.

Acknowledgements

Authors’ contributions.

DMO and PG jointly drafted the Editorial and read and approved the final version.

Availability of data and materials

Ethics approval and consent to participate, consent for publication, competing interests.

DMO and PG are editors-in-chief of this journal but have no other interests to declare.

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Office of Undergraduate Research

What i’ve learned through involvement in research, by kerry morgan, our peer research ambassador.

In my years at UConn, I have been involved in many different types of activities. Whether it be sports, academics, volunteering, hobbies, there is certainly something for everyone at UConn. As I am beginning my senior year at UConn, I look back and reflect on the time I have had here, and most importantly the things I’ve learned and enjoyed. Now, I can say with clarity that research shaped me into the person I am today, and it has been one of my most cherished experiences from my undergraduate education.

As a Freshman at UConn, I was much like any other student: starting new. I wanted to make the most out of my four years– as many others do– but I didn’t know how to yet. I joined numerous clubs, I volunteered, but getting involved in research seemed so unattainable. I wondered how people got involved and where they worked on research. What was I interested in researching? What if I’m not good at research? Where do I even begin? All these questions held me back until I finally decided to take the first step sophomore year. Since then, I have worked in three different labs– all in completely different fields. From kinesiology and human clinical research to genetic research of cerebellar development, I saw all different aspects of research. Not every experience is the same, but once you find what you are passionate about, you never look back!

Why did I get involved in research?

This is a question with a slightly different answer for everyone, and your answer may even change over time. Personally, I got involved in research to learn . Of course we all learn in our daily classes each semester, but learning about something new and completely unfamiliar is beyond exciting. It may be something you have long thought about or something completely new to you. Either way, research has a way of opening up a whole new world of ideas, thinking, and creativity. Before getting involved in research, I never could have imagined that I would have learned so much. Not just about science, but about how to think critically. Research has taught me how to problem solve, analyze, and think creatively.

What were my research goals and interests?

When I first thought about getting involved in research, I honestly had no idea what I was interested in. I figured “genetics” and “psychology” were two areas to start with, but at this point in my academic career, anything would have been exciting to me. As I got older and read more, I became fascinated by stem cell research, specifically relating to nerves and bones. I began applying to opportunities for summer research in hopes of finding a project that would fit my specific interests. Luckily, I came across HRP (Health Research Program) and found several faculty members at UConn Health that were working on orthopedic research and neuroscience research. I applied and interviewed with a variety of PI’s, but found that what I was most interested in was not what I had initially expected. After participating in HRP at Dr. James Li’s lab, I was certain I had found what I was truly interested in. One and a half years later, and I am still working on cerebellar research, which I would consider a combination of developmental biology, genetics, and neuroscience. I learned that it is ok to try new things, and maybe you will even surprise yourself by what you end up loving. Most importantly, you aren’t expected to know exactly what you love when you haven’t seen a fraction of what’s out there yet!

What have I learned from research?

This question is not a simple one, for I feel I have learned so many indescribable things from my research experiences.

First and foremost, I have learned to be confident. The trust and responsibility that my PI gave me right at the start boosted my confidence by a ten-fold. I felt that I was treated not like a student, but rather an equal. I was given every opportunity to contribute, present, and discuss in a manner that I had never been accustomed to before this experience. In addition, I felt accomplished after learning and mastering intricate lab tasks that I could never have imagined would be within my skillset as an undergrad.

As for everything else I learned in my research experience, it would probably be easier to list what I haven’t learned. The first few weeks at my current lab were beyond overwhelming. The rate of information being taken in was at an all-time high for me, and I felt I would never fully learn everything. But, slowly and surely, everything does come with ease. Repetition is the key to any success, and somehow I became familiar with concepts far beyond my years.

Every day in a lab is an opportunity to learn something. Whether it be procedural or conceptual, the potential is limitless. When I think back on my experience in research, it makes me quite proud thinking of where I started to what I have accomplished. It took a lot of hard work to get here, but it has been the most rewarding experience imaginable.

Kerry is a senior majoring in Molecular & Cell Biology and Allied Health Sciences. Click here to learn more about Kerry.