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How to Do Research

Last Updated: March 13, 2023 References

This article was co-authored by Matthew Snipp, PhD and by wikiHow staff writer, Jennifer Mueller, JD . C. Matthew Snipp is the Burnet C. and Mildred Finley Wohlford Professor of Humanities and Sciences in the Department of Sociology at Stanford University. He is also the Director for the Institute for Research in the Social Science’s Secure Data Center. He has been a Research Fellow at the U.S. Bureau of the Census and a Fellow at the Center for Advanced Study in the Behavioral Sciences. He has published 3 books and over 70 articles and book chapters on demography, economic development, poverty and unemployment. He is also currently serving on the National Institute of Child Health and Development’s Population Science Subcommittee. He holds a Ph.D. in Sociology from the University of Wisconsin—Madison. This article has been viewed 226,470 times.

The idea of doing research may seem daunting, but as long as you keep yourself organized and focus on the question you want to answer, you'll be fine. If you're curious and interested in the topic, you might even find it fun! We here at wikiHow have gathered answers to all your most common questions about how to do research, from finding a good topic to identifying the best sources and writing your final paper.

How do I find a topic to research?

• For example, if you're researching in the political science field, you might be interested in determining what leads people to believe that the 2020 US presidential election was illegitimate.

How do I get started on my research?

• For example, if you're researching the 2020 election, you might find that "absentee ballots" and "voting by mail" come up frequently. Those are issues you could look into further to figure out how they impacted the final election results.
• You don't necessarily have to use the overview articles you look at as resources in your actual paper. Even Wikipedia articles can be a good way to learn more about a topic and you can check the references for more reputable sources that might work for your paper.

What's the best way to keep track of my sources?

• Research papers typically discuss 2 or 3 separate things that work together to answer the research question. You might also want to make a note on the front of which thing that source relates to. That'll make it easier for you to organize your sources later.
• For example, if you're researching the 2020 election, you might have a section of your paper discussing voting by mail. For the sources that directly address that issue, write "voting by mail" in the corner.

What kind of notes should I be taking as I research?

• If you find something that you think would make a good quote, copy it out exactly with quote marks around it, then add the page number where it appears so you can correctly cite it in your paper without having to go back and hunt for it again.

How do I evaluate the quality of a source?

• Does the article discuss or reference another article? (If so, use that article instead.)
• What expertise or authority does the author have?
• When was the material written? (Is it the most up-to-date reference you could use?)
• Why was the article published? (Is it trying to sell you something or persuade you to adopt a certain viewpoint?)
• Are the research methods used consistent and reliable? (Appropriate research methods depend on what was studied.)

What if I'm having a hard time finding good sources?

• For example, if you're writing about the 2020 election, you might find tons of stories online, but very little that is reputable enough for you to use in your paper. Because the election happened so recently, it might be too soon for there to be a lot of solid academic research on it. Instead, you might focus on the 2016 election.
• You can also ask for help. Your instructor might be able to point you toward good sources. Research librarians are also happy to help you.

How do I organize my research for my paper?

• For example, if you're researching the effect of the COVID-19 pandemic on the 2020 election, you might have sections on social distancing and cleaning at in-person voting locations, the accessibility of mail-in ballots, and early voting.

What's the best way to start writing my paper?

• Include an in-text citation for everything that needs one, even in your initial rough draft. That'll help you make sure that you don't inadvertently misattribute or fail to cite something as you work your way through substantive drafts.
• Write your introduction and conclusion only after you're satisfied that the body of your paper is essentially what you want to turn in. Then, you can polish everything up for the final draft.

How can I make sure I'm not plagiarizing?

• If you have any doubt over whether you should cite something, go ahead and do it. You're better off to err on the side of over-citing than to look like you're taking credit for an idea that isn't yours.
• ↑ https://www.nhcc.edu/student-resources/library/doinglibraryresearch/basic-steps-in-the-research-process
• ↑ Matthew Snipp, PhD. Sociology Professor, Stanford University. Expert Interview. 26 March 2020.
• ↑ https://library.taylor.edu/eng-212/research-paper
• ↑ http://www.butte.edu/departments/cas/tipsheets/research/research_paper.html
• ↑ https://www.potsdam.edu/sites/default/files/documents/support/tutoring/cwc/6-Simple-Steps-for-Writing-a-Research-Paper.pdf
• ↑ https://www.umgc.edu/current-students/learning-resources/writing-center/online-guide-to-writing/tutorial/chapter4/ch4-05.html

Expert Q&A

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About This Article

If you need to do research on a particular topic, start by searching the internet for any information you can find on the subject. In particular, look for sites that are sourced by universities, scientists, academic journals, and government agencies. Next, visit your local library and use the electric card catalog to research which books, magazines, and journals will have information on your topic. Take notes as you read, and write down all of the information you’ll need to cite your sources in your final project. To learn how interviewing a first-hand source can help you during your research, read on! Did this summary help you? Yes No

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College Info Geek

How to Do Research in 7 Simple Steps

C.I.G. is supported in part by its readers. If you buy through our links, we may earn an affiliate commission. Read more here.

It’s 2 am, and you’re on your fifth cup of coffee (or was it your sixth?). You’re crouched at a table in some dark corner of the library surrounded by fifteen open books. Equally as many tabs are open on your laptop, and you still haven’t written a word of the paper that’s due in 7 hours.

Many things can explain how you got to this point, including procrastination , poor organization , and a messy schedule .

Very often, however, the problem is a lack of research skills .

And it’s not your fault. High school does a poor job of teaching you how to do research, and most college classes do little better. It feels like you’re expected to figure it out through trial and error.

I think we can do better than that, however. In this guide, I’m going to show you the 7-step process for researching everything from a 10-page term paper to a final presentation. Not only will you learn how to do better research; you’ll also learn how to research more efficiently.

What Is Research?

Before we go any further, what  is  research?

At its core, research is an attempt to answer a question. This could be anything from “How can we reduce infant mortality rates?” to “Why does salt make food taste good?”

To answer your question, you consult books, academic papers, newspaper articles, historical records, or anything else that could be helpful. The broad term for these things is “sources.”

And, usually, once you’ve done the research, you present or summarize it in some way. In many cases, this means writing an essay or another type of scholarly paper, but it could also mean giving a presentation or even creating a YouTube video.

Even if you have no interest in academia, research is an extremely useful skill to learn. When you know how to do research, it’s much easier to improve your life and work more effectively . Instead of having to ask someone every time you have a question, research will help you solve problems yourself (and help others in turn).

Note:  Research can also mean conducting surveys, performing experiments, or going on archaeological digs. While these activities are crucial for advancing human knowledge, I won’t be discussing them here. This article focuses on the research you can do with only a library and an internet connection.

The 7 Steps of the Research Process

Research can feel overwhelming, but it’s more manageable when you break it down into steps. In my experience, the research process has seven main steps:

• Find a topic
• Refine your topic
• Find key sources
• Take notes on your sources
• Create your paper or presentation
• Do additional research as necessary
• Cite your sources

Let’s look at each of these steps in more detail.

1. Find a Topic

If you don’t have a topic, your research will be undirected and inefficient. You’ll spend hours reading dozens of sources, all because you didn’t take a few minutes to develop a topic.

How do you come up with a topic? My number one suggestion is to create a mind map.

A mind map is a visual way to generate ideas. Here’s how it works:

• Get a piece of paper and a pen. Make sure the paper isn’t too small — you want lots of room for your ideas.
• Draw an oval in the center of the paper.
• Inside that oval, write a super vague topic. Start with whatever your professor has assigned you.
• Draw lines from the oval towards the edges of the paper.
• Draw smaller ovals connected to each of these lines.
• Inside the smaller ovals, write more specific ideas/topics related to the central one.
• Repeat until you’ve found 3-5 topic ideas.

When I write it out step by step, it sounds kind of strange. But trust me, it works . Anytime I’m stuck on a writing assignment, this method is my go-to. It’s basically magic.

To see what mind mapping looks like in practice, check out this clip:

Want to create a digital mind map like the one Thomas uses in the video? Check out Coggle .

2. Refine Your Topic

Okay, so now you have a list of 3-5 topics. They’re all still pretty general, and you need to narrow them down to one topic that you can research in depth.

To do this, spend 15 minutes doing some general research on each topic. Specifically, take each topic and plug it into your library’s catalog and database search tools.

The details of this process will vary from library to library. This is where consulting a librarian can be super helpful. They can show you how to use the tools I mentioned, as well as point you to some you probably don’t know about.

Furthermore, I suggest you ask your professor for recommendations. In some cases, they may even have created a resource page specifically for your assignment.

Once you’ve found out where to search, type in your topic. I like to use a mixture of the library catalog, a general academic database like EBSCO Host , and a search on Google Scholar .

What exactly are you trying to find? Basically, you’re trying to find a topic with a sufficient quantity and variety of sources.

Ideally, you want something with both journal articles and books, as this demonstrates that lots of scholars are seriously engaging with the topic.

Of course, in some cases (if the topic is very cutting edge, for example), you may be only able to find journal articles. That’s fine, so long as there are enough perspectives available.

Using this technique, you’ll be able to quickly eliminate some topics. Be ruthless. If you’re not finding anything after 15 minutes, move on. And don’t get attached to a topic.

Tip: If you find two topics with equal numbers of sources available, ask your professor to help you break the tie. They can give you insight into which topic is super common (and thus difficult to write about originally), as well as which they find more interesting.

Now that you have your topic, it’s time to narrow down your sources.

3. Find Key Sources

If you’ve picked a good topic, then you probably have lots of sources to work with. This is both a blessing and a curse. A variety of sources shows that there’s something worth saying about your topic, and it also gives you plenty of material to cite.

But this abundance can quickly turn into a nightmare in which you spend hours reading dense, mind-numbing material without getting any closer to actually producing a paper.

How do you keep this from happening? Choose 3–5  key sources and focus on them intently. Sure, you may end up needing more sources, especially if this is a long paper or if the professor requires it. But if you start out trying to read 15 sources, you’re likely to get overwhelmed and frustrated.

Focusing on a few key sources is powerful because it:

• Lets you engage deeply with each source.
• Gives you a variety of perspectives.
• Points you to further resources.
• Keeps you focused.

4. Read and Take Notes

But what do you do with these sources, exactly? You need to read them the right way . Follow these steps to effectively read academic books and articles:

Go through the article and look at the section headings. If any words or terms jump out at you, make note of them. Also, glance at the beginning sentences of each section and paragraph to get an overall idea of the author’s argument.

The goal here isn’t to comprehend deeply, but to prime your mind for effective reading .

Write down any questions you have after skimming the article, as well as any general questions you hope the article can answer. Always keep your topic in mind.

Read Actively

Now, start reading. But don’t just passively go through the information like you’re scrolling through Tumblr. Read with a pen or pencil in hand , underlining any unfamiliar terms or interesting ideas.

Make notes in the margins about other sources or concepts that come to mind. If you’re reading a library book, you can make notes on a separate piece of paper.

Once you’ve finished reading, take a short break. Have a cup of tea or coffee. Go for a walk around the library. Stretch. Just get your mind away from the research for a moment without resorting to distracting, low-density fun .

Now come back to the article and look at the things you underlined or noted. Gather these notes and transfer them to a program like Evernote .

If you need to look up a term, do that, and then add that definition to your notes. Also, make note of any sources the author cites that look helpful.

But what if I’m reading a book?   Won’t this take forever?  No, because you’re not going to read the entire book.

For most research you’ll do in college, reading a whole academic book is overkill . Just skim the table of contents and the book itself to find chapters or sections that look relevant.

Then, read each of those in the same way you would read an article. Also, be sure to glance at the book’s bibliography, which is a goldmine for finding additional sources.

Note: The above method is a variation on the classic SQ3R method , adapted slightly since we’re not interested in taking notes from textbooks .

5. Create Your Paper or Presentation

“You can’t turn in raw research.”

Research is crucial to crafting a great paper or presentation, but it’s also a great way to procrastinate. I had classmates in college who would spend 8 hours researching a 5-page paper. That’s way too much!

At some point, you need to stop researching and start writing (or whatever method you’re using to present your research).

How do you decide when to stop researching? There’s no strict rule, but in general I wouldn’t spend more than 30 minutes per page of the final paper.

So if the final paper is supposed to be 10 pages, don’t spend more than 5 hours researching it.

6. Do Additional Research (As Necessary)

Once you’ve started writing the draft of your paper, you’ll probably find a few gaps. Maybe you realize that one scholar’s argument isn’t relevant to your paper, or that you need more information for a particular section. In this case, you are free to return to researching as necessary.

But again, beware the trap of procrastination masquerading as productivity! Only do as much additional research as you need to answer your question. Don’t get pulled into rabbit holes or dragged off on tangents. Get in there, do your research, and get back to writing .

To keep yourself focused, I suggest keeping a separate document or piece of paper nearby to note points that need additional research.

Every time you encounter such a point, make note of it in the document and then keep writing. Only stop when you can’t get any further without additional research.

It’s much better to get a full draft done first. Otherwise, you risk suffering a cognitive switching penalty , making it harder to regain your focus.

7. Cite Your Sources

Whether you’re creating an oral presentation, essay, or video, you’ll need to cite your sources. Plagiarism is a serious offense, so don’t take any chances.

How to cite your sources depends on the subject and the professor’s expectations. Chicago, MLA, and APA are the most common citation formats to use in college, but there are thousands more.

Luckily, you don’t need to painstakingly type each of your citations by hand or slog through a style manual. Instead, you can use a tool like Zotero to track and generate your citations. To make things even easier, install the Zotero Connector browser extension. It can automatically pull citation information from entries in an online library catalog.

Once you’ve collected all of your sources, Zotero can generate a properly formatted works cited page or bibliography at just the click of a button.

For help setting up and using Zotero, read this guide . If you need further assistance, ask a librarian.

Go Research With Confidence

I hope you now understand how to do research with more confidence. If you follow the procedures I’ve covered in this article, you’ll waste less time, perform more effective research, and ultimately have the material for a winning essay.

Curious about how to use your research to write a great research paper? Check out this guide .

Image Credits: picking book from shelf

How to Do Research: A Step-By-Step Guide: Get Started

• Get Started
• 1a. Select a Topic
• 1b. Develop Research Questions
• 1c. Identify Keywords
• 1d. Find Background Information
• 1e. Refine a Topic
• 2a. Search Strategies
• 2d. Articles
• 2e. Videos & Images
• 2f. Databases
• 2g. Websites
• 2h. Grey Literature
• 2i. Open Access Materials
• 3a. Evaluate Sources
• 3b. Primary vs. Secondary
• 3c. Types of Periodicals
• 4a. Take Notes
• 4b. Outline the Paper
• 4c. Incorporate Source Material
• 5a. Avoid Plagiarism
• 5b. Zotero & MyBib
• 5c. MLA Formatting
• 5d. MLA Citation Examples
• 5e. APA Formatting
• 5f. APA Citation Examples
• 5g. Annotated Bibliographies

Research Essentials Video Tutorials

Related guides.

• Elmira College Writing Center Get one-on-one assistance for all types of writing.

Recommended Websites

• Purdue University's Online Writing Lab (OWL)

Research Process Overview

Step 1.  Develop a topic Select a Topic | Develop Research Questions | Identify Keywords | Find Background Information | Refine a Topic

Step 2. Locate information Search Strategies | Books | eBooks | Articles  | Videos & Images | Databases | Websites | Grey Literature

Step 3. Evaluate and analyze information Evaluate Sources | Primary vs Secondary | Types of Periodicals

Step 4. Write, organize, and communicate information Take Notes | Outline the Paper | Incorporate Source Material

Step 5. Cite sources Avoid Plagiarism | Zotero & MyBib | MLA | APA | Chicago Style | Annotated Bibliographies

For research help,  use one of the following options:

Ask the GTL

• Next: Step 1: Develop a Topic >>
• Last Updated: Feb 21, 2024 11:01 AM
• URL: https://libguides.elmira.edu/research

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How to Do Research: and How to Be a Researcher

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There are many textbooks on research methods, but these tend to be targeted at particular disciplines. Equally, there are plenty of books on popular science and other academic fields, but few that provide an overview of career opportunities or a framework for getting started. The principles underlying humanity’s past and continuing acquisition of knowledge are straightforward and are illustrated here across academic fields, from history to quantum physics—stories of clever and inventive people with good ideas, but also of personalities, politics, and power. This book draws together these strands to provide an informal and concise account of knowledge acquisition in all its guises. Having set out what research hopes to achieve, and why we are all researchers at heart, early chapters describe the basic principles underlying this—ways of thinking which may date back to the philosophers of the Athenian marketplace but are still powerful influences on the way research is carried out today. Drawing on a broad range of disciplines, the book takes the reader well beyond the pure ‘scientific method’, which might work well enough in physics or chemistry but falls apart in life sciences, let alone humanities. Later chapters consider the realities of carrying out research and the ways in which these continue to shape its progress—researchers and their personalities, their employers, funding, publication, political forces, and power structures.

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Research Basics

• What Is Research?
• Types of Research
• Secondary Research | Literature Review
• Developing Your Topic
• Primary vs. Secondary Sources
• Evaluating Sources
• Responsible Conduct of Research
• Additional Help

A good working definition of research might be:

Research is the deliberate, purposeful, and systematic gathering of data, information, facts, and/or opinions for the advancement of personal, societal, or overall human knowledge.

Based on this definition, we all do research all the time. Most of this research is casual research. Asking friends what they think of different restaurants, looking up reviews of various products online, learning more about celebrities; these are all research.

Formal research includes the type of research most people think of when they hear the term “research”: scientists in white coats working in a fully equipped laboratory. But formal research is a much broader category that just this. Most people will never do laboratory research after graduating from college, but almost everybody will have to do some sort of formal research at some point in their careers.

So What Do We Mean By “Formal Research?”

Casual research is inward facing: it’s done to satisfy our own curiosity or meet our own needs, whether that’s choosing a reliable car or figuring out what to watch on TV. Formal research is outward facing. While it may satisfy our own curiosity, it’s primarily intended to be shared in order to achieve some purpose. That purpose could be anything: finding a cure for cancer, securing funding for a new business, improving some process at your workplace, proving the latest theory in quantum physics, or even just getting a good grade in your Humanities 200 class.

What sets formal research apart from casual research is the documentation of where you gathered your information from. This is done in the form of “citations” and “bibliographies.” Citing sources is covered in the section "Citing Your Sources."

Formal research also follows certain common patterns depending on what the research is trying to show or prove. These are covered in the section “Types of Research.”

• Next: Types of Research >>
• Last Updated: Dec 21, 2023 3:49 PM
• URL: https://guides.library.iit.edu/research_basics

Basic Steps in the Research Process

The following steps outline a simple and effective strategy for writing a research paper. Depending on your familiarity with the topic and the challenges you encounter along the way, you may need to rearrange these steps.

Step 1: Identify and develop your topic

Selecting a topic can be the most challenging part of a research assignment. Since this is the very first step in writing a paper, it is vital that it be done correctly. Here are some tips for selecting a topic:

• Select a topic within the parameters set by the assignment. Many times your instructor will give you clear guidelines as to what you can and cannot write about. Failure to work within these guidelines may result in your proposed paper being deemed unacceptable by your instructor.
• Select a topic of personal interest to you and learn more about it. The research for and writing of a paper will be more enjoyable if you are writing about something that you find interesting.
• Select a topic for which you can find a manageable amount of information. Do a preliminary search of information sources to determine whether existing sources will meet your needs. If you find too much information, you may need to narrow your topic; if you find too little, you may need to broaden your topic.
• Be original. Your instructor reads hundreds of research papers every year, and many of them are on the same topics (topics in the news at the time, controversial issues, subjects for which there is ample and easily accessed information). Stand out from your classmates by selecting an interesting and off-the-beaten-path topic.
• Still can't come up with a topic to write about? See your instructor for advice.

Once you have identified your topic, it may help to state it as a question. For example, if you are interested in finding out about the epidemic of obesity in the American population, you might pose the question "What are the causes of obesity in America ?" By posing your subject as a question you can more easily identify the main concepts or keywords to be used in your research.

Step 2 : Do a preliminary search for information

Before beginning your research in earnest, do a preliminary search to determine whether there is enough information out there for your needs and to set the context of your research. Look up your keywords in the appropriate titles in the library's Reference collection (such as encyclopedias and dictionaries) and in other sources such as our catalog of books, periodical databases, and Internet search engines. Additional background information may be found in your lecture notes, textbooks, and reserve readings. You may find it necessary to adjust the focus of your topic in light of the resources available to you.

Step 3: Locate materials

With the direction of your research now clear to you, you can begin locating material on your topic. There are a number of places you can look for information:

If you are looking for books, do a subject search in One Search . A Keyword search can be performed if the subject search doesn't yield enough information. Print or write down the citation information (author, title,etc.) and the location (call number and collection) of the item(s). Note the circulation status. When you locate the book on the shelf, look at the books located nearby; similar items are always shelved in the same area. The Aleph catalog also indexes the library's audio-visual holdings.

Use the library's  electronic periodical databases  to find magazine and newspaper articles. Choose the databases and formats best suited to your particular topic; ask at the librarian at the Reference Desk if you need help figuring out which database best meets your needs. Many of the articles in the databases are available in full-text format.

Use search engines ( Google ,  Yahoo , etc.) and subject directories to locate materials on the Internet. Check the  Internet Resources  section of the NHCC Library web site for helpful subject links.

Step 4: Evaluate your sources

See the  CARS Checklist for Information Quality   for tips on evaluating the authority and quality of the information you have located. Your instructor expects that you will provide credible, truthful, and reliable information and you have every right to expect that the sources you use are providing the same. This step is especially important when using Internet resources, many of which are regarded as less than reliable.

Step 5: Make notes

Consult the resources you have chosen and note the information that will be useful in your paper. Be sure to document all the sources you consult, even if you there is a chance you may not use that particular source. The author, title, publisher, URL, and other information will be needed later when creating a bibliography.

Step 6: Write your paper

Begin by organizing the information you have collected. The next step is the rough draft, wherein you get your ideas on paper in an unfinished fashion. This step will help you organize your ideas and determine the form your final paper will take. After this, you will revise the draft as many times as you think necessary to create a final product to turn in to your instructor.

Step 7: Cite your sources properly

Give credit where credit is due; cite your sources.

Citing or documenting the sources used in your research serves two purposes: it gives proper credit to the authors of the materials used, and it allows those who are reading your work to duplicate your research and locate the sources that you have listed as references. The  MLA  and the  APA  Styles are two popular citation formats.

Failure to cite your sources properly is plagiarism. Plagiarism is avoidable!

Step 8: Proofread

The final step in the process is to proofread the paper you have created. Read through the text and check for any errors in spelling, grammar, and punctuation. Make sure the sources you used are cited properly. Make sure the message that you want to get across to the reader has been thoroughly stated.

Additional research tips:

• Work from the general to the specific -- find background information first, then use more specific sources.
• Don't forget print sources -- many times print materials are more easily accessed and every bit as helpful as online resources.
• The library has books on the topic of writing research papers at call number area LB 2369.
• If you have questions about the assignment, ask your instructor.
• If you have any questions about finding information in the library, ask the librarian.

Contact Information

Craig larson.

Librarian 763-424-0733 [email protected] Zoom:  myzoom   Available by appointment

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Doing Research: A New Researcher’s Guide pp 1–15 Cite as

What Is Research, and Why Do People Do It?

• James Hiebert 6 ,
• Jinfa Cai 7 ,
• Stephen Hwang 7 ,
• Anne K Morris 6 &
• Charles Hohensee 6  
• Open Access
• First Online: 03 December 2022

16k Accesses

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

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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do a research / make a research

• Thread starter Gema
• Start date Jul 23, 2004
• Jul 23, 2004

Hi! I'm a spanish girl. Now I'm doing an english course and I must do a writing for monday. I have a doubt. Which of this two options is correct, "do a research" or "make a research"? Thank you in advance for your help. Gema  

''Do a research , is more appropriate..although you can very well say i am going to research on this subject  

rinks said: ''Do a research , is more appropriate..although you can very well say i am going to research on this subject Click to expand...

Administrator

Hi Gema, (Yes, this type of question is much more appropriate.) Welcome to the forum! For many "hacer un ..." constructions in Spanish, we just use the verb form of the noun. So, we would usually say "We researched" or "We are researching."  

hypertweeky

Senior member.

• Jul 24, 2004

Gema said: Hi! I'm a spanish girl. Now I'm doing an english course and I must do a writing for monday. I have a doubt. Which of this two options is correct, "do a research" or "make a research"? Thank you in advance for your help. Gema Click to expand...

• Jul 25, 2004

el alabamiano

You can also use: I'm going to do some research / I did some research /  

el alabamiano said: You can also use: I'm going to do some research / I did some research / Click to expand...

Mary Solari

• Jul 31, 2004

Norman P. Bock

• Aug 1, 2004

If you are using "research" as a noun, you would say doing "research" or do "research". But "research" is also a verb. So you can either say "I am going to do research on the causes of the civil war." Or you can just say, "I am going to research the causes of the civil war."  

Moderator: EHL, Arabic, Hebrew, German(-Spanish)

• Aug 2, 2004

"To research a subject" (not ON a subject) suggests something relatively in-depth. "To do research on a subject" suggests little or partial research. "To conduct" or "carry out" research on a subject would be a more elevated way to express the same idea. As was said, definitely not "make." Hope this helps.  

• Apr 6, 2007

elroy said: "To research a subject" (not ON a subject) suggests something relatively in-depth. "To do research on a subject" suggests little or partial research. "To conduct" or "carry out" research on a subject would be a more elevated way to express the same idea. As was said, definitely not "make." Hope this helps. Click to expand...

• Apr 11, 2008

Gema to do a research on a topic is more common I hope that I helped you  

Wilma_Sweden

I have also found that you can undertake or carry out research, and that into and on are valid prepositions. However, when using research as a verb , my dictionaries (Longman & Cambridge online) give into as the only valid preposition. I have also found research used in the plural, e.g. scientists being awarded the Nobel Prize for their researches into [whatever subject], and I'm assuming that this is idiomatic if you are referring to multiple research projects. /Wilma  

• Dec 2, 2009

Hi! I actually have a question about what follows the word research . Can you say, f. e. , I did some research about it, or should it always be on/into or without anything like > I researched it. I'm really confused and I don't know what's wrong or right anymore. Thanks for your help.  

thoughtdots

• May 15, 2011

Let's say I researched World War II. I think it sounds better to either say, "I researched WWII" or "I did research on WWII". However, if you use any other preposition, people will still understand you.  

• Jan 22, 2014
• Dec 14, 2015

Hi! What about 'I did my own research to prepare a talk for the students' ? In this case I'm using it as a noun, but if its uncountable would it be ok to 'classify' it as 'my own'? Thanks!  

Member Emeritus

Yes, "my own research" is fine.  

• Aug 29, 2020

Maigualida said: ‘I have to conduct a research or I conducted a research’ . Click to expand...

Maigualida said: Can I correct ? Instead of saying to do research yo say ‘I have to conduct a research or I conducted a research’ . ( the verb conduct is more common) Also you don’t say I must do a writing, you say: I have to write a paper about... The days of the week are written with capital letters...Monday, Tuesday , etc I hits it helps Click to expand...

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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 does a researcher do?

Would you make a good researcher? Take our career test and find your match with over 800 careers.

What is a Researcher?

A researcher is trained to conduct systematic and scientific investigations in a particular field of study. Researchers use a variety of techniques to collect and analyze data to answer research questions or test hypotheses. They are responsible for designing studies, collecting data, analyzing data, and interpreting the results. Researchers may work in a wide range of fields, including science, medicine, engineering, social sciences, humanities, and many others.

To become a researcher, individuals usually need to obtain a graduate degree in their chosen field of study. They may also need to gain experience working as an assistant or intern in a research setting before becoming a full-fledged researcher. Researchers may work in academic or industrial settings, or they may work independently as consultants or freelance researchers. Regardless of the setting, researchers play a vital role in advancing knowledge and finding solutions to real-world problems.

What does a Researcher do?

Researchers are essential to the advancement of knowledge in various fields, including science, technology, medicine, social sciences, and humanities. Their work involves conducting systematic investigations to gather data, analyze it, and draw meaningful conclusions. Through their research, they can identify new problems and challenges, develop innovative solutions, and test hypotheses to validate theories.

Researchers also play a critical role in improving existing practices and policies, identifying gaps in knowledge, and creating new avenues for future research. They provide valuable insights and information that can inform decision-making, shape public opinion, and drive progress in society.

Duties and Responsibilities The duties and responsibilities of researchers can vary depending on the field of study and the type of research being conducted. However, here are some common duties and responsibilities that researchers are typically expected to fulfill:

• Develop research proposals: Developing a research proposal typically involves identifying a research question or problem, reviewing the relevant literature, selecting appropriate research methods and techniques, and outlining the expected outcomes of the research. Researchers must also ensure that their proposal aligns with the funding agency's objectives and guidelines.
• Conduct literature reviews: Literature reviews involve searching for and reviewing existing research papers, articles, books, and other relevant publications to identify gaps in knowledge and to build upon previous research. Researchers must ensure that they are using credible and reliable sources of information and that their review is comprehensive.
• Collect and analyze data: Collecting and analyzing data is a key aspect of research. This may involve designing and conducting experiments, surveys, interviews, or observations. Researchers must ensure that their data collection methods are valid and reliable, and that their analysis is appropriate and accurate.
• Ensure ethical considerations: Research ethics involve ensuring that the research is conducted in a manner that protects the rights, welfare, and dignity of all participants, as well as the environment. Researchers must obtain informed consent from human participants, ensure that animal research is conducted ethically and humanely, and comply with relevant regulations and guidelines.
• Communicate research findings: Researchers must communicate their research findings clearly and effectively to a range of audiences, including academic peers, policymakers, and the general public. This may involve writing research papers, presenting at conferences, and producing reports or other materials.
• Manage research projects: Managing a research project involves planning, organizing, and coordinating resources, timelines, and budgets to ensure that the project is completed on time and within budget. Researchers must ensure that they have the necessary resources, such as funding, personnel, and equipment, and that they are managing these resources effectively.
• Collaborate with others: Collaboration is an important aspect of research, and researchers often work with other researchers, academic institutions, funding agencies, and industry partners to achieve research objectives. Collaboration can help to facilitate the sharing of resources, expertise, and knowledge.
• Stay up-to-date with developments in their field: Research is an evolving field, and researchers must stay up-to-date with the latest developments and trends in their field to ensure that their research remains relevant and impactful. This may involve attending conferences, workshops, and seminars, reading academic journals and other publications, and participating in professional development opportunities.

Types of Researchers There are many types of researchers, depending on their areas of expertise, research methods, and the types of questions they seek to answer. Here are some examples:

• Basic Researchers: These researchers focus on understanding fundamental concepts and phenomena in a particular field. Their work may not have immediate practical applications, but it lays the groundwork for applied research.
• Applied Researchers: These researchers seek to apply basic research findings to real-world problems and situations. They may work in fields such as engineering, medicine, or psychology.
• Clinical Researchers: These researchers conduct studies with human subjects to better understand disease, illness, and treatment options. They may work in hospitals, universities, or research institutes.
• Epidemiologists : These researchers study the spread and distribution of disease in populations, and work to develop strategies for disease prevention and control.
• Social Scientists: These researchers study human behavior and society, using methods such as surveys, experiments, and observations. They may work in fields such as psychology, sociology, or anthropology.
• Natural Scientists: These researchers study the natural world, including the physical, chemical, and biological processes that govern it. They may work in fields such as physics, chemistry, or biology.
• Data Scientists : These researchers use statistical and computational methods to analyze large datasets and derive insights from them. They may work in fields such as machine learning, artificial intelligence, or business analytics.
• Policy Researchers: These researchers study policy issues, such as healthcare, education, or environmental regulations, and work to develop evidence-based policy recommendations. They may work in government agencies, think tanks, or non-profit organizations.

What is the workplace of a Researcher like?

The workplace of a researcher can vary greatly depending on the field and area of study. Researchers can work in a variety of settings, including academic institutions, government agencies, non-profit organizations, and private companies.

In academic settings, researchers often work in universities or research institutions, conducting experiments and analyzing data to develop new theories and insights into various fields of study. They may also teach courses and mentor students in their area of expertise.

In government agencies, researchers may work on projects related to public policy, health, and safety. They may be responsible for conducting research to support the development of new regulations or programs, analyzing data to assess the effectiveness of existing policies, or providing expertise on specific issues.

Non-profit organizations often employ researchers to study social and environmental issues, such as poverty, climate change, and human rights. These researchers may conduct surveys and collect data to understand the impact of various programs and initiatives, and use this information to advocate for policy changes or other interventions.

Private companies also employ researchers, particularly in industries such as technology and healthcare. These researchers may be responsible for developing new products, improving existing technologies, or conducting market research to understand consumer preferences and behaviors.

Regardless of the setting, researchers typically spend a significant amount of time conducting research, analyzing data, and communicating their findings through presentations, reports, and publications. They may also collaborate with other researchers or professionals in their field, attend conferences and workshops, and stay up-to-date with the latest research and developments in their area of expertise.

Frequently Asked Questions

Academic writer vs researcher.

An academic writer is someone who produces written material for academic purposes, such as research papers, essays, and other scholarly works. Academic writers may work as freelance writers, editors, or as staff writers for academic institutions or publishers.

On the other hand, a researcher is someone who conducts original research to generate new knowledge or validate existing knowledge. Researchers may work in academic settings, government agencies, private companies, or non-profit organizations. They typically design and execute experiments, surveys, or other data collection methods, analyze the data, and draw conclusions based on their findings.

While there may be some overlap between the skills required for academic writing and research, they are distinct activities with different goals. Academic writers often rely on the research of others to support their arguments, while researchers generate new knowledge through their own experiments and data analysis. However, academic writers may also be researchers who write about their own research findings.

Continue reading

15 Steps to Good Research

• Define and articulate a research question (formulate a research hypothesis). How to Write a Thesis Statement (Indiana University)
• Identify possible sources of information in many types and formats. Georgetown University Library's Research & Course Guides
• Judge the scope of the project.
• Reevaluate the research question based on the nature and extent of information available and the parameters of the research project.
• Select the most appropriate investigative methods (surveys, interviews, experiments) and research tools (periodical indexes, databases, websites).
• Plan the research project. Writing Anxiety (UNC-Chapel Hill) Strategies for Academic Writing (SUNY Empire State College)
• Retrieve information using a variety of methods (draw on a repertoire of skills).
• Refine the search strategy as necessary.
• Write and organize useful notes and keep track of sources. Taking Notes from Research Reading (University of Toronto) Use a citation manager: Zotero or Refworks
• Evaluate sources using appropriate criteria. Evaluating Internet Sources
• Synthesize, analyze and integrate information sources and prior knowledge. Georgetown University Writing Center
• Revise hypothesis as necessary.
• Use information effectively for a specific purpose.
• Understand such issues as plagiarism, ownership of information (implications of copyright to some extent), and costs of information. Georgetown University Honor Council Copyright Basics (Purdue University) How to Recognize Plagiarism: Tutorials and Tests from Indiana University
• Cite properly and give credit for sources of ideas. MLA Bibliographic Form (7th edition, 2009) MLA Bibliographic Form (8th edition, 2016) Turabian Bibliographic Form: Footnote/Endnote Turabian Bibliographic Form: Parenthetical Reference Use a citation manager: Zotero or Refworks

Adapted from the Association of Colleges and Research Libraries "Objectives for Information Literacy Instruction" , which are more complete and include outcomes. See also the broader "Information Literacy Competency Standards for Higher Education."

Princeton Correspondents on Undergraduate Research

How to Make a Successful Research Presentation

Turning a research paper into a visual presentation is difficult; there are pitfalls, and navigating the path to a brief, informative presentation takes time and practice. As a TA for  GEO/WRI 201: Methods in Data Analysis & Scientific Writing this past fall, I saw how this process works from an instructor’s standpoint. I’ve presented my own research before, but helping others present theirs taught me a bit more about the process. Here are some tips I learned that may help you with your next research presentation:

More is more

In general, your presentation will always benefit from more practice, more feedback, and more revision. By practicing in front of friends, you can get comfortable with presenting your work while receiving feedback. It is hard to know how to revise your presentation if you never practice. If you are presenting to a general audience, getting feedback from someone outside of your discipline is crucial. Terms and ideas that seem intuitive to you may be completely foreign to someone else, and your well-crafted presentation could fall flat.

Less is more

Limit the scope of your presentation, the number of slides, and the text on each slide. In my experience, text works well for organizing slides, orienting the audience to key terms, and annotating important figures–not for explaining complex ideas. Having fewer slides is usually better as well. In general, about one slide per minute of presentation is an appropriate budget. Too many slides is usually a sign that your topic is too broad.

Limit the scope of your presentation

Don’t present your paper. Presentations are usually around 10 min long. You will not have time to explain all of the research you did in a semester (or a year!) in such a short span of time. Instead, focus on the highlight(s). Identify a single compelling research question which your work addressed, and craft a succinct but complete narrative around it.

You will not have time to explain all of the research you did. Instead, focus on the highlights. Identify a single compelling research question which your work addressed, and craft a succinct but complete narrative around it.

Craft a compelling research narrative

After identifying the focused research question, walk your audience through your research as if it were a story. Presentations with strong narrative arcs are clear, captivating, and compelling.

• Introduction (exposition — rising action)

Orient the audience and draw them in by demonstrating the relevance and importance of your research story with strong global motive. Provide them with the necessary vocabulary and background knowledge to understand the plot of your story. Introduce the key studies (characters) relevant in your story and build tension and conflict with scholarly and data motive. By the end of your introduction, your audience should clearly understand your research question and be dying to know how you resolve the tension built through motive.

• Methods (rising action)

The methods section should transition smoothly and logically from the introduction. Beware of presenting your methods in a boring, arc-killing, ‘this is what I did.’ Focus on the details that set your story apart from the stories other people have already told. Keep the audience interested by clearly motivating your decisions based on your original research question or the tension built in your introduction.

• Results (climax)

Less is usually more here. Only present results which are clearly related to the focused research question you are presenting. Make sure you explain the results clearly so that your audience understands what your research found. This is the peak of tension in your narrative arc, so don’t undercut it by quickly clicking through to your discussion.

• Discussion (falling action)

By now your audience should be dying for a satisfying resolution. Here is where you contextualize your results and begin resolving the tension between past research. Be thorough. If you have too many conflicts left unresolved, or you don’t have enough time to present all of the resolutions, you probably need to further narrow the scope of your presentation.

• Conclusion (denouement)

Return back to your initial research question and motive, resolving any final conflicts and tying up loose ends. Leave the audience with a clear resolution of your focus research question, and use unresolved tension to set up potential sequels (i.e. further research).

Use your medium to enhance the narrative

Visual presentations should be dominated by clear, intentional graphics. Subtle animation in key moments (usually during the results or discussion) can add drama to the narrative arc and make conflict resolutions more satisfying. You are narrating a story written in images, videos, cartoons, and graphs. While your paper is mostly text, with graphics to highlight crucial points, your slides should be the opposite. Adapting to the new medium may require you to create or acquire far more graphics than you included in your paper, but it is necessary to create an engaging presentation.

The most important thing you can do for your presentation is to practice and revise. Bother your friends, your roommates, TAs–anybody who will sit down and listen to your work. Beyond that, think about presentations you have found compelling and try to incorporate some of those elements into your own. Remember you want your work to be comprehensible; you aren’t creating experts in 10 minutes. Above all, try to stay passionate about what you did and why. You put the time in, so show your audience that it’s worth it.

For more insight into research presentations, check out these past PCUR posts written by Emma and Ellie .

— Alec Getraer, Natural Sciences Correspondent

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Meaning of research in English

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• He has dedicated his life to scientific research.
• He emphasized that all the people taking part in the research were volunteers .
• The state of Michigan has endowed three institutes to do research for industry .
• I'd like to see the research that these recommendations are founded on.
• It took months of painstaking research to write the book .
• absorptive capacity
• dream something up
• modularization
• nanotechnology
• non-imitative
• operational research
• think outside the box idiom
• think something up
• uninventive
• study What do you plan on studying at university?
• major US She majored in philosophy at Harvard.
• cram She's cramming for her history exam.
• revise UK I'm revising for tomorrow's test.
• review US We're going to review for the test tomorrow night.
• research Scientists are researching possible new treatments for cancer.
• The amount of time and money being spent on researching this disease is pitiful .
• We are researching the reproduction of elephants .
• She researched a wide variety of jobs before deciding on law .
• He researches heart disease .
• The internet has reduced the amount of time it takes to research these subjects .
• adjudication
• interpretable
• interpretive
• interpretively
• investigate
• reinvestigate
• reinvestigation
• risk assessment
• run over/through something
• run through something

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Translations of research

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the act of an animal running around, sometimes in circles, in a very energetic way

Binding, nailing, and gluing: talking about fastening things together

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When some schools are banning ChatGPT, Vanderbilt is embracing generative AI technology to unlock opportunities for research and learning.

By michael blanding.

In her class on the politics of the French Revolution, Holly Tucker starts off by assigning a historical character to each student—Marquis de Lafayette, Jean-Jacques Rousseau, Louis XVI—and giving them a multi-page role sheet detailing their alter ego’s political affiliation, life philosophy and strategic goals. Monarchist or revolutionary firebrand, this will be the student’s persona for the next six weeks, as Tucker has the class role-play scenarios, seek out alliances and vanquish their enemies in a simulation of the crucial historical event.

She next encourages them to do something many teachers wouldn’t dream of—talk to ChatGPT. “One of their first assignments is to upload their role sheet and then ask questions about it,” says Tucker, Mellon Foundation Chair in the Humanities and professor of French, of the interaction with the generative artificial intelligence app that has exploded onto the internet, generating equal parts excitement and fear. “I have them say, ‘Can you help me find three characters I might want to correspond with, and help me brainstorm approaches to frame my letters to them?’”

From then on, artificial intelligence becomes a vital part of the course. Students use it to analyze vast amounts of data, to communicate with each other and to make strategic moves. In all, Tucker says, students write an average of 18,000 messages to each other, as AI helps keep track of the interactions and even offers student insights into potential outcomes of decisions they are considering—teaching students about the French Revolution in a uniquely immersive way.

“It’s a watershed moment for the humanities. We now have the ability to communicate with a computer using natural language,” Tucker says. “We owe it to ourselves to find ways to use generative AI to glean insights from our texts faster and ask new questions about the human endeavor.”

Tucker’s enthusiastic embrace of ChatGPT in her class is just one example of Vanderbilt faculty’s groundbreaking work in harnessing the growing power of artificial intelligence. At a time when some schools are banning ChatGPT in classes—concerned that students will lean too heavily on AI or use it to write papers for them—Vanderbilt has become a leader in integrating AI into academic work. Faculty are using AI in their research, as well as introducing it to students, teaching them how to use it as a tool and not a crutch.

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FUTURE OF LEARNING

“Everybody’s focused on artificial intelligence replacing humans,” says Jules White, professor of computer science and associate dean for strategic learning programs. “But what we want to focus on is augmented intelligence, where it’s all about amplifying human creativity and problem-solving. It’s like an exoskeleton for the mind—you help people create more interesting and expressive things than they could have done before, and at a larger scale.”

White leads the Future of Learning and Generative AI Initiative, a new interdisciplinary program to connect and advise faculty on how to make the most of the prodigious computing power generative AI can offer. A CNN article this summer said Vanderbilt was “among the early leaders taking a strong stance in support of generative AI,” specifically citing an 18-hour online course White created on the e-learning platform Coursera that teaches the fundamentals of “prompt engineering”—how to best fashion a prompt to ChatGPT and other AI platforms to return the most helpful response. The course has been taken by 240,000 people and counting.

In their simplest form, White says, generative AI models are trained to predict the next word in a sentence. If you give it “Mary had a little,” then it should predict “lamb.” The magic happens when you train it on vast amounts of data from the World Wide Web. “It turns out this has surprising ramifications when you do this at a large enough scale, as it learns patterns in our language and can do all of these computations.”

Most of the problems with ChatGPT and other generative AI platforms, White says, result from people not knowing how to use it properly. “People see a text box, and they think they need to use it like Google, which is exactly the wrong way to use it,” he explains. “That doesn’t give you augmented intelligence, that gives you minus intelligence.”

Rather than using it to search for information, he says, generative AI is most effective when treated like you are sending a text message to an incredibly smart and capable assistant. One example he uses in his class is to ask it to create a meal plan “that’s a fusion of food from Ethiopia and Uzbekistan, is keto-friendly and has ingredients I can get from the average grocery store.” There isn’t a page on Google that could give you that info, and yet ChatGPT can create a complete multi-week menu in seconds. Another trick, he adds, is to give it a role, for example, telling it to “act like a speech pathologist” before presenting it with a problem where a child mixes up words and asking it to diagnose possible causes. “Knowing the pattern of interaction allows it to tap into these emergent computational capabilities that no other system on the planet can perform.”

APPLYING AI TO VAST AMOUNTS OF DATA

Another use for the software is to analyze and summarize vast amounts of complex information. In the past, Doug Schmidt, Cornelius Vanderbilt Professor of Computer Science, has worked in government procurement for defense systems—for example, building a next-generation air traffic management or missile defense system. “It involves an enormous number of people over a very long time and at great expense,” he says. Comparing information in multiple reports by different people and then trying to figure out if they meet government regulations can be a major headache. “As luck would have it, large language models are very good at that,” says Schmidt, who is researching how generative AI can dramatically save time and money by comparing and synthesizing such reports.

On another level, Schmidt is using the same tools in his computer science classes, using a Chrome plugin called Glasp to take videos of his lectures and toss a transcript into ChatGPT to summarize the main points. Schmidt then asks it to generate several quiz questions based on the videos. “And boom, within seconds, I have fresh up-to-date questions on what I talked about in class,” he says. Of course, Schmidt reviews the questions to see if they are accurate—something easy to do since he generated the material himself—but the tool helps take away from tasks he finds tedious, so he can focus on those he enjoys, such as writing lectures and code.

As for the fears that students will cheat on tests and papers by using ChatGPT, he addresses that head-on by changing the way he designs problems. Instead of asking students to write very specific code they could easily generate using AI, he presents more open-ended questions that could be solved in a variety of ways, requiring students to use their own creativity. Of course, those tests are harder to grade, but Schmidt has come up with a solution to that, too, training ChatGPT to automatically find elements that should or shouldn’t be in the code. “Instead of hiring an army of graders and asking them to follow some rubric, I’ve found a way to automatically do something that used to require tremendous time and effort on the part of me and my TAs.”

Efforts by some to ban ChatGPT and other AI software, Schmidt says, are misguided. “They think this is a flash in the pan and are actively discouraging people from using it,” he says. “Our hypothesis is that in the very near future people who know how to use this stuff well are going to run rings around the people who don’t. They won’t be able to get anywhere near the level of productivity for the amount of effort expended.”

BUILDING SKEPTICAL AND INFORMED AI USERS

His colleague Jesse Spencer-Smith, chief data scientist and interim director of the Data Science Institute and professor of the practice of computer science, has gone a step further in embracing generative AI for coding. As someone who has taught artificial intelligence for 20 years, Spencer-Smith recently changed the name of his advanced coding class to AI-Assisted Coding. “Rather than trying to detect whether you used ChatGPT to solve a programming problem, we’ve turned it around, to say, ‘Use ChatGPT and get very efficient and know how to guide it,’” he says.

He encourages the same approach in the humanities, citing a clever exercise by a faculty member in the English department who specifically told students to use ChatGPT to write an essay—and then turn around and grade it, so they could see its shortcomings where it used poor phrasing or got information wrong, as well as how it can be used to help organize ideas. “It turns people into skeptical and informed users and also gets them to the point where they can understand what good writing is,” Spencer-Smith says.

On the other hand, generative AI can be an excellent tool for studying or brainstorming. The DSI and Center for Teaching have collaborated on a platform which acts as a personalized tutor, where students can upload a book chapter or paper they need to review, and the AI can generate questions to quiz them on the material. The entire transcript can then be uploaded so the professor can see what the student understands and where they need help. “I used to have help sessions where half the class would be in every week,” Spencer-Smith says. “Now, I have very few people because they are all using ChatGPT to explain concepts in a way customized to their background.”

DSI has also collaborated with faculty to integrate AI into their teaching and research. Recently, for example, it’s been working with Karan Jani, professor of physics and astronomy, on creating an AI model to identify gravity waves to detect the presence of black holes. “The idea is to train a model that could be used to solve not just one problem, but a host of problems, and then be known as the Vanderbilt foundational model for gravity waves,” Spencer-Smith says.

Beyond using AI for research, Spencer-Smith also directs the Data Science for Social Good program, a 10-week program for graduate students who receive a stipend to use AI for practical applications. One recent project with The Vanderbilt Kennedy Center Treatment and Research Institute for Autism Spectrum Disorders (TRIAD) helped develop a workplace app for people with autism, providing a virtual coach they could ask questions and receive help for navigating challenging situations. Another project worked with Professor Emerita of Psychology and Human Development Georgene Troseth and Professor Amy Booth, who spent years developing an app to help provide prompts to parents and other caregivers to better engage with their children when reading books. The AI Storybook project has finally realized their vision, using generative AI to suggest questions in real time for any children’s book.

“The whole purpose of this curriculum is to get students to understand how complex history is and how, during these watershed moments, history can turn on a dime. We don’t need to tell them that—they’re living it.” —Holly Tucker

When and how to best deploy AI in classrooms is something best left to individual instructors rather than mandated by university-wide policy, says Doug Fisher, associate professor of computer science and computer engineering. “While the technology is changing so much, it makes sense for us to allow individuals to investigate different options and then come together to compare notes,” says Fisher, who previously oversaw programs in AI for the National Science Foundation and co-taught a class at Vanderbilt on AI ethics.

Some professors may decide that AI is not appropriate to use in entry-level classes, where students are better off developing their own skills before seeking out computer-assisted aid. At the same time, Fisher noted, AI’s propensity for bias—being trained on a vast corpus of data on an imperfect internet—might give instructors pause before using it around sensitive topics such as race and gender studies. While students might feel more comfortable discussing those ideas with an impersonal machine, “there could be problematic exchanges humans are better equipped to handle.”

However the technology is incorporated into the classroom or the lab, it’s clear that the adventure with AI—particularly generative AI—is just beginning. It may take months or years before students and faculty best understand where it can be used most effectively and how it can best augment learning and discovery. In the meantime, it’s clear that AI is affecting learning now. Tucker says that students in her French Revolution class are required to turn in 20 pages by the end of the course—but they are so engaged that the average student turns in 25. “I’d never used ChatGPT before,” says Remi Bristol, one of Tucker’s students. “Now I definitely see myself using it in the future, for readings in classes that are confusing for me or to help prepare for a job interview.”

A recent survey of executives by IBM predicted that up to 40 percent of the workforce will have to reskill to manage AI in the next three years. It’s clear from their experiences in Tucker’s class and others that Vanderbilt students will be ready for that challenge.

“The whole purpose of this curriculum is to get students to understand how complex history is and how, during these watershed moments, history can turn on a dime,” Tucker says. “We don’t need to tell them that—they’re living it.”

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Do research responsibly and ethically on marginalized communities such as LGBTQ+ people

Working together while recognizing each other’s strengths is how we create equitable and impactful community change..

Finn Shelp-Peck is the transgender and gender expansive justice specialist at inclusion tennessee who moved from North Carolina to Nashville in 2022 for graduate school at Vanderbilt University.

As activism and community-centered research evolves, we have a chance to turn a new page in ethical commitments to data collection, distribution, and implementation.

In the last six years I have conducted over 3,000 hours of research in multiple different fields ranging from reproductive and cellular biology to social science and community health.

I have attended and spoken at conferences, written and edited publications, and analyzed and disseminated data. Thankfully, I have been lucky to have incredible mentors who have taught me and guided me through these endeavors.

Through this time I have noticed an opportunity for research to take a more community-centric approach.

Data has been collected on marginalized communities with little regard for their well-being

I love the ways that activism informs research projects and strategies, just as research is informed, inspired, and shaped by social movements and community needs. In Nashville, 48% of LGBT people don’t feel a sense of belonging, showcasing the disconnect between place, community, and purpose.

All of the researchers I know are passionate about what they are doing and the communities they work with. Similarly, all of the activists, advocates, and organizers I know love the communities they serve with every cell of themselves. These fields seem different and separate, but really are deeply dependent on one another.

Historically , marginalized communities have had information and data collected from them without a regard for the physical, emotional, and mental lasting impact of such actions. Those in positions of power and privilege have taken this information for their benefit and often do not implement change using the extracted data but rather leave that to professionals and organizers in different fields.

Data is not subjective, but rather infused with bias shaped by the creator – no matter how hard they try to neutralize it. Big Data and machine learning is not without bias, but inevitably reinforces existing stereotypes and biases because it is created to generalize populations.

In chapter one of her book, "Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy," Cathy O’Neil talks about mathematical models as being mere simplifications which “reflect the judgments and priorities of its creators” (page 21). She goes on to discuss the impact of bias on predictive models for events as benign as the outcome of a baseball game to viciously harmful engrained systems like racism.

More: Tennessee lawmakers prefer to target transgender citizens than solve real-world problems

These four important steps will produce ethical and community-oriented results

Given the history and pattern of Big Data, apprehension about participating in data collection is understandable and expected. This is where I think there is a poignant opportunity for those collecting data to more ethically partner with communities, activists, and organizers to create equitable and impactful programming and resources.

• This starts by including community members, advocates, activists, and organizers in the process of creating surveys and collecting data. Better collaboration will lead to more empathetic and trustworthy surveys.
• Next, there needs to be an intentional and active effort to appropriately compensate participants and organizers for their time and contributions. Taking a survey that asks you to disclose personal and delicate information about yourself is taxing in many ways, asking someone to spend valuable time and remain uncompensated is unethical.
• The third step is making sure that people who participate in the research projects are the first to receive results and are not left guessing about what will come of their time and information. This is an important step in conducting community-centric research.
• Finally, there need to be collaborative efforts in using gathered data to implement impactful programming. While research is important, if the information taken from a community is not given back then it can be harmful and perpetuate an existing power imbalance. This collaboration can look like mutual aid, information sharing, or program development to name a few.

Ultimately, activism and research support one another and are inextricably linked. An effort needs to be made to actively collaborate and support more sustainable and ethical practices. Working together while recognizing each other’s strengths is how we create equitable and impactful community change.

Innovative growers: A view from the top

In this current era of competing priorities and endless disruption and uncertainty, we know that innovation remains a must-have , not just a nice-to-have, when capital is readily available. 1 Matt Banholzer, Michael Birshan, Rebecca Doherty, and Laura LaBerge, “ Innovation: Your solution for weathering uncertainty ,” McKinsey, January 10, 2023. We also know that making a conscious choice to grow  and supporting that choice with the right mindsets, development pathways, and capabilities can yield superior shareholder returns. 2 “ Choosing to grow: The leader’s blueprint ,” McKinsey, July 7, 2022. But what is the role of innovation in growth and vice versa?

Where do innovative growers come from?

To find out, we identified and analyzed about 650 of the largest public companies that achieved profitable growth relative to their industry between 2016 and 2021 while also excelling in the essential capabilities associated with innovation . 3 Our assessment is based on McKinsey’s proprietary database of about 12,000 companies and their relative mastery of capabilities along four innovation categories: aspire/choose, discover/evolve, accelerate/scale, and extend/mobilize. Using machine learning, natural-language processing, and sentiment analysis of employee reviews, we created a score that served as a reliable proxy for innovation capabilities across these categories. We then reviewed companies that grew faster than their industry while delivering positive economic profit between 2016 and 2021. Some of these companies outgrew their peers, others were more innovative than competitors, but 53 companies managed to do both. The 50-plus “innovative growers,” as we call them, are a diverse group, spread across four continents and ten industries. They include renowned brands with a trillion-dollar market capitalization as well as smaller companies that are just starting to make a name for themselves, some as young as three years old (see sidebar, “Where do innovative growers come from?”).

For all their diversity, these companies consistently excel in both growth and innovation—and they share a number of best practices that other companies can learn from.

Do innovative growers perform better than others?

In a word, yes.

Most of our innovative growers achieved total shareholder returns (TSR) above their industry median between 2012 and 2022 (Exhibit 1). The median excess annual shareholder return among these 50-plus companies was 11 points higher than that for Global 2000 companies. What’s more, two-thirds of the innovative growers were in the top quintile of the economic-profit power curve , which represents the distribution of economic profit among Global 2000 companies. 4 Chris Bradley, Martin Hirt, and Sven Smit, “ Strategy to beat the odds ,” McKinsey Quarterly , February 13, 2018. Their presence on the high end of the curve is not surprising: McKinsey research on the power curve points to the importance of making big innovative moves to beat the market, including programmatic M&A , dynamic reallocation of resources, and differentiating product and process improvements. In fact, the research suggests making no moves is a dangerous strategy—one that brings stagnation and underperformance.

What sets innovative growers apart?

The numbers speak for themselves, but when we examined how innovative growers were achieving such a high level of performance, we observed that all demonstrate a mastery of the eight essentials of innovation , which our past research  shows are correlated with strong financial performance.

Specifically, they build innovation into their overall strategy aspirations. They activate critical growth pathways within their core businesses and enter only those adjacent markets where they have the strongest competitive advantage . They pursue excellence in execution and invest in key innovation capabilities. And they use M&A, particularly programmatic M&A, to extend their innovation reach.

Aspire: Link innovation to growth aspirations

According to our research, innovative growers unfailingly put innovation at the center of strategic and financial discussions, thereby signaling its importance to the growth and health of the organization. For instance, our review of the innovative growers’ earnings calls reveals that they talk about innovation twice as much as their peers 5 We analyzed a lexicon of innovation keywords across earnings calls across our sample set and determined the relative frequency of usage and discussion of innovation topics versus the overall management discussion. and, in those conversations, emphasize innovation as a means to create profitable and sustainable growth . This is consistent with our previous research on “ courageous growers ” and the importance of cultivating an innovation mindset among employees. 6 “ Courageous growth: Six strategies for continuous growth outperformance ,” McKinsey, October 23, 2023. Innovative growers communicate to employees achievable aspirations and clear targets to reduce fears of failure, criticism, and negative career impact  that often hold back innovation. Innovative growers share frequent progress updates and success stories to inspire and motivate teams and investors. What’s more, innovative growers frequently voice their commitment to investing more resources in talent and digital capabilities, and they are almost three times more likely than their fast-growing but not innovative peers to frame their efforts as a “transformation.”

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High digital aspirations. Digital transformation was the impetus for innovation at one leading retailer among our innovative growers: the company sought to increase its online sales by introducing new features such as faster mobile checkout and an app with augmented reality built into it so customers could visualize how the retailer’s products might look in their homes. The CEO and other C-suite executives reinforced the importance of “transformation through innovation” in town hall meetings with employees, during earnings calls, in public interviews, and in press releases. The leaders’ words and investments sent a clear message to customers, employees, and other stakeholders about the importance of innovation in the retailer’s ability to transform and grow. And the efforts paid off: over time, as the new features were launched, the company’s online sales grew 80 percent, with digital sales accounting for 60 percent of overall revenue.

Activate: Pursue multiple pathways to growth

Our research shows that innovative growers deliver market-leading revenue growth in both their core businesses and when entering adjacent customer segments, industries, or geographies. In their core businesses, for instance, innovative growers tend to generate twice as much excess growth, even relative to other companies that outperform on growth. And when diversifying into adjacent segments, innovative growers achieve at least double the revenue growth compared with other firms (Exhibit 2).

They do this by entering adjacent business areas  where they can connect to one or more clear opportunities to create value, such as customer-driven growth, capability-driven growth, value chain–driven growth, or business model innovation in areas such as digital and sustainability. For instance, a recent McKinsey analysis  shows that chemical players with low-carbon product portfolios or high exposure to end markets supporting sustainability grew their shareholder returns at more than double the rate of sustainability laggards between 2016 and 2021. 7 “ The triple play: Growth, profit, and sustainability ,” McKinsey, August 9, 2023.

In fact, our data indicate that innovative growers combine two or more of the previously mentioned value propositions in more than 70 percent of the adjacencies they enter (compared with less than 25 percent among peers). They seem to prioritize growth in those adjacencies where there is some similarity among portfolios and an obvious “right to win.” And make no mistake, portfolio similarity matters: consider General Mills’ purchase of Pillsbury, a company that shared many of the same competencies and assets. This move allowed General Mills to reduce its purchasing, manufacturing, and distribution costs and raise its operating profit by about 70 percent. 8 Chris Bradley, Rebecca Doherty, Nicholas Northcote, and Tido Röder, “ The ten rules of growth ,” McKinsey, August 12, 2022.

Additionally, innovative growers are using advanced analytics and other digital tools to identify hidden growth opportunities, and then they are going through a rigorous process of selecting the just-right operating model and governance structure for the new business and appointing senior leaders with the competencies most needed in the new business. 9 Chris Bradley, Rebecca Doherty, Anna Koivuniemi, and Nicholas Northcote, “ Igniting your next growth business ,” McKinsey, July 23, 2021.

Game, set, and match. A leading technology company with deep expertise in hardware design, artificial intelligence, and cloud computing acquired a gaming company with the goal of using its own capabilities to improve the gaming company’s offerings. The pathway to growth here was relatively clear and unencumbered; although they were in slightly different segments of the technology market, the companies boasted similar product portfolios, and once the technical capabilities were integrated, the joint venture was able to go to market with several special releases of legacy games and one-off “special event” gaming offerings, all of which were well received.

Execute: Invest productively in all innovation capabilities

Our research shows that innovative growers invest productively in a range of critical innovation capabilities—including R&D, resourcing, and operational agility—leading to strong business outcomes. In fact, they delivered more than five points of additional excess gross margin versus other Global 2000 firms, which is a key indicator of product differentiation . 10 “ Strategy to beat the odds ,” February 2018.

R&D. Innovative growers tend to deliver more tangible outcomes from their R&D investments than their peers. In our research, they generated, on average, 100-plus more patents than their peers but also delivered more strong patents—or patents with broad applicability and lots of citations to other patents. In fact, over the past two decades, innovative growers were awarded three times as many strong patents compared with industry peers (Exhibit 3). And the presence of strong patents often indicates higher value creation potential.

Resourcing and operations. Innovative growers are also more likely than peers to have adopted agile operating models and implemented rigorous and dynamic resource allocation processes. They also tend to invest more in digital and analytics and other new technologies compared with peers: our research shows innovative growers have 30 percent more digital and analytics personnel on staff compared with industry peers. And in McKinsey’s recent digital strategy survey of more than 1,000 companies, there was a clear link between organizations with strong innovation cultures and operating models and their ability to increase value through new technologies, including generative AI. 11 Matt Banholzer, Ben Fletcher, Laura LaBerge, and Jon McClain, “ Companies with innovative cultures have a big edge with generative AI ,” McKinsey, August 31, 2023. Even in the current uncertain business climate, almost 90 percent of the survey respondents said they are still looking for new growth. Over the past two years, they have been allocating resources to a range of growth pathways—expanding the core, innovating in adjacent areas, or igniting breakout businesses (Exhibit 4). 12 “ Companies with innovative cultures have a big edge with generative AI ,” August 31, 2023.

Smart resourcing, smart growth. Combining strong innovation capabilities with appropriate levels of resourcing can result in significant value creation opportunities. Senior management at one medical-technology company wanted to build a new line of surgical robotics offerings and, to that end, increased the amount of resources allocated to the company’s R&D function. Over time, that R&D team generated a flood of new patents, averaging about 750 more patents than its medtech peers and delivering one and a half times the total shareholder return. Similarly, a global technology company invested upward of $3 billion to adapt its existing hardware products to support applications in the fast-growing AI and data-processing spaces, more than tripling its annual capital expenditure between 2017 and 2022. This bold move has resulted in 20 percent annual revenue growth at the company over the past five years.

Extend: Cultivate a strong M&A capability

In our experience, innovative growers also distinguish themselves through their dealmaking—and specifically, in their ability to cultivate a strong M&A capability (alongside strong capabilities in R&D, finance, operations). To be clear, there are many “nondigital” technologies (new molecules, for instance). However, looking at digital M&A provides one illustrative lens. For instance, our research shows that innovative growers complete three times more digital M&A deals 13 Digital M&A deals are those that target assets or capabilities in the digital, analytics, or technology spaces. compared with peers, demonstrating a desire to acquire promising technical capabilities and intellectual property (IP) and a willingness to embrace new technologies and methods to stay ahead of the competition. 14 “ Are you chasing the right digital assets? ,” McKinsey, December 22, 2021. Additionally, innovative growers routinely define their growth and M&A objectives up front , and leaders come to a shared understanding of the types of deals they want to target, which allows innovative growers to act with speed and purpose when M&A opportunities come up. What’s more, innovative growers are 50 percent more likely than peers to follow a programmatic approach to M&A, 15 A programmatic approach to M&A involves creating value by choreographing a series of deals (two or more) around a specific business case or M&A theme rather than pursuing singular “big bang” transactions. which McKinsey has repeatedly reaffirmed is far more likely than other M&A approaches to lead to stronger performance and less risk. 16 “ How one approach to M&A is more likely to create value than all others ,” McKinsey Quarterly , October 13, 2021.

Forging an ecosystem through programmatic M&A. One technology company pursued a series of midsize acquisitions to bolster its product offerings and exploit cross-product synergies to create an ecosystem for “home security” products. Over a two-year period, the company acquired a wireless security camera player, a home security company, and a DIY home security system provider. These acquisitions came with associated patents, such as the smart doorbell, and allowed the company to expand its reach and to innovate new products (combining the acquired IP with the company’s own hardware and software products).

Innovative growers are delivering profitable growth relative to their industry while also excelling in the essential capabilities associated with innovation. Our research reveals the degree to which their focus on both is helping these organizations create lasting value. It also suggests that other companies, too, can join this small but diverse set of outperformers by putting innovation at the center of all decision making and supporting it with the right mindsets, pursuing multiple pathways to growth and innovation, and establishing the right capabilities across R&D, digital, analytics, and M&A.

The path may be steep, and the transformation will likely take time and dedicated management attention, but the companies that seek to emulate the innovative growers may eventually achieve a profitable balance between today’s growth objectives and tomorrow’s innovation potential.

Matt Banholzer is a partner in McKinsey’s Chicago office, Rebecca Doherty is a partner in the Bay Area office, Alex Morris is a partner in the Toronto office, and Scott Schwaitzberg is an associate partner in the New York office.

The authors wish to thank Guillermo Domínguez, Gopal Galgali, Brooke Harvey, Tim Koller, Laura LaBerge, Karin Löffler, Karthik Ramesh, Werner Rehm, Tido Röder, Erik Roth, Eshita Sangal, and Jill Zucker for their contributions to this article.

This article was edited by Roberta Fusaro, an editorial director in the Waltham, Massachusetts, office.

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What does friendship look like in America?  

Americans place a lot of importance on friendship. In fact, 61% of U.S. adults say having close friends is extremely or very important for people to live a fulfilling life, according to a recent Pew Research Center survey . This is far higher than the shares who say the same about being married (23%), having children (26%) or having a lot of money (24%).

Pew Research Center conducted this analysis to understand Americans’ views of and experiences with friendship. It is based on a survey of 5,057 U.S. adults conducted from July 17-23, 2023. Everyone who took part in this survey is a member of the Center’s American Trends Panel (ATP), an online survey panel that is recruited through national, random sampling of residential addresses. This way nearly all U.S. adults have a chance of selection. The survey is weighted to be representative of the U.S. adult population by gender, race, ethnicity, partisan affiliation, education and other categories.  Read more about the ATP’s methodology .

Here are the  questions used for the analysis , along with responses, and its methodology .

We decided to ask a few more questions to better understand how Americans are experiencing friendship today. Here’s what we found:  

Number of close friends

A narrow majority of adults (53%) say they have between one and four close friends, while a significant share (38%) say they have five or more. Some 8% say they have no close friends.

There’s an age divide in the number of close friends people have. About half of adults 65 and older (49%) say they have five or more close friends, compared with 40% of those 50 to 64, 34% of those 30 to 49 and 32% of those younger than 30. In turn, adults under 50 are more likely than their older counterparts to say they have between one and four close friends.

There are only modest differences in the number of close friendships men and women have. Half of men and 55% of women say they have between one and four close friends. And 40% of men and 36% of women say they have five or more close friends.

Gender of friends

Most adults (66%) say all or most of their close friends are the same gender as them. Women are more likely to say this than men (71% vs. 61%).

Among adults ages 50 and older, 74% of women – compared with 59% of men – say all or most of their close friends are the same gender as them. Among adults younger than 50, the difference is much smaller: 67% of women in this age group say this, as do 63% of men.

Race and ethnicity of friends

A majority of adults (63%) say all or most of their close friends are the same race or ethnicity as them – though this varies across racial and ethnic groups.

White adults (70%) are more likely than Black (62%), Hispanic (47%) and Asian adults (52%) to say this.

This also differs by age. Adults 65 and older are the most likely (70%) to say all or most of their close friends share their race or ethnicity, compared with 53% of adults under 30 – the lowest share among any age group.

Satisfaction with friendships

The majority of Americans with at least one close friend (72%) say they are either completely or very satisfied with the quality of their friendships. Those 50 and older are more likely than their younger counterparts to be highly satisfied with their friendships (77% vs. 67%).

The survey also finds that having more friends is linked to being more satisfied with those friendships. Some 81% of those with five or more close friends say they are completely or very satisfied with their friendships. By comparison, 65% of those with one to four close friends say the same.

The survey didn’t ask adults who reported having no close friends about their level of satisfaction with their friendships.

What do friends talk about?

Of the conversation topics asked about, the most common are work and family life. Among those with at least one close friend, 58% say work comes up in conversation extremely often or often, while 57% say family comes up this often. About half say the same about current events (48%).

There are differences by gender and age in the subjects that Americans discuss with their close friends:

Differences by gender

Women are much more likely than men to say they talk to their close friends about their family extremely often or often (67% vs. 47%).

Women also report talking about their physical health (41% vs. 31%) and mental health (31% vs. 15%) more often than men do with close friends. The gender gap on mental health is particularly wide among adults younger than 50: 43% of women in this age group, compared with 20% of men, say they often discuss this topic with close friends.

By smaller but still significant margins, women are also more likely than men to talk often about their work (61% vs. 54%) and pop culture (37% vs. 32%) with their close friends.

Men, in turn, are more likely than women to say they talk with their close friends about sports (37% vs. 13%) and current events (53% vs. 44%).

Differences by age

Those ages 65 and older (45%) are more likely than younger Americans to say they often talk with their close friends about their physical health.

There are two topics where young adults – those under 30 – stand out from other age groups.

About half of these young adults (52%) say they often talk with their friends about pop culture. This compares with about a third or fewer among older age groups. And young adults are more likely to say they often talk about their mental health with close friends: 37% say this, compared with 29% of those 30 to 49 and 14% of those 50 and older.

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Do women who live together get their periods together, or is it a myth?

What research says about the common assumption.

Is it true women who live together will menstruate at the same time?

Although some women believe this, the answer, experts say, is no, not really.

Menstrual synchrony, as it is known, does occur occasionally, but not because of proximity or the release of chemical pheromones, which has long been a popular theory. “It’s a mathematical coincidence,” says Jeffrey Schank, professor of psychology at the University of California at Davis, whose studies provide an explanation as to why women in close quarters sometimes menstruate at the same time. “In one sense, it’s a real experience, but it’s due to statistical characteristics of cycles, not nearness or any biological processes. It’s not pheromones or anything evolutionary. There’s no good evolutionary reason for it — there’s no evolutionary advantage to having babies at the same time.”

Women don’t always cycle at the same frequency, so irregularity can sometimes lead to menstruation occurring together, “but it’s statistical,” Schank says. “Cycles vary in length, and all this variability will lead to convergence and divergence.” Not all women menstruate on a regular schedule; while many have a 28-day cycle, others can have shorter, longer or very irregular ones.

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The belief that women sharing space had their periods together originated in a 1971 paper by psychologist Martha K. McClintock, who studied 135 women in a college dormitory and concluded that social interaction has a strong effect on the menstrual cycle, probably because of something physiological. Support for this so-called McClintock effect has persisted, despite many later studies that were inconsistent and failed to prove her hypothesis and challenged her methodology.

McClintock, professor emerita of psychology at the University of Chicago, says the science has changed since her original paper was published. She now believes that pheromones secreted from the armpits of women in close quarters changes the timing of ovulation, prompting simultaneous ovulation — not menstruation.“I am aware of all this focus on mathematics, but we’ve gone beyond that,” she says. “In the phrase ‘menstrual synchrony,’ scratch out ‘menstrual’ and put in ‘ovulation’.“

Social psychologist Leonard Weller, professor emeritus in the department of sociology and anthropology at Bar-Ilan University in Israel, conducted a series of small studies — about 15 by his count — in the 1990s with his son, Aron Weller, professor of psychology at Bar-Ilan, on menstrual synchrony. They found that sometimes women were in sync — and sometimes they weren’t. He agrees with Schank that the alignment in cycles was a mathematical coincidence.

“The majority opinion is that it is a mathematical coincidence,” Leonard Weller says. “If you plot the onset for each of two women over a period of time, you will probably find they will converge as well as become disparate, having nothing to do with pheromone influence. Also, assuming the normal menstrual cycle lasts about five days, two women will have some overlap in the timing of their cycles. This has nothing to do with synchrony.”

Noha Ahmed, an obstetrician-gynecology resident physician in D.C., speaking on behalf of the American College of Obstetricians and Gynecologists, remembers hearing about menstrual synchrony when she was in college, but says existing studies have been too varied and conducted in too small samples to support the idea.

“It can be hard to say why so many believe this very common misconception,” she says. “If these individuals are all living together, they may experience overlap in the timing of their periods. I imagine that this is where the misconception stems from.”

Menstrual synchrony can provide a form of gendered solidarity for some — a sense of sisterhood — for an experience traditionally regarded as shameful and stigmatizing, says Breanne Fahs, professor of women and gender studies at Arizona State University and author of two studies that explore the sociological implications of many women’s belief in menstrual synchrony.

“For some women, there’s also the notion that menstrual synchrony is somehow magical, and they become very upset when you tell them it probably isn’t true,” Fahs says.

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Poll: Election interest hits new low in tight Biden-Trump race

The share of voters who say they have high interest in the 2024 election has hit a nearly 20-year low at this point in a presidential race, according to the latest national NBC News poll , with majorities holding negative views of both President Joe Biden and former President Donald Trump.

The poll also shows Biden trimming Trump’s previous lead to just 2 points in a head-to-head contest, an improvement within the margin of error compared to the previous survey, as Biden bests Trump on the issues of abortion and uniting the country, while Trump is ahead on competency and dealing with inflation.

And it finds inflation and immigration topping the list of most important issues facing the country, as just one-third of voters give Biden credit for an improving economy.

But what also stands out in the survey is how the low voter interest and the independent candidacy of Robert F. Kennedy Jr. could scramble what has been a stable presidential contest with more than six months until Election Day. While Trump holds a 2-point edge over Biden head to head, Biden leads Trump by 2 points in a five-way ballot test including Kennedy and other third-party candidates.

“I don’t think Biden has done much as a president. And if Trump gets elected, I just feel like it’s going to be the same thing as it was before Biden got elected,” said poll respondent Devin Fletcher, 37, of Wayne, Michigan, a Democrat who said he’s still voting for Biden.

“I just don’t feel like I have a candidate that I’m excited to vote for,” Fletcher added.

Another poll respondent from New Jersey, who declined to provide her name and voted for Biden in 2020, said she wouldn’t be voting in November.

“Our candidates are horrible. I have no interest in voting for Biden. He did nothing. And I absolutely will not vote for Trump,” she said.

Democratic pollster Jeff Horwitt of Hart Research Associates, who conducted the survey with Republican pollster Bill McInturff of Public Opinion Strategies, said, “Americans don’t agree on much these days, but nothing unites the country more than voters’ desire to tune this election out.”

The poll was conducted April 12-16, during yet another turbulent time in American politics, including the  beginning of Trump’s criminal trial  in New York and new attacks and heightened tensions  in the Middle East.

According to the poll, 64% of registered voters say they have high levels of interest in November’s election — registering either a “9” or a 10” on a 10-point scale of interest.

That’s lower than what the NBC News poll showed at this time in the 2008 (74%), 2012 (67%), 2016 (69%) and 2020 (77%) presidential contests.

The question dates to the 2008 election cycle. The lowest level of high election interest in the poll during a presidential cycle was in March 2012 — at 59%. But it quickly ticked up in the next survey.

This election cycle, high interest has been both low and relatively flat for months, according to the poll.

McInturff, the Republican pollster, says the high level of interest in the poll has “always been a signal for the level of turnout” for a presidential contest.

“It makes it very hard for us to predict turnout this far in advance of November, but every signal is turnout will be a lower percentage of eligible voters than in 2020,” he said.

By party, the current poll shows 70% of self-identified Republicans saying they have high interest in the coming election, compared with 65% of Democrats who say so.

Independents are at 48%, while only 36% of voters ages 18 to 34 rate themselves as highly interested in the election.

“They just aren’t low interest,” McInturff said of young voters. “They are off-the-charts low.”

NBC News poll: Frequently asked questions

Professional pollsters at a Democratic polling firm (Hart Research Associates) and a Republican firm (Public Opinion Strategies) have worked together to conduct and operate this poll since 1989. (Coldwater Corporation served as the Republican firm from 1989-2004.)

The polling firms employ a call center, where live interviewers speak by cell phone and telephone with a cross section of (usually) 1,000 respondents. The respondents are randomly selected from national lists of households and cell numbers. Respondents are asked for by name, starting with the youngest male adult or female adult in the household.

One of the common questions that critics ask of polls is, "I wasn't interviewed, so why should this poll matter?” By interviewing 1,000 respondents and applying minimal weights based on race, ethnicity, age, gender, education and the 2020 presidential vote, the poll achieves a representative sample of the nation at large – with a margin of error at a 95% confidence level.

NBC News editors and reporters — along with the pollsters at Hart Research and Public Opinion Strategies — all work to formulate the questions to try to capture the news and current events NBC is trying to gauge. Both Hart Research and Public Opinion Strategies work to ensure the language and placement of the questions are as neutral as possible.

Biden trims Trump’s lead

The poll also finds Trump narrowly ahead of Biden by 2 points among registered voters in a head-to-head matchup, 46% to 44% — down from Trump’s 5-point advantage in January, 47% to 42%.

The movement, which is within the poll’s margin of error of plus or minus 3.1 percentage points, is consistent with what other national polls have found in the Trump-Biden race.

Trump’s biggest advantages are among men (53% to 37%), white voters (54% to 37%) and white voters without college degrees (65% to 25%).

Biden’s top advantages are among Black voters (71% to 13%), women (50% to 39%) and Latinos (49% to 39%).

The poll shows the two candidates are essentially tied among independents (Biden 36%, Trump 34%) and voters ages 18-34 (Biden 44%, Trump 43%). One of the big polling mysteries this cycle is whether young voters have defected from Biden (as the NBC News poll has found over multiple surveys) or whether Democrats have maintained their advantage among that demographic.

When the ballot is expanded to five named candidates, Biden takes a 2-point lead over Trump: Biden 39%, Trump 37%, Kennedy 13%, Jill Stein 3% and Cornel West 2%.

Again, the result between Biden and Trump is within the poll’s margin of error.

Notably, the poll finds a greater share of Trump voters from the head-to-head matchup supporting Kennedy in the expanded ballot compared with Biden voters, different from the results of some other surveys.

(Read more here about how Kennedy's candidacy affe cts the 2024 race, according to the poll.)

The president’s approval rating ticks up to 42%

In addition, the poll found 42% of registered voters approving of Biden’s overall job performance — up 5 points since January’s NBC News poll, which found Biden at the lowest point of his presidency.

Fifty-six percent of voters say they disapprove of the job he has done, which is down 4 points from January.

Biden’s gains over the past few months have come from key parts of his 2020   base, especially among Democrats and Black voters. But he continues to hold low ratings among Latinos (40% approval), young voters (37%) and independents (36%).

“The data across this poll show that Joe Biden has begun to gain some ground in rebuilding his coalition from 2020,” said Horwitt, the Democratic pollster. “The question is whether he can build upon this momentum and make inroads with the groups of voters that still are holding back support.”

But McInturff, the GOP pollster, points out that the only recent presidents   who lost re-election had approval ratings higher than Biden’s at this point in the election cycle: George H.W. Bush (43%) and Trump (46%).

“President Biden has a precarious hold on the presidency and is in a difficult position as it relates to his re-election,” McInturff said.

On the issues, 39% of voters say they approve of Biden’s handling of the economy (up from 36% in January), 28% approve of his handling of border security and immigration, and just 27% approve of his handling of the Israel-Hamas war (down from 29% in January).

Voters gave Biden his highest issue rating on   addressing student loan debt, with 44% approving of his handling of the issue, compared with 51% who say they disapprove.

Biden leads on abortion and unity; Trump leads on inflation and competency

The NBC News poll asked voters to determine which candidate they thought is better on several different issues and attributes.

Biden holds a 15-point advantage over Trump on dealing with the issue of abortion, and he is ahead by 9 points on having the ability to bring the country together — though that is down from his 24-point advantage on that issue in the September 2020 NBC News poll.

Trump, meanwhile, leads in having the ability to handle a crisis (by 4 points), in having a strong record of accomplishments (by 7 points), in being competent and effective (by 11 points), in having the necessary mental and physical health to be president (by 19 points) and in dealing with inflation and the cost of living (by 22 points).

Inflation, immigration are the top 2024 issues

Inflation and the cost of living top the list of issues in the poll, with 23% of voters saying they’re the most important issue facing the country.

The other top voters is   immigration and the situation at the border (22%) — followed by   threats to democracy (16%), jobs and the economy (11%), abortion (6%) and health care (6%).

In addition, 63% of voters say their families’ incomes are falling behind the cost of living — essentially unchanged from what the poll found in 2022 and 2023.

And 53% of voters say the country’s economy hasn’t improved, compared with 33% who say that it has improved and that Biden deserves some credit for it and another 8% who agree the economy has improved but don’t give him credit for it.

“If I look back to when I had all three of my children in the house — we only have one child left in the house now, and we’re spending more now than what we did when we had a family of five,” said poll respondent Art Fales, 45, of Florida, who says he’s most likely voting for Trump.

But on a separate question — is there an issue so important that you’ll vote for or against a candidate solely on that basis? — the top responses are protecting democracy and constitutional rights (28%), immigration and border security (20%) and abortion (19%).

Indeed, 30% of Democrats, 29% of young voters and 27% of women say they are single-issue voters on abortion.

“I have a right to what I do with my body,” said poll respondent Amanda Willis, 28, of Louisiana, who said she’s voting for Biden. “And I don’t believe that other people should have the ability to determine that.”

Other poll findings

• With Trump’s first criminal trial underway, 50% of voters say he is being held to the same standard as anyone else when it comes to his multiple legal challenges. That compares with 43% who believe he’s being unfairly targeted in the trials. 
• 52% of voters have unfavorable views of Biden, while 53% share the same views of Trump.
• And Democrats and Republicans are essentially tied in congressional preference, with 47% of voters preferring Republicans to control Congress and 46% wanting Democrats in charge. Republicans held a 4-point lead on this question in January.

The NBC News poll of 1,000 registered voters nationwide — 891 contacted via cellphone — was conducted April 12-16, and it has an overall margin of error of plus or minus 3.1 percentage points.

Mark Murray is a senior political editor at NBC News.

Sarah Dean is a 2024 NBC News campaign embed.