academic research study definition

Introduction to Academic Research

What is Academic Research?

• Planning your Research
• Search Strategies
• Choosing Sources
• Choosing Databases
• Scholarly Sources
• Evaluating Websites
• Citing your Sources

Academic research involves a thorough investigation into what is known about a given topic. In most cases, you will be required to examine and analyze scholarly sources when completing your assignments (unless otherwise indicated by your instructor).  Scholarly sources help:

• Add depth to your understanding.
• Strengthen your argument.
• Reduce bias and misconceptions.

Research assignments are designed to help you think like a researcher and learn good research skills, such as selecting appropriate topics, identifying keywords, searching for information efficiently, and evaluating your sources. In this guide, we'll cover some of the key information and skills you need to know to succeed at Sheridan.

In this Guide

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What is Academic Research?

After completing this module you will be able to:

• recognize why information exists, who creates it, and how information of all kinds can be valuable, even when it’s biased.
• understand what scholarly research is, how to find it, how the process of peer-review works, and how it gets published.
• identify types of databases and understand why databases are critical for academic research

How to use this module

This module is organized into a number of pages. To navigate, you can either:

• use the “Previous” and “Next” buttons at the bottom of each page (suggested)

• follow the links in the “Contents” menu on the left side of the page

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Academic Research

Raysonho/ Wikimedia Commons. Academic research can be intense, stimulating, and rewarding. But it is important to know that a research career involves many activities besides research. Scientists spend their time writing applications for funding to do research, as well as writing scientific papers to report the findings of their research. In addition, they spend time presenting their research in oral or poster form to other scientists at group meetings, institutional meetings, and scientific conferences; they also spend time teaching students about their field of study. A scientist's life is often full of tasks that need to be done and most scientists work very hard, but they also love what they do.

Fields of Study

• Clinical Scientist: David Fredricks
• Epidemiologist: Gloria Coronado
• Geneticist: Katie Peichel
• Clinical Research: Dana Panteleef
• Research Technician: Nanna Hansen

If you're interested in a general sense in academic research, the first thing to figure out is which field of research is best for you.

The fundamental task of research is asking questions. There are many areas of research in the life sciences, and they generally fall into three categories based on the types of questions that are asked and the tools that are used to answer the questions:

Basic Research

Clinical research, population-based research.

Basic researchers ask questions about how fundamental life processes work. Examples of questions include the following:

• What are the mechanisms that determine how and when cells divide?
• How do DNA mutations associated with a disease occur?
• How and why do cells age?
• How and why does one type of cell work differently from another type of cell?

Basic researchers usually work in laboratories with other scientists, usually with one faculty member leading a group of postdoctoral fellows, graduate students, and lab technicians who do most of the lab work. The hours can be very long and the work can be challenging, especially for graduate students and postdoctoral fellows. Basic researchers often ask their questions using model organisms, including yeast, worms, flies, fish, and mice.

• Scientific Recruiter: Scott Canavera
• Staff Scientist: Tom Paulson
• Shared Resources: Julie Randolph-Habecker
• Faculty Member: Wendy Leisenring

Clinical researchers ask questions about how disease occurs and how it can be cured in humans. Examples of questions include the following:

• How can we manipulate the body's immune system to improve treatment of a disease?
• How can we create a drug to improve disease survival?
• What are the long-term impacts of treatment on quality of life?

Clinical researchers work in laboratories that are very similar to basic researchers, but they often work with human tissue samples to ask their questions. Many clinical researchers find it rewarding to work on a question that may have an impact that they will eventually see come to fruition. At the same time, when you're working with human tissue, you usually have a limited amount of it so the risks of making a mistake that will lose your sample could be high. Clinical researchers will often collaborate with biostatisticians to best design and analyze their studies in order to yield the maximum amount of relevant information.

Population-based research is done by epidemiologists who ask questions to determine how diet, genetics, and lifestyle may influence the risk of disease. They ask these questions in one of two ways:

• by following a group of people over time and correlating exposure to who gets a disease;
• by asking a group of people with a disease about their lifestyle and diet choices and comparing the data to a randomly chosen group without the disease in order to look for differences between the two groups.

The types of questions they ask include the following:

• How can we best prevent teenagers from starting to smoke?
• Do some genetic variants place a person at greater risk for cancer?
• Do vitamins help prevent cancer?
• Does exposure to certain chemicals increase the risk of getting a particular disease?

Epidemiologists also collaborate with biostatisticians in order to design and analyze studies so they can get the most information from them. Rather than work in a lab, epidemiologists often need no more than a desk and computer. However, the interdisciplinary field of molecular epidemiology is changing this, and many epidemiologists ask questions about how a particular gene can influence disease risk, rather than, or in addition to, a lifestyle exposure.

Roles in Research

Faculty member.

Faculty members usually have Ph.D.'s or M.D.'s and have gone through graduate school or medical school followed by several years of being a postdoctoral fellow or medical resident. A faculty member is the leader of their own lab or work group and determines the direction of the research in their group. Most faculty members spend a good deal of their time writing grant proposals and manuscripts, reading research papers, reviewing colleagues' manuscripts and grant proposals, thinking and talking with others about their research to gain new ideas, and mentoring the people in their group.

Faculty positions are usually very competitive to get and are often a result of hard work over many years. However, most faculty members love what they do and wouldn't trade it for anything.

Research Scientist

Shared resource specialist, technician and other support staff, administrative positions.

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ARTiFACTS / Blog / What Is Academic Research and What Does It Look Like in Practice?

• Science Students

What Is Academic Research and What Does It Look Like in Practice?

Table of contents:

We’ve all heard the phrase “according to a new study” or “research shows” but have you ever wondered what that actually means?

It’s obvious that research is important because we hear about it all of the time in all parts of life. What is academic research and why is it important?

Research comes in all different forms and places. And whether we know it or not, it affects most things that we deal with in our lives. From the technology that we use to the medicine we take. Research is vital to improvement.

So let’s dive into what research is, how it happens, and why it should be important to you.

What is a Research Project?

A research project is when someone conducts an experiment to find the answers to a question or to solve a problem they have observed.

When we think of an experiment, we often think about test tubes and beakers. But that is not the only kind of experiment that can be run.

The possibilities for research projects are really endless. It could be following a group of people over some time, it could be testing new technology, or it could be growing a plant with different variables.

A research project can propel the study of any field of interest.

The only requirement is that there is a problem to be solved, a theory to be verified, or a question to be answered. If one of those exists, a research project can be developed to find the resolution.

There are two main types of research projects; academic and professional.

Academic research is focused primarily on making new discoveries for the scientific community. Professional research is geared more towards solving a specific problem for an organization, often a business, or its customers.

The two are both  valid and contribute to progress . But we are going to focus primarily on academic research.

What is Academic Research?

While any research is good and can, in certain cases, be helpful. There is a major difference between casual research and academic research.

As was mentioned before, academic research is usually intended for the sole purpose of creating knowledge. It is not designed to benefit a specific company or organization. Academic research is designed to be from a voice of authority and can change how people view whatever is being researched. For this reason, it is held to a high standard.

Academic research follows the  scientific method  as a way to ensure that objectivity is kept at all times.

The scientific method follows the same pattern from beginning to end in order to find the most logical conclusion for the question at hand. The researcher creates a hypothesis, which is the answer she believes she will find.

The hypothesis can be a little bit tricky because though it is important (the project is just trying to prove or disprove that thought), the researcher cannot let it sway the project.

Any biases or preconceived opinions can really sway the findings and conclusions if there are no safeguards put in place. When the research is not done to academic standards, it can be hard to trust.

And what is the point of doing the research if the audience cannot trust the conclusions?

The point of research is to find ways to improve our understanding of what is being studied or to verify that our understanding of the subject is correct. So if you as a researcher find a better way or discover something new but the findings cannot be trusted, then no change will be made.

What is Academic Writing?

So once the experiment has been completed and the conclusion found, what happens next? How does the researcher share what they’ve learned?

Most often, the researcher will publish their study and findings as an academic paper in a journal. These are established publications with a reputation for bringing valuable, valid information  to the public.

When a researcher writes up the findings from their experiment, they have to use an academic writing style in order to be published.

This style of writing is generally more formal with a rigid tone. There is no common narrative, instead just the methods, facts or data and conclusions are presented. The technical jargon of that discipline, such as chemistry, or their industry is used as well.

The whole goal of the academic writing style is to articulate exactly what was done and exactly what was found. These articles are very straight-forward to read, especially if you understand that area of expertise and its technical words.

It’s also very important to explain the findings in a clear and straight forward way with no added opinions.

The writing style is important to keep the validity of the research and the article intact. The better written the article, the more likely it is to be published which is the whole goal.

What Does Peer-Reviewed Mean?

An important aspect of a legitimate journal article from an academic research project is peer review.

When a research project or research article has been peer-reviewed it means that the procedures and findings have undergone intense scrutiny by others who are already familiar with the topic and been found to be valid.

This process can look different depending on the specific field the research is being done in and where it is being done. But the process always takes place before the research is presented in an academic journal.

The paper is submitted to various peers and experts in the same field. They review the case, research, and findings and give recommendations for edits before it is published.

When an article has been peer-reviewed, it shows the reader that the findings being presented are valid.

The peers or experts who are reviewing are looking for how valid the findings are and also whether the information can be trusted. They may suggest taking out parts that are not helpful or for changes the make the paper more insightful. And they may point out problems with the methods used and suggest ways to fix them.

A peer-reviewed academic article is typically viewed as more trustworthy than an article that was not peer-reviewed.

Who is Involved in Academic Research?

Academic research involves a few different people and groups every time. Each group is necessary to make the research effective.

The first person is the researcher. This is the person (or group) conducting the experiments and writing the articles. The next is the university or the organization sponsoring the research. And last is the publisher, which is the academic journal that will distribute the academic article.

These three groups rely on each other to be able to meet their individual needs within the research realm. The researcher needs a reputable publication to publish their academic paper to make it legitimate. Academic publications need researchers who do interesting work.

They all work together to bring innovation and increase knowledge.

Why is Academic Research and Writing Important?

Okay, so now that we understand a little bit about what research is and how it works. Now, why is it important for each of us.

Higher education institutions in America spent more than  $71 billion in research  in 2018. This is a very clear indicator of how important research is. If there wasn’t a need for it, there wouldn’t be so much money spent.

People conduct research experiments and studies to enhance development and growth.

Academic research and writing are the catalysts to change in many ways.

Once there is a discovery made in a field that often leads to more inquiries and deeper dives into the subject. It can become like a domino effect for new, increased knowledge.

Research studies often show experts in the field where new opportunities are. These opportunities may come in the form of another research study, a new way of looking at the subject, a new organization, or a new invention.

Another reason that research can be important, especially for major organizations or universities, is to pique interest in the field being studied. When there are new, major developments in a field, the buzz from that is exciting and often leads to others wanting to study that same topic.

When research is reported it allows for more confidence in the way that things are understood. If a theory is studied and proven correct, those in the field can be assured that they are doing things right. If it is proven incorrect, then adjustments can be made moving forward.

Research is vital to the continual evolution and improvements we all seek, without it everything would always stay the same.

How is Academic Research Used in Practice?

We’ve talked a lot about how academic research can lead to change and progress. But how is that done?

Well, that depends on the field of study. But let’s look at a few examples.

In healthcare, academic research is used to allow the provider an opportunity to use evidence-based practice techniques. This means that the way they are treating their patients comes from specific research studies and can be backed up.

In education, academic research is used to teach concepts and principles. The teacher can use the latest data collected from a research study to prove a point or emphasize the importance.

Educating on research is also done to show the continual progression of the field of interest.

In technology, research studies are done to see how the equipment or systems can be improved. There is always better technology coming out and that is due, in part, to continual research being done on how it can be improved.

When used correctly, academic research can be a vital piece in an industry. If the right question is asked and studied, the results can be life-changing for those who are involved.

Why Get Involved in Academic Research?

From the outside, the world of academic research can seem tedious and boring. But that is actually pretty far from the truth.

True, impactful research is exciting to be a part of. Those who are doing the research could potentially be changing history in their field of study.

Being involved in academic research gives you an inside look into the inner workings of the study area or industry. Often researchers will get access to equipment or experts during an experiment that they may not get otherwise.

Academic research also brings  recognition and accolades  that can be helpful in moving forward in your career.

When an academic research study is made known to the public, that researcher’s name is attached and then known within the community. This can bring a lot of new opportunities for the researcher.

Often these opportunities look like chances to connect and collaborate with others in the same field. For someone who is really invested in a field of study, this can be invaluable to make these connections.

If for nothing else, being involved in academic research can give you answers to questions you have about the field you are studying.

What Tools Are Available for Academic Research?

If you have looked into what is academic research and now feel inclined to get involved in this world, there are many tools available to you moving forward.

The process and procedure for conducting a research study will vary depending on the actual subject being studied, so the tools required will look different for each project.

But every researcher can benefit from using a blockchain platform to keep their peers up to date on research progress. This type of platform allows the researcher to immediately publish findings as they come in, to collaborate with other researchers, and get credit for their work quickly.

A resource like this helps researchers to keep their findings accessible from the beginning, which can be an important part of keeping it going.

Check out the platform for more ideas on how it can benefit your academic research project.

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Understanding Scholarly/Academic Research

• What is Scholarly/Academic Research?
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Scholarly research articles or journals share these characteristics: 

• scholarly works are considered unbiased within their discipline and are backed up with evidence
• are published in academic, scholarly, scientific or empirical journals
• reports on original research  in a specific academic fields
• results are generalizable across populations
• use a research methodology that is replicable
• their authors are most often experts in the field and have their credentials listed

The structure of a scholarly article includes:

• a hypothesis: a proposed question
• a methods section
• conclusions
• suggestions for further research
• a citation reference list

All content in the library is credible, but not all of it is scholarly

These content formats are NOT scholarly

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Academic Research: What it is + Free Tools

Academic research is critical to the success of a university, involving the whole system participating in it, whether it’s students, faculty members, or administrators. Although research is stereotypically associated with being in a laboratory mixing substances, the reality is that academic research involves all disciplines.

As a university student, you probably have many subjects to take, pending projects, and academic research to do. As part of that research, collecting information and data is essential for a final delivery that will give you an A and a 100% reliable result. Researchers use academic papers to earn colleagues’ respect, be a pioneer in their respective fields, and participate in future related research.

But how do you create an excellent quality academic research paper? Why is data collection a crucial point to it? In the following blog post, you’ll find the answers to those questions.

What is academic research?

Academic research is the best tool universities have to create or enhance knowledge and facilitate learning. Additionally, most academic research helps solve different social and economic problems in the community surrounding the university where it originated.

Academic research is a systematic process of studying a research problem or situation, where the intention is to identify facts that help solve the problem or deal with the situation.

Academic research aims to generate new knowledge that improves social development. This research is one of the essential responsibilities of a faculty member working at an educational institution. 

Mainly this focuses on scientific discoveries, conducting studies into various aspects of life, with the eventual aim of developing a more in-depth knowledge of the subject.

It’s all about using new research techniques, creating studies into untouched areas of life, and giving us a better understanding of the world in which we live. There are four types of Academic Research:

• Exploratory research to identify new situations/problems. Because of its nature, this type of research is often qualitative; however, a study with a large sample in an exploratory manner can incorporate qualitative research.
• Descriptive research identifies the characteristics of a particular phenomenon without investigating its causes.
• Explanatory research identifies cause-and-effect relationships in a problem, allowing generalizations that can apply in similar situations.
• Correlational research identifies the relationship between two or more variables and the effect on the system when a change in one of them occurs.

Characteristics of academic research

Academic research is more than just choosing a topic, collecting data, and putting it together on paper. To be considered good research, this must meet specific criteria to ensure the quality of the research. Some of the characteristics of good research are:

• Good research anchors to its topic question; this is the critical factor in the research. When coming up with the research question, try using FINER criteria (Feasible, Interesting, Novelty, Ethical, and Relevant)
• Every research follows a systematic and appropriate methodology.
• Acknowledgment of previous research is critical for the discovery of new knowledge. Using articles, journals, and investigations done in the past will give you a notion of the study’s direction.
• The criteria of good research is that it is representative and generalizable; this refers to the sample’s ability to represent a larger group with minimal variation.
• External validation of the research is a huge differentiator, as it gives recognition to the investigation for it to be used in future studies. 

Objectives of academic research

Academic research seeks to advance new knowledge and has relevance based on solving problems that contribute to the improvement of society.

When you perform academic research, you are essentially trying to solve a mystery—you want to know how something works or why something happened. In other words, you want to answer a question that you, academics, and professionals have about the world. This is one of the most fundamental reasons for performing research.

The process doesn’t stop right after solving the problem. Academic research needs to be presented, the most common way is through an academic paper, but if the paper is outstanding in quality, it can be published in professional journals.

Importance of academic research

As we have said before, academic research facilitates learning, highlights key issues in society, and can promote the growth of students.

• Facilitates the learning process: It is the best activity to develop or improve knowledge and allows to understand specific problems through varied angles that were never identified or talked about much. While conducting the study, you collect the evidence based on facts and rationale. This is how academic research papers open the doors for more discourse and debate.
• Highlights the problems: Generally, academic research highlights some problems that prevail in society, which could be related to cultural norms, health, education, specific practices, etc.
• Leads to the personal growth of students: This process helps in the development of skills. Students learn to identify a problem and arrive at a possible solution or develop a point of view on a specific issue. In addition, they develop skills such as big data analysis, critical thinking, time management, and organization.

Difference between academic and professional research  

There are several types of research, depending on the perspective and objective of each one. If we talk about academic research, it mainly focuses on making new discoveries for the scientific community.

Instead, professional research is more geared towards solving a specific problem for an organization, often a company or its clients. It could be called the next step of the investigation because it is at the same time collecting information and finding a solution, only applied to different approaches and objectives of life, one academic and one more from working life.

Academic research focuses on the research objectives and questions that arise from independent researchers. It uses formal, scientific, and systematic procedures to discover answers and to prove or reject existing theories.

On the other hand, professional research is defined as work carried out to achieve the objectives of an organization and focuses on the research objectives that arise from the requirements of the company. 

You may or may not use formal, scientific, and systematic procedures to discover answers. It is not based on theory and may not require a representative sample.

LEARN MORE: Descriptive Research vs. Correlational Research

Academic research methods

Research methods are the strategies, processes, or techniques used to collect data or analyze evidence to uncover new information or better understand a topic.

Different types of research methods use different tools for data collection. The principal tools for this type of research are interviews, focus groups, observation, and surveys.

• Interviews . A qualitative interview is the best research technique that allows the researcher to gather data from the subject using open-ended questions. The most important aspect of an interview is how it is made. Typically, it would be a one-on-one conversation focusing on the substance of the question.
• Focus group. Focus group is one of the best examples of qualitative data in education or in academic research. It is also a qualitative approach to gathering information. The main difference from an interview is that the group is composed of 6 – 10 people purposely selected to understand the perception of a social group. Rather than trying to understand a more significant population in the form of statistics, the focus group is directed by a moderator to keep the group in topic conversation. Hence, all the participants contribute to the research.
• Observation. Observation is a method of data collection that incorporates the researcher into the natural setting where the participants or the phenomenon is happening. This enables the researcher to see what is happening in real-time, eliminating some bias that interviews or focus groups can have by having the moderator intervene with the subjects.
• Surveys . A survey is a research method used to collect data from a determined population to gain information on a subject of interest. The nature of the survey allows for gathering the information at any given time and typically takes no time, depending on the research. Another benefit of a survey is its quantitative approach, which makes it easier to present it comprehensively.

Tips for doing academic research through surveys

Data collection is the process by which information is collected and measured based on our interests, taking the right path to answer specific research questions , test our hypotheses and predict the results.

The data collected should be similar to that of the study area, while the methods vary depending on the rules and regulations of each industry. Emphasis must be placed on ensuring accuracy and honesty in data collection, this is very important. 

Regardless of what qualitative and quantitative research methods you are conducting in your academic research, data collection must be accurate, which is essential to maintaining the integrity of academic research.

01. Perform effective sampling

Survey sampling size has to do with correctly defining the number of participants. This is one of the main steps in designing and organizing a survey. 

• Main concept : Before starting your academic research survey, you must confirm the study population and give it the correct follow-up. We must be aware that a change throughout the research process can critically affect the reality of the data collected. 
• Diversity: Ensuring the diversity of your sample and getting them to participate can be tedious work. However, it is very important to have a representative sample of the population to obtain richness in the responses. 
• Clarity : There are several limitations to determining the size and structure of the population sample. It is crucial that researchers describe their limitations and maintain the procedures they follow to select the sample transparently so that the results of surveys are seen from the correct perspective.

02. Select Survey Software 

We at QuestionPro are interested in fostering an interest in students in conducting effective academic research. It is because of students that we have different tools that will help them achieve it effectively:

The platform allows you to select different types of questions such as multiple choice , open , matrix type , satisfaction questions with smileys , and many more. 

In addition, our survey software allows students to email their survey, share it on social media, send it via SMS, etc., to facilitate data collection. 

03. Analysis of the responses

Analyzing the responses will help to know in detail the data obtained in the data collection process and confirm or refute the established hypothesis. 

With QuestionPro, it is possible to view survey data responses in real time. This way, you can effectively perform in-depth analysis for your academic research.

We have for you this article on data analysis, techniques, and step-by-step guide .

04. Research report

There are several essential points to consider when reporting the research results. All reports should be educational, relevant to the target audience, and customized to each company’s needs. 

The report of your academic research can be presented through visual presentations, written on an academic paper, or electronic reports. The way you present your survey results will make a big difference. A complete, formal report usually includes the following elements:

• Cover Sheet
• Introduction
• Research Purpose
• Survey Sample
• Methodology
• Conclusion and Recommendations
• Contact Information

QuestionPro platform also provides you with survey dashboards that will be very useful for presenting a report of results.

Online surveys will help you obtain the data you need for decision-making in your academic research. However, it is important that before collecting a series of data, you choose the right topic, the right questions to ask, and the type of survey you will carry out. 

The design of your survey and the target audience, that is, the right people to answer the questions in your questionnaire, will depend on all of the above.

We know that surveys play an important role in educational projects. That is why our platform allows you to conduct quantitative and qualitative research, polls, questionnaires, and online surveys. 

QuestionPro is a global company concerned about education. That’s why we offer academic alliances so that university students and teachers obtain our tool to take online exams, create forms, conduct research projects, and perform data analysis.

If you are interested in using our platform to carry out academic research, we invite you to learn about the benefits of our academic alliances. Take advantage of everything you can achieve by implementing our tool into your education services and start carrying powerful research to your education institution.

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What Is Research, and Why Do People Do It?

• Open Access
• First Online: 03 December 2022

Cite this chapter

You have full access to this open access chapter

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

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

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Abstractspiepr Abs1

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

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

Part I. What Is Research?

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

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

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

Exercise 1.1

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

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

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

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

Exercise 1.2

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

Creating an Image of Scientific Inquiry

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

Descriptor 1. Experience Carefully Planned in Advance

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

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

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

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

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

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

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

Exercise 1.3

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

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

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

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

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

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

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

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

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

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

Doing Scientific Inquiry

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

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

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

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

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

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

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

Exercise 1.4

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

Unpacking the Terms Formulating, Testing, and Revising Hypotheses

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

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

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

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

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

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

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

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

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

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

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

Exercise 1.5

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

Exercise 1.6

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

Learning from Doing Scientific Inquiry

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

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

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

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

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

Part II. Why Do Educators Do Research?

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

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

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

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

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

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

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

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

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

Exercise 1.7

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

Part III. Conducting Research as a Practice of Failing Productively

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

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

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

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

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

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

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

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

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

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

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

Exercise 1.8

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

Exercise 1.9

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

Part IV. Preview of Chap. 2

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

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

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Expert Commentary

Academic research and studies: How they work and why journalists should care

Overview article that provides an introduction to the academic research world and explains how it can be leveraged by journalists.

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To newcomers the world of academic studies can seem like a foreign land. But as with traveling, one can become quite comfortable over time by learning some of the language and basic customs. The following provides an overview of how studies are produced, their relevance and how they might be used.

What is a scholarly study?

When professors and researchers are not teaching, they are often working on academic studies. These are the basic unit of work in higher education, and are typically a paper of anywhere from several pages up to 50 pages or more. These studies help advance knowledge in a particular field, from AIDS research to the understanding of racial issues in America.

Unlike most journalistic stories or blogs, academic studies are the product of months or years of work; they can include analysis of large sets of data or carefully conducted experiments. A scholar might finish just a few important studies in his or her career, contributing incremental knowledge on a question that may have been studied for decades. Studies aspire to say as much as can definitively be known on a particular question, be it complex or seemingly self-evident. Does money in politics cause corruption? You may consider that an obvious question, but for scholars the answer — not just yes or no, but also why and how — has to be proven with precise weighing of evidence. The essence of the scientific method is to come up with a hypothesis, test it, and then make sure it can be repeated — and that no external factors skewed the results.

Many corporations, commercial research firms, advocacy groups and consulting firms also produce studies and in-depth reports. While these can have news value, bear in mind that the findings of such work are not always independently fact-checked prior to publication, whereas studies produced by academic scholars typically are.

In a world overflowing with information of uncertain quality, it’s hard to find knowledge that is as unbiased, thoughtful and reliable as that contained in the best academic studies. This is why journalists should be familiar with how to read them. Studies can provide a baseline of solid fact where reporting can begin. When journalists call experts to hear their views, having familiarity with the basic research allows for more enlightening conversations and makes stories deeper. Studies almost always suggest a wealth of new angles for journalists to pursue. Further, journalists are connection points between information and the public; it is a journalist’s job to make things clear to the public that are often hidden. Sometimes this means misdeeds by public officials or large corporations. But sometimes important insights can be locked away in research studies and journals. Understanding how to read studies can allow you to bring sunlight to issues and knowledge that might otherwise remain obscure.

Where can I find studies?

Nearly every college and university provides access to research databases such as JSTOR . (Be aware, though, that databases such as JSTOR may not provide access to the latest research.) If you want to look for good studies on the Internet, searching at Google Scholar is another typical route; that can also lead you to the latest research, provided you search by date with the advanced scholar search feature. If you find a study you don’t have access to, you can usually ask your college librarian to help you get access through Academic Search Premier or similar resources. Libraries pay a lot of money for this access — use it. Scholars are also increasingly posting early versions of their studies on their websites. These can typically be downloaded for free, but should be checked against the final versions after publication.

There are an increasing number of “open access” databases that freely offer studies to the public. These include Social Science Research Network (SSRN), Harvard’s DASH repository and the Public Library of Science (PLoS). Such sites are part of the debate about whether studies and the knowledge they contain should remain costly and inaccessible or be freely available. This primer provides an overview of online databases ; you should become familiar with many of them. Whatever the outcome of this debate, as a journalist your instinct should be to hunt for the full version of studies and if necessary contact scholars to obtain them. Be aggressive in your pursuit of information. This is the essence of journalism.

How do I read a study?

Studies often have the following structure: abstract; introduction; methods; results; discussion. As tempting as it may be, don’t just read the abstract or summary at the beginning. The more studies you read, the more you’ll get the hang of the language. In fact, the vocabulary and analytical frameworks themselves can become useful for framing stories. Example: Imagine you are reporting on women in the workplace. Is there a “glass ceiling” or a “glass escalator” problem ? In the introduction, you’ll generally find that authors review previous scholarship on a particular question. An example is: How does a family’s income relate to a child’s brain development? The literature review tells the reader what has been learned so far and where questions remain.

In the methods and results sections, the researchers describe what data they used, how they analyzed it, and the results. Don’t be intimidated by mathematical jargon; as complicated as it may sound, there’s often a common-sense way to think about it . For example, “regression” basically means trying to figure out how strong the relationship is between the two things — in our example, income and children’s brain development. Ultimately, the researchers are trying to prove not just that the two things are correlated — that they move in parallel — but that there is causation — one thing causes the other.

In the study above, this might mean that a poor child’s development suffers because of lack of parental income. There may be no correlation between the two things or the relationship may be explained by some other factors, such as geography or lack of medical care. The scholar has to sort this all out. Before studies are published in academic journals, they go through a process called “peer review” — other scholars look at the findings to verify that there aren’t any errors. This system ensures that the study is of the highest possible quality, and is the basis on which all good research rests.

While there are an infinite number of questions in the world that can be studied, most research falls into a number of basic types. Below are a few of the categories and loose genres that you should be familiar with:

Data analysis: Social scientists tend to analyze existing datasets, many of them from governmental sources — census data, health information, transportation data and more. This information can be current as well as historical. For example, if you’re interested in education rates among African-American men and women , it’s useful to compare recent and historical levels.

Longitudinal: Long-term datasets can be useful for what are known as longitudinal studies. For example, Social Security data is gathered over long periods, and so can provide insight into the how U.S. residents’ incomes and locations evolve over time . Select groups can also be tracked for years, and thus allow one to understand the relationship between pre-school education and well-being later in life .

Experimental, observational: Studies can also be based on experiments conducted by the scholars themselves; this is often the case in the “hard sciences” such as medicine, chemistry, biology or botany. But they are also used in fields such as psychology and human cognition: For example, medical researchers might want to understand how having Google at our fingertips might affect our memory . The scholars devise and run an experiment — in this case, a memory test of a group of study subjects — and then analyze the results. When studying medical questions (say, the impact of a new HIV/AIDS treatment ) it’s essential to have a what’s known as a control group — subjects who are given a placebo rather than the substance under study. If the control group is under the control of the researchers, the study is known as experimental; if they’re not, it’s observational. Social scientists are also running more controlled trials in the field: For example, how hearing the Spanish language in America affects perceptions and political attitudes.

Metastudies: These are, in essence, studies of studies. These can be helpful when there is a lot of research on a particular topic — for example, how studying at a diverse college might affect civic engagement later in life . Using meta-analysis, the researchers take the results of the previous studies and combine them, looking for patterns and, in essence, finding “the truth” on a particular question.

Survey-based research reports: While not technically studies, surveys frequently contain valuable information for journalists. They’re often conducted by organizations with a longstanding expertise in the area such as the Pew Research Center, a gold standard for this sort of study. Questions can range from the American public’s changing views of government to the rise of women in higher education .

Reports: Governmental and nonprofit research organizations often produce reports that synthesize a wide variety of data and look at particular questions — for example, the importance of infrastructure investment , the disparities faced by minorities in California , or trends in college spending . Reports can be supported by an organization with a particular mission or point of view, but that doesn’t necessarily invalidate their findings, particularly if they’re published by a credible organization.

Papers: While there’s no precise definition, papers tend to be written by a smaller number of researchers — often just one or two — on broader societal questions. Examples include a rethinking of economic development in poor countries or the case for banning subprime mortgages . Papers are often produced by think tanks such as the Brookings Institution or the RAND Corporation, but can also come out of academia.

How can I use a study in my journalism?

The reading of scholarly studies can be important to get context — to know what smart people have thought about a particular issue. But they can also be cited and summarized in your story or blog. You might strongly consider sending the author of a study an email inquiry or calling him or her to be sure you correctly understand the findings of the study. No matter what, be sure to give the scholar full credit by mentioning the institutions the study came from and the journal in which it was published. And link to the study so your audience can go further into the question. It will improve the depth of your journalism and demonstrate transparency and respect for your audience.

You might first think about how to localize a study. Here are 10 examples of such study-based ideas . Furthermore, the following are examples of high-level stories that use research in a variety of different ways. You’ll see that study findings can be used for context or background; for the purpose of providing alternative perspective on issues; or as hooks for stories themselves.

• “Wasting Time Is New Divide in Digital Era,” The New York Times
• “The Killing Agency: Wildlife Services’ Brutal Methods Leave a Trail of Animal Death,” Sacramento Bee
• “The Unpersuaded: Who Listens to a President?” The New Yorker
• “Whole Food Blues: Why Organic Agriculture May Not Be So Sustainable,” Time

Studies can also be used to provide crucial context and fact-check claims.

Take, for example, the 2012 story about a congressman’s explosive comments casting doubt on the possibility of pregnancy from rape (he was asked about abortions in such situations.) An initial online article such as this one at NPR includes reaction quotes and reporting on the outrage stirred up. But a reporter could also, in theory, quickly search the PubMed database and locate this peer-reviewed study giving the facts behind the issue. “Rape-related pregnancy occurs with significant frequency,” the study notes, putting the figure at 5% and estimating more than 32,000 rape-related pregnancies across the population annually. This Pacific Standard blog post — written shortly after the story broke — performed that research. The data highlighted in the study can then be used to anchor all subsequent reports on the controversy, improving public understanding and not allowing the discussion to revolve around simple “he said, she said” exchanges between partisan sources.

What are the hazards of using studies?

The greatest danger of using studies in journalism is through oversimplifying the findings or misinterpreting them altogether. Researchers often present their findings with many, many reservations — they want to get things right, and so if they have any doubts or see areas for future research, they’ll mention them. You might wish that they’d made a direct, unqualified assertion that fits in a headline, but it’s often not that simple. As a journalist, you may find that there is no way to accurately state the study’s conclusions in a few sentences. In those cases, it is essential that you tell your audience that the study’s findings are limited by certain factors.

By all means, call or email the author and ask questions until you are satisfied that you understand the study’s findings and implications. Researchers are often very helpful to media members, as they have every interest in seeing their work presented accurately to the public.

Keep in mind that scholars consider research to be a process that is constantly unfolding. While some questions can be definitively answered — for example, that certain drugs can slow the spread of HIV — on almost all subjects there is always more research to be done.

As a journalist, it is crucial to avoid what some call the “single-study syndrome” — basing a story entirely on the results of one study, without exploring alternative research angles. While the peer-review process should ensure that only the best and most reliable research is published, some studies can be “outliers” and not necessarily represent general facts about an issue. This is most often a problem with studies based on experiments, because their precise design can greatly influence the results obtained. So if you see an experiment-based study that has produced unusual results, proceed with caution.

Finally, there are always questions about potential bias, particularly as a consequence of who funded the research. This can be difficult for non-experts to assess. Typically, scholars will disclose any conflicts of interest at the bottom of the study. You should be especially wary of research that does not appear in a peer-reviewed journal, or research that is funded by commercial firms that might have a vested interest in the results.

What should a journalist do after reading the study?

You should make every effort to get in touch with the author. But that may not be the end of your follow-up. One thing you can do to assess the validity of the findings independently is to go to the study’s citations — all of the footnotes contained in the bibliography at the bottom — and contact the authors of the other studies that are cited. You might email them and say, “You are cited in this study. What do you think of the findings?” If you are going to be reporting in this area over time, you might also begin signing up for email alerts for the journals that are related to this field. That way you can stay up to date with what the academic community is saying about aspects of your beat.

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Search catalog, critical thinking and academic research: assumptions.

• Information
• Point of View
• Assumptions
• Implications

Question Assumptions

An assumption is an unexamined belief: what we think without realizing we think it. Our inferences (also called conclusions) are often based on assumptions that we haven't thought about critically. A critical thinker, however, is attentive to these assumptions because they are sometimes incorrect or misguided. Just because we assume something is true doesn't mean it is.

Think carefully about your assumptions when finding and analyzing information but also think carefully about the assumptions of others. Whether you're looking at a website or a scholarly article, you should always consider the author's assumptions. Are the author's conclusions based on assumptions that she or he hasn't thought about logically?

Critical Questions

• What am I taking for granted?
• Am I assuming something I shouldn't?
• How can I determine whether this assumption is accurate?
• What is this author assuming?
• How can I determine if this author's assumptions are accurate?

Consider the following situations, then respond to these questions:

• Do you agree or disagree with the inference/conclusion? Why or why not?
• What assumption(s) may have led to the inference/conclusion?
• What are some alternative ways of thinking about this situation?

Situation #1

Bill needs six scholarly articles for his paper on the psychological effects of domestic violence. He searches Google for "psychological effects of domestic violence," looks through the first few hits, and finds six sources, including some articles on the websites of legitimate organizations. A few of these articles include bibliographies.

• Bill's Inference/Conclusion: I'm going to stop researching because I have my six sources.

Situation #2

Christie is researching representations of gender in popular music. She decides to search Google and, within a few minutes, locates more sources that she could possibly incorporate into her final paper.

• Christie's Inference/Conclusion: I can just use Google for my research.

Situation #3

Jennifer has decided to write her literary analysis paper on drug use in David Foster Wallace's novel, Infinite Jest (1996). She tries a few Google searches for Infinite Jest, drugs, and drug use, but she has trouble finding scholarly sources. She gives up on Google and moves on to EBSCO Academic Search Premier, one of the databases she heard about in a library instruction class. She runs a search for Infinite Jest and drug use, but she still can't find much.

• Jennifer's Inference/Conclusion: I need to change my topic.
• << Previous: Inferences
• Next: Implications >>
• Last Updated: Jul 10, 2023 11:50 AM
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Published by Owen Ingram at May 5th, 2023 , Revised On December 8, 2023

What is Academic Research? – Definition, Types & Steps

The phrases “according to a new research study” or “research demonstrates” are commonplace, but have you ever pondered their significance? 

Table of Contents

The importance of academic research cannot be overlooked since it is mentioned frequently in all aspects of life. What is academic research, and why is it essential? 

Research exists in various shapes and locations and impacts most aspects of our lives, whether we recognise it or not, from the technology we employ to the medicine we ingest. Thus, research is indispensable for advancement. 

Let’s now explore the definition of research, its objectives and characteristics, how it is conducted, and why it should matter to you.

Definition and Meaning of Academic Research 

“Academic research refers to a systematic and rigorous inquiry conducted by scholars, researchers, or experts in a particular field of study to expand the existing knowledge, validate or challenge theories, and develop new ones.” 

It involves collecting and analysing data and information using established methods, tools, and techniques to address research questions or hypotheses. 

The main goal of academic research is to advance knowledge and understanding in a specific discipline, such as science, social sciences, humanities, or arts. 

Academic research is usually conducted in universities, research institutions, or other academic settings and is often published in scholarly journals, books, or conferences.

Objectives of Academic Research

Academic research aims to generate new knowledge and has practical significance by addressing problems that can contribute to the betterment of society.

Academic research involves unravelling a mystery to understand how or why something functions or occurs while ensuring it is 100% free of research bias . In essence, it involves finding answers to questions that academics and professionals have about the world, and this constitutes a fundamental reason for engaging in research.

The research process does not end after the problem has been resolved. Academic research must be communicated, typically through an academic paper, and if the paper meets high-quality standards, it may be published in professional journals.

Characteristics of Academic Research

Academic research involves more than simply selecting a topic, gathering data, and presenting it in written form. For research to be deemed high-quality, it must meet specific standards to ensure its excellence. Some key features of good research include the following:

• The research must be closely tied to its research question, which is the most crucial element. When formulating a research question, it is advisable to use the FINER criteria (Feasible, Interesting, Novelty, Ethical, and Relevant).
• All research should follow a systematic and appropriate methodology.
• Acknowledgment of previous research is critical for the development of new knowledge. You can understand the study’s direction by referring to articles, journals, and past investigations.
• The criteria of good research include that it is representative and generalisable. This pertains to the sample’s capacity to represent a larger group with minimal variation.
• External research validation is a significant distinguishing factor, as it provides recognition to the investigation for future studies.

Also read: What is grey literature

What is the Importance of Academic Research?

Academic research is crucial in advancing knowledge, understanding, and innovation in various fields of study. Here are some of the key reasons why academic research is essential:

• Expanding Knowledge: Academic research helps to expand the existing body of knowledge in various fields of study, including science, social sciences, humanities, and the arts.
• Validating or Challenging Theories: Academic research enables scholars to validate or challenge existing theories, concepts, and practices and to develop new ones based on empirical evidence.
• Problem-Solving: Academic research addresses real-world problems and challenges, contributing to developing practical solutions that improve people’s lives and society.
• Innovation: Academic research is a vital source of innovation, leading to new products, services, and technologies that can drive economic growth and social progress.
• Education: Academic research supports teaching and learning, as it provides up-to-date information, new ideas, and fresh perspectives that enrich the educational experience.
• Career Advancement: Academic research can lead to career advancement and recognition for scholars, as publications in academic journals and other forms of dissemination are often used to measure professional achievement.

Academic research is crucial to advancing knowledge, understanding, and innovation, and it is essential for the progress and well-being of society.

Types and Methods of Academic Research 

Academic research can be broadly classified into two main types:

• Quantitative research focuses on using numerical data and statistical analysis to understand and explain phenomena. It involves collecting data through structured surveys, experiments, or observations and analysing it using statistical tools and techniques.
• Qualitative research explores and understands social phenomena by collecting and analysing non-numerical data, such as interviews, focus groups, and case studies. It aims to uncover individuals’ and groups’ underlying meanings and subjective experiences.

Within these two main types of research, there are several subtypes of academic research, such as:

• Experimental research: In this type of research, researchers manipulate variables and measure the effects to establish cause-and-effect relationships.
• Descriptive research: This type of research aims to describe the characteristics of a phenomenon or population.
• Correlational research: In this type of research, researchers examine the relationship between two or more variables.
• Case study research: This type of research focuses on the in-depth study of a single case or a small number of cases.
• Action research: This type of research involves collaboration between researchers and practitioners to identify and address problems in real-world settings.

The choice of research type and subtype depends on the research question, the nature of the phenomenon under study, and the research methodology .

How to Use Academic Research Used in Practice?

We have already discussed how academic research can bring about progress and change in various fields, such as healthcare, education, and technology. 

Academic research enables healthcare providers to use evidence-based techniques to treat patients, while in education, it can be used to teach concepts and principles. 

Furthermore, research in a particular field of interest is essential in demonstrating its continual progression. In technology, research studies are used to improve equipment and systems. 

By asking the right questions and studying them thoroughly, academic research can significantly impact and bring life-changing results for those involved in the industry.

How to Structure Academic Research

Academic research papers usually follow a specific sequence, which includes Abstract, Introduction, Methods, Results and Discussion, References, Tables & Figures, and Appendices.

The Abstract section of a research paper is essential, as it briefly summarises the entire study in one paragraph. It is usually limited to 250 words and helps readers decide whether to read further.

Researchers use various referencing styles, and one commonly used style in the UK is Harvard referencing. This style includes in-text citations and reference lists, which allow readers to locate the original text easily. Most university websites have a guide to Harvard referencing that you can refer to for assistance.

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Steps of Conducting Academic Research 

The steps of conducting academic research can vary depending on the field and nature of the study but generally include the following:

Identify a research question

Determine the purpose and focus of the research, and develop a clear research question that can be investigated.

Review existing literature

Conduct a thorough review of existing research and literature related to the topic to identify gaps in knowledge and potential research areas.

Develop a research plan

Decide on the research design, methodology, data collection methods, and analysis techniques that will be used to investigate the research question.

Collect data

Carry out data collection activities in accordance with the research plan, which may involve conducting surveys, interviews, experiments, or other methods.

Analyse data

Analyse and interpret the data collected to draw conclusions and make findings related to the research question.

Write up findings

Communicate the research findings in a written report or paper, including an introduction, methods, results, discussion sections, references, and supplementary materials.

Peer review and publication

Submit the research for peer review and publication in a relevant academic journal or other outlet, where it can be reviewed and validated by other experts in the field.

Present findings

Share the research findings with others through presentations at conferences, seminars, or other professional settings, to disseminate the knowledge and contribute to the ongoing dialogue in the field.

Difference Between Academic Research & Professional Research 

Academic research and professional research share many similarities, but there are some key differences between them.

What is a Research Paradigm?

A research paradigm is a set of assumptions, beliefs, and practices guiding researchers’ approach. It includes the researcher’s worldview, theoretical framework, and research methodology. 

The paradigm shapes the researcher’s views of the world and influences how they define and approach research questions, collect and analyse data, and interpret their findings. 

Examples of research paradigms include positivism, interpretivism, critical theory, constructivism, and pragmatism. Each of these paradigms has different assumptions about the nature of reality, the role of the researcher, and the methods used to conduct research.

Academic Research Ideas

After identifying a problem and finding a gap, academic research explores a unique idea. A researcher must select an appropriate title or topic for their research before starting. 

The depth and complexity of the chosen topic depend on a range of factors, including the researcher’s academic level and subject. 

Our free research topics database lets you find interesting and unique ideas for all study areas. 

How to Access Academic Research?

Accessing academic research typically involves the following steps:

Check with your local library 

Many libraries have subscriptions to academic databases and journals, and they may provide access to these resources to library cardholders.

Check with academic institutions 

If you are a student or faculty member at a university, you likely have access to the institution’s library and its online resources.

Use academic search engines

Many academic search engines, such as Google Scholar, allow you to search for academic articles and papers.

Contact the author

If you encounter an article or paper you cannot access, contact the author directly to request a copy.

Look for open-access resources

Many academic journals and databases now offer open-access options, meaning the content is freely available to anyone.

Attend conferences or seminars

Attending academic conferences or seminars can give you access to the latest research in your field and the opportunity to network with other researchers.

It is important to note that accessing academic research can sometimes be costly, and access may be restricted to those with paid subscriptions or memberships. However, many resources are available for free or at a lower cost, and it is always worth checking with your local library or academic institution to see what options are available to you.

Frequently Asked Questions

Who is an academic researcher.

An academic researcher is a professional who conducts systematic and rigorous investigations to discover new knowledge or insights in their field of study.

They work in academic institutions such as universities, research institutes, and think tanks and publish their findings in scholarly publications such as academic journals, books, and conference proceedings.

What does peer-reviewed mean in academic research? Peer-reviewed means that a scholarly work, such as an academic article, has been evaluated and scrutinised by other experts in the same field before it is published.

This process ensures the quality, validity, and reliability of the research. Peer review is a crucial aspect of academic publishing and promotes high standards of scholarship.

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A variety of literature reviews are carried out in academic research and evidence-based practice to compile the body of information […]

A web-based software platform called Covidence was created especially for researchers and medical professionals who do systematic reviews and other types of evidence synthesis.

A research topic is a specific area of inquiry or investigation chosen for study by a researcher or research team. It is the subject of the research study and defines the research questions or objectives that the researcher seeks to address as part of the project.

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What Research Has Been Conducted on Procrastination? Evidence From a Systematical Bibliometric Analysis

Associated data.

The original contributions presented in the study are included in the article/ Supplementary Material , further inquiries can be directed to the corresponding author/s.

Procrastination is generally perceived as a common behavioral tendency, and there are a growing number of literatures to discuss this complex phenomenon. To elucidate the overall perspective and keep abreast of emerging trends in procrastination research, this article presents a bibliometric analysis that investigates the panorama of overviews and intellectual structures of related research on procrastination. Using the Web of Science Database, we collected 1,635 articles published between 1990 and 2020 with a topic search on “procrastination” and created diverse research maps using CiteSpace and VOS viewer. Bibliometric analysis in our research consists of category distribution, keyword co-occurrence networks, main cluster analysis, betweenness centrality analysis, burst detection analysis, and structure variation analysis. We find that most research has focused on students' samples and has discussed the definition, classification, antecedents, consequences and interventions to procrastination, whereas procrastination in diverse contexts and groups remains to be investigated. Regarding the antecedents and consequences, research has mainly been about the relationship between procrastination and personality differences, such as the five-factor model, temperament, character, emotional intelligence, and impulsivity, but functions of external factors such as task characteristics and environmental conditions to procrastination have drawn scant attention. To identify the nature and characteristics of this behavior, randomized controlled trials are usually adopted in designing empirical research. However, the predominant use of self-reported data collection and for a certain point in time rather than longitudinal designs has limited the validation of some conclusions. Notably, there have been novel findings through burst detection analysis and structure variation analysis. Certain research themes have gained extraordinary attention in a short time period, have evolved progressively during the time span from 1990 to 2020, and involve the antecedents of procrastination in a temporal context, theoretical perspectives, research methods, and typical images of procrastinators. And emerging research themes that have been investigated include bedtime procrastination, failure of social media self-control, and clinical interventions. To our knowledge, this is almost the first time to conduct systematically bibliometric analysis on the topic of procrastination and findings can provide an in-depth view of the patterns and trends in procrastination research.

Introduction

Procrastination is commonly conceptualized as an irrational tendency to delay required tasks or assignments despite the negative effects of this postponement on the individuals and organizations (Lay, 1986 ; Steel, 2007 ; Klingsieck, 2013 ). Poets have even written figuratively about procrastination, with such phrases as “ Procrastination is the Thief of Time ,” and “ Procrastination is the Art of Keeping Up with Yesterday ” (Ferrari et al., 1995 ). Literal meanings are retained today in terms of time management. The conceptualizations of procrastination imply inaction, or postponing, delaying, or putting off a decision, in keeping with the Latin origins of the term “pro-,” meaning “forward, forth, or in favor of,” and “-crastinus,” meaning “tomorrow” (Klein, 1971 ). Time delay is just the behavioral reflection, while personality traits, cognitive and motivational process, as well as contextual conditions are in-depth inducements to procrastination. Procrastination can be viewed as purposive and irrational delay so as to miss the deadlines (Akerlof, 1991 ; Schraw et al., 2007 ).

Procrastination is believed to be a self-regulation failure that is associated with a variety of personal and situational determinants (Hen and Goroshit, 2018 ). Specifically, research suggests that task characteristics (e.g., unclear instructions, the timing of rewards and punishment, as well as task aversiveness), personality facets (e.g., the five-factor model, motivation, and cognition), and environmental factors (e.g., temptation, incentives, and accountability) are the main determinants of procrastination (Harris and Sutton, 1983 ; Johnson and Bloom, 1995 ; Green et al., 2000 ; Wypych et al., 2018 ). Procrastination can be an impediment to success, and may influence the individual's mood, and increase the person's anxiety, depression, and low self-esteem (Ferrari, 1991 ; Duru and Balkis, 2017 ). Furthermore, a person with procrastination is prone to poor performance, with lower exam scores, slower job promotions, and poorer health (Sirois, 2004 ; Legood et al., 2018 ; Bolden and Fillauer, 2020 ). Importantly, if policymakers postpone conducting their decision-making until after the proper timing, that procrastination can cause a significant and negative impact on the whole society, such as the cases with the COVID-19 pandemic management in some countries (Miraj, 2020 ).

In practice, procrastination is stable and complex across situations, ranging from students' academic procrastination, to staffs' work procrastination, to individuals' bedtime procrastination, to administrative behavior procrastination when government organizations face multiple tasks in national governance, and even to delayed leadership decision-making in crisis situations in global governance (Nevill, 2009 ; Hubner, 2012 ; Broadbent and Poon, 2015 ; Legood et al., 2018 ). As for science research, procrastination has attracted more and more attention and been studied extensively. Personally, possible explanations for emerging research focuses mainly consist of two aspects. On one hand, procrastination with high prevalence and obvious consequences highlights the importance to explore the complex phenomenon deeply, especially the meteoric rise in availability of information and communications technologies (ICTs) amplifies chronic procrastination, such as problematic social media use, smartphone addictions as well as mobile checking habit intrusion (Ferrari et al., 2007 ; Przepiorka et al., 2021 ; Aalbers et al., 2022 ). On the other hand, more and more basic and milestone research emerges in large numbers, which set the foundation for latecomer' further exploration toward procrastination. In particular, it can't be ignored the efforts of those productive authors in different periods to drive the knowledge development of procrastination.

Procrastination research has experienced tremendous expansion and diversification, but systematic and overview discussion is lacking. Several meta-analyses about procrastination have emerged, but they emphasize more on specific topics (Steel, 2007 ; Sirois et al., 2017 ; Malouff and Schutte, 2019 ). Furthermore, the number of newly published articles is increasing, so it becomes difficult to fully track the relevant domain literature. In order to grasp knowledge development about the fast-moving and complex research field, bibliometric analysis is necessary to construct diagram-based science mapping, so as to provide a comprehensive and intuitive reference for subsequent researchers. Thus, this article emphasizes on the following major research question: what is the intellectual base and structure of procrastination research? How does the emerging direction of procrastination develop? In our research, bibliometric analysis included the annual distribution of literature, distribution of categories, keyword co-occurrence networks, main research clusters, high citation betweenness centrality, and the strongest citation bursts, as well as the recent publications with transformative potential, in order to look back on the early development of procrastination research and look forward to the future transformation of that research. For both scholars and members of the public, this study can comprehensively enhance their understanding of procrastination and can provide overall perspectives for future research.

Data and Methodology

Bibliometric analysis is a quantitative method to investigate intellectual structures of topical field. On the basis of co-citation assumption that if two articles are usually cited together, then there are high associations between those articles, bibliometric analysis can reflect the scientific communicational structures holistically (Garfield, 1979 ; Chen et al., 2012 ). Bibliometric techniques, such as CiteSpace, VOSviewer, HistCite, can generate the science maps based on plenty of literature concerning certain domain. Through the process of charting, mining, analyzing, sorting, and displaying knowledge, science mapping can extract pivotal information from huge complex literature, present knowledge base and intellectual structure of a given field visually, then researchers even general individual can quickly grasp one subject's core structure, development process, frontier field and the whole knowledge framework (Chen, 2017 ; Widziewicz-Rzonca and Tytla, 2020 ). Bibliometric analysis is commonly regarded as a complementary method to traditional structured literature reviews such as narrative analysis and meta-analysis (Fang et al., 2018 ; Jiang et al., 2019 ). Traditional literature analysis tends to labor intensive with subjective preferences, and faces difficulties in analyzing larger body of literature, whereas bibliometric analysis provides a more objective approach for investigating considerable literature's intellectual structure through statistical analysis and interactive visual exploration.

In order to master the characteristics of procrastination research, the study adopted the bibliometric software of CiteSpace and VOSviewer to analyze the literature on procrastination during the time period 1990–2020. The software tool VOSviewer is designed for creating maps of authors, journals, and keyword co-occurrences based on network data (van Eck and Waltman, 2010 ), whereas CiteSpace is applied to conduct co-citation analysis, including centrality betweenness analysis, burst detection, and the emerging trends of research (Chen, 2006 , 2017 ). In our study, we adopted the CiteSpace (5.7.R1) and VOSviewer (1.6.15) software together. Specifically, co-citation analysis mainly depends on CiteSpace software, and co-occurrence analysis is conducted through VOS viewer (Markscheffel and Schroeter, 2021 ).

Though there is one similar bibliometrics analysis toward this topic (Tao et al., 2021 ), related research just focuses on academic procrastination, and mainly conducts co-occurrence analysis using VOSviewer, so as to there is a lack of analysis to core co-citation structures including high betweenness centrality articles, citation burst research and structure variation analysis. To offer insight into the intellectual structure of procrastination research, we further employ CiteSpace — a java application including bibliometric analysis, data mining algorithms and visualization methods developed by Chen — to visualize and elucidate vital trends and pivotal points about knowledge development.

To conduct our bibliometric analysis of procrastination research, we collected bibliographic records from the Web of Science Core Collection as of December 31, 2020. Web of Science is currently the most relevant scientific platform regarding systematic review needs, allowing for a “Topic” query, including searching a topic in the documents' “title”, “abstract”, “author keywords” and “keywords plus” of the documents being reviewed (Yi et al., 2020 ). A topic search strategy is broad enough to be used in science mapping (Olmeda-Gomez et al., 2019 ). Given the aim of the study, records were downloaded if they had the term “procrastination” in the “Topic” field. After restricting the type of publication to “Article” for the years 1900–2020, we had searched 2105 papers about procrastination research.

Figure 1 shows the yearly distribution of 2105 literature during 1900–2020, and it can be classified into three phases. In phase I (1900–1989), the annual number of publications never exceeded 10. In phase II (1990–2010), the annual quantity gradually increased from 11 papers in 1991 to 48 in 2010. The annual number of publications had begun to grow in this period, but remained below 50 papers yearly. In phase III (2011–2020), however, the procrastination research experienced a dramatic growth, with 255 literature in the year 2020. Although procrastination research appeared as early as 1900s, it had a stable total volume until the 1990s, when it developed sustained growth, and that growth became extraordinary during the 2010s. Therefore, this research emphasized centered on 1,635 literature that were published during the time span 1990–2020.

Distribution of publications on the topic of procrastination, 1900-2020.

Panoramic Overview of Procrastination Research

Category distribution.

Procrastination research has been attracting increasing attention from scholars, and it has been successfully integrated into various scientific fields. With the help of CiteSpace software, we present in Figure 2 the timelines of the various disciplines that are involved in procrastination research, and the cumulative numbers of literature that have been published.

Distribution of categories involved in procrastination research.

As Figure 2 shows, the size of node on the horizontal lines represents the quantity of literature published. Node colors denote the range of years of occurrence, and purple outlining is an indication of those articles with prominent betweenness centrality, and red nodes present references with high citation burst (Chen, 2017 ). Besides, the uppermost line shows the timeline of different disciplines, and the numbers on the longitudinal lines describe the distinct categories of procrastination research, of which are arranged vertically in the descending order of cluster's size. Clusters are numbered from 0, i.e Cluster #0 is the largest cluster and Cluster #1 is the second largest one. Specifically, the earlier research about procrastination occurs in the Psychology and Social Science disciplines. Subsequently, research has expanded into Computer Science and Information Systems, Economics, the Neurosciences, the Environmental Sciences, Ethics, Surgery, and general Medicine. As the connections arc in the Figure 2 presents, those categories #0 Psychology and Social Sciences, #1 Computer Science, and #2 Economics interact actively, but the interdisciplinary research about the remaining categories, such as #9 Medicine, #5 Ethics, and #4 Environmental Science, is not active.

Our analysis of the category distribution reveals two aspects of the characteristics about procrastination research. One, related research mostly has its roots in the Psychology and Social Science disciplines, and interdisciplinary research needs to be improved. And Two, the foundational literature dates back to the 1990s, and transformational exploration is currently needed in order to further develop the research on procrastination.

Keyword Co-occurrence Network: Core Contents

Analysis of co-occurring keywords is often used to obtain the content of research fields. Using the VOS viewer, we obtained a total of 5,203 keywords and created a co-occurrence network. As mentioned above, the size of a node represents the number of times that a specific keyword occurs. Several keywords turn up frequently, such as Procrastination, Performance, Academic Procrastination, Motivation, Personality, Self-regulation, Self-control, and Behavior. To create a readable map, the “minimum number of occurrences” is set to 20, and the final network includes 90 high-frequency keywords and five clusters with 2,650 links, as is shown in Figure 3 .

Keywords co-occurrence network for procrastination research.

Among the five clusters depicted in Figure 3 , the blue cluster is mainly related to the definition of procrastination, with keywords such as Procrastination, Delay, Deadlines, Choice, Self-Control, and Implementation Intentions. Procrastination is a complex phenomenon, and previous research has elaborated on the core traits about procrastination from various dimensions. Mainstream views hold that procrastination can be defined as the intentional delay of work because of a self-regulation failure, time-management inefficiency, short-term benefits, a gap between intention and action (Tice and Baumeister, 1997 ; Steel, 2007 ; Pychyl and Flett, 2012 ; Klingsieck, 2013 ), or missing a deadline and causing negative outcomes (Johnson and Bloom, 1995 ; Howell and Watson, 2007 ; Sirois, 2021 ).

The cluster in red in Figure 3 involves procrastination performance in relation to different life-domains, including Academic Achievement, Life Satisfaction, Online Learning, and Technology Uses. Previous research has elaborated on procrastination as being negatively correlated with performance. However, intrinsic motivation, self-regulated learning, and time-management have been shown to relieve the procrastination behavior (Wolters, 2003 ; Howell and Watson, 2007 ; Baker et al., 2019 ).

The green cluster highlights traits associated with procrastination. Related research in that cluster mostly discusses the correlation between the five-factor model (neuroticism, extraversion, openness to experience, agreeableness, conscientiousness) and procrastination (Schouwenburg and Lay, 1995 ). In addition, personality traits including indecisiveness, indecision, and perfectionism have been elaborated upon (Klingsieck, 2013 ; Tibbett and Ferrari, 2019 ). Furthermore, to measure the trait of procrastination itself, various scales have been developed, such as the General Procrastination Scale, Decisional Procrastination Questionnaire, Procrastination at Work Scale, Irrational Procrastination Scale, Adult Inventory of Procrastination Scale and so on (Lay, 1986 ; Ferrari et al., 1995 ; Steel, 2010 ; Metin et al., 2016 ). The validity and reliability of those scales have also been investigated fully.

The cluster presented in yellow depicts studies that focuses on academic procrastination, and especially those that discuss the antecedents of the prevalent behavior, such as Anxiety, Perfectionism, Self-efficacy, Depression, and Stress (Schraw et al., 2007 ; Goroshit, 2018 ). Owing to their accessibility for use as a research sample, a large body of procrastination research has chosen students in an academic setting as the research objects. Researchers have found that academic procrastination is an impediment to academic performance, especially for very young students. Notably, too, female students may perform lower levels of academic procrastination than males do.

The last cluster, presented in purple, relates to chronic procrastination's involvement in health and addiction, for either adults or adolescents. Discussion about chronic procrastination is growing, and interventions can be effective in relieving this behavior.

From the analysis of co-occurrence keywords, we can infer that procrastination research has been developing steadily. The fundamental discussion has become more adequate and persuasive in regard to the definition, the individual differences, and the antecedents of procrastination, and a discussion of how to relieve the behavior has begun.

Main Research Cluster: Core Theme and Hot Topics

Comparing to keyword co-occurrence network analyses, cluster analysis can help us grasp the primary themes in procrastination research. Clusters are based on the assumption that if two references are often cited together, they may be associated in some way (Chen et al., 2012 ; Pan et al., 2019 ). Eventually, related references shape diverse co-citation networks. Clustering is a procedure to classify co-cited references into groups, with references in the same clusters being tightly connected with each other but loosely associated with other clusters (Chen et al., 2010 ).

Based on the references of the top 50 articles with the most citations every year (if the number was less than 50 in a certain year, then all of the articles were combined), the final network contained 982 references and we were able to develop the final cluster landscape. Two procedures are used to label each cluster: (1) retrieval of keywords from the citing articles using the log likelihood ratio, and (2) retrieval of terms contained in the cited articles with latent semantic indexing (Olmeda-Gomez et al., 2019 ). In our research, we adopted the log-likelihood ratio (LLR) method to label the clusters automatically. Given the related structural and time-based values, articles in the co-citation network are assigned to each cluster. Eventually, the network was divided into 23 co-citation clusters.

In addition, two critical parameters, silhouette and modularity, are used to measure whether clusters are available and whether they are well-constructed. Silhouette indicates the homogeneity of clusters, whereas modularity measures whether the network is reasonably divided into independent clusters. The silhouette value ranges from −1 to 1, and the modularity score ranges from 0 to 1. When values of the two metrics are high, the co-citation network is well-constructed (Chen et al., 2010 ; Widziewicz-Rzonca and Tytla, 2020 ). As is shown in Figure 4 , the mean silhouette score of 0.9223 suggested that the homogeneity of these clusters was acceptable, and the modularity score of 0.7822 indicated that the network was reasonably divided.

Landscape view of co-citation network of procrastination research.

In our research, we summed the largest nine clusters. As is shown in Table 1 , the silhouette value for all clusters was higher than 0.8, suggesting the references in each cluster were highly homogeneous. The labels of these clusters were controlled trial, avoidant procrastination, conscientiousness procrastination, smoking cessation, explaining lack, academic achievement, procrastinatory media use, career indecision, and goal orientation.

Summary of the nine largest clusters in procrastination research.

In Table 1 , the year in the far-right column indicated the average year when the reference was cited. Ranking the clusters by the mean cited year, we can follow the development of research themes. During the 1990s, research themes focused on discussions about the antecedents of procrastination. For example, Lay ( 1988 ) discussed that the self-regulation model cannot explain procrastination fully, and errors in estimations of the time taken to complete a task may be attributed to procrastination. Procrastinators were thought to tend to lack conscientiousness and goal orientation as well as to be motivated by neurotic avoidance (Ferrari et al., 1995 ; Elliot and Harackiewicz, 1996 ). Besides, procrastination was prevalent throughout our lifespan, and empirical research on procrastination conducted through controlled trials had considered various settings or scenarios, such as academic procrastination, smoking cessation, career indecision, and in the most recent years, media use (Klassen et al., 2008 ; Germeijs and Verschueren, 2011 ; Du et al., 2019 ). Because procrastination was negatively associated with performance, life satisfaction, health and well-being, research on procrastination avoidance and intervention, including strengths-based training and cognitive behavioral therapy had attracted the most attention from scholars (van Eerde, 2003 ; Balkis and Duru, 2016 ; Visser et al., 2017 ).

Intellectual Structure of Procrastination Research

Co-citation analysis and clustering analysis form the cornerstone for bibliometric investigation (Olmeda-Gomez et al., 2019 ), especially for the microscopic intellectual structures of the science, such as betweenness centrality, burst detection, and structural variation analysis (Pan et al., 2019 ). Based on the cited references network during the period of 1990–2020, we generated a landscape visualization of intellectual structures about procrastination research. The section consists of three parts: (1) Betweenness Centrality Analysis captures the bridge nodes, which represents the landmark and pivotal literature of a scientific field (Freeman, 1978 ). (2) Burst Detection Analysis is used to detect the emergent and sharp increases of interest in a research field (Kleinberg, 2003 ), which is a useful method for easily tracing the development of research focus and research fronts. (3) Structural Variation Analysis (SVA) is an optional measurement to identify whether newly published articles have the potential to transform the citation network in the latest years. Newly published articles initially have fewer citations and may be overlooked. To overcome the limitation, structural variation analysis often employs zero-inflated negative binomial (ZINB) and negative binomial (NB) models to detect these transformative and potential literature (Chen, 2013 ).

Betweenness Centrality Analysis

Literature with high betweenness centrality tends to represent groundbreaking and landmark research. On the basis of our co-citation network on procrastination research for the period 1990–2020, we chose the top 10 articles to explore (see Supplementary Material for details). Related research mainly focuses on three areas.

Definition and Classification of Procrastination

Procrastination is described as the postponement of completion of a task or the failure to meet deadlines, even though the individual would meet adverse outcomes and feel uncomfortable as a result (Johnson and Bloom, 1995 ). Extracting from authoritative procrastination scales, Diaz-Morales et al. ( 2006 ) proposed a four-factor model of procrastination: dilatory behaviors, indecision, lack of punctuality, and lack of planning. Procrastination is commonly considered to be a pattern of self-regulation failure or self-defeating behavior (Tice and Baumeister, 1997 ; Sirois and Pychyl, 2013 ).

The most popular classification is the trinity of procrastination: decisional, arousal, and avoidant procrastination (Ferrari, 1992 ). Using the General Behavioral Procrastination Scale and Adult Inventory of Procrastination Scale, Ferrari et al. ( 2007 ) measured the difference between arousal and avoidant procrastination, and they elaborated that those two patterns of procrastination showed similarity and commonality across cultural values and norms. However, by conducting a meta-analytic review and factor analyses, Steel ( 2010 ) found that evidence for supporting the tripartite model of procrastination may not be sufficient. Research has reached a consensus about the basic definition of procrastination, but how to classify procrastination needs further discussion.

Procrastination Behavior in a Temporal Context

Procrastination is related to time management in its influence on one's behavior. Non-procrastinators or active procrastinators have better time control and purposive use of time (Corkin et al., 2011 ). However, time management is an obstacle to procrastinators. From the temporal disjunction between present and future selves, Sirois and Pychyl ( 2013 ) pointed out that procrastinators tended to give priority to short-term mood repair in the present, even though their future self would pay for the inaction. Similarly, in a longitudinal study Tice and Baumeister ( 1997 ) pointed out that maladjustment about benefits-costs in participants' timeframe shaped their procrastination. When a deadline is far off, procrastination can bring short-term benefits, such as less stress suffering and better health, whereas early benefits are often outweighed by possible long-term costs, including poor performance, low self-esteem, and anxiety. These viewpoints confirm that procrastination is a form of self-regulation failure, and that it involves the regulation of mood and emotion, as well as benefit-cost tradeoffs.

Causes of and Interventions for Procrastination

Procrastination shows significant stability among persons across time and situations. Predictors of procrastination include personality traits, task characteristics, external environments, and demographics (Steel, 2007 ). However, typically, empirical research has mostly focused on the relationship between the five-factor model and procrastination behavior. Johnson and Bloom ( 1995 ) systematically discussed five factors of personality to variance in academic procrastination. Research also had found that facets of conscientiousness and neuroticism were factors that explained most procrastination. In alignment with these findings above, Schouwenburg and Lay ( 1995 ) elaborated that procrastination was largely related to a lack of conscientiousness, which was associated with six facets: competence, order, dutifulness, achievement-striving, self-discipline, and deliberation. Meanwhile, impulsiveness (a facet of neuroticism) has some association with procrastination, owing to genetic influences (Gustavson et al., 2014 ). These discussions have established a basis for research about personality traits and procrastination (Flett et al., 2012 ; Kim et al., 2017 ).

To relieve procrastination, time management (TM) strategies and clinical methods are applied in practice. Glick and Orsillo ( 2015 ) compared the effectiveness of those interventions and found that acceptance-based behavior therapies (ABBTs) were more effective for chronic procrastinators. Regarding academic procrastination, Balkis ( 2013 ) discussed the role of rational beliefs in mediating procrastination, life satisfaction, and performance. However, there is no “Gold Standard” intervention for procrastination. How to manage this complex behavior needs further investigation.

Burst Detection Analysis

A citation burst indicates that one reference has gained extraordinary attention from the scientific community in a short period of time, and thus it can help us to detect and identify emergent research in a specialty (Kleinberg, 2003 ). A citation burst contains two dimensions: the burst strength and the burst status duration. Articles with high strength values can be considered to be especially relevant to the research theme (Widziewicz-Rzonca and Tytla, 2020 ). Burst status duration is labeled by the red segment lines in Figure 5 , which presents active citations' beginning year and ending year during the period 1990-2020. As can be seen in Figure 5 , we ranked the top 20 references (see Supplementary Material for details) with the strongest citation bursts, from the oldest to the most recent.

Top 20 references with the strongest citation bursts.

To systematically investigate the active areas of procrastination research in different time periods, we divided the study's overall timespan into three time periods. During the period 1990 through 1999, there were six references with high citation bursts, with two of them by Ferrari and a third by Ferrari, Johnson, and McCown. Subsequently, in 2000 through 2009, there were eight reference bursts, and the meta-analysis and theoretical review by Steel ( 2007 ) had the highest citation burst among those 20 references. From the period 2010 through 2020, six references showed high citation bursts.

Period I (1990–1999): Preliminary Understanding of Procrastination's Antecedents

How one defines procrastination is important to interventions. During the early period of procrastination research, scholars paid significant attention to define procrastination and discuss its antecedents. Time delay in completing tasks constitutes the vital dimension that distinguishes procrastination behavior, and that distinction has set the foundation for future exploration of the behavior. Lay ( 1988 ) found that errors in estimations of time led to procrastination, then identified two types of procrastinators: pessimistic procrastinators and optimistic ones, according to whether one is optimistic or pessimistic about judgments of time. In addition, the timeframe or constraint scenario influences one's behavioral choices. Procrastinators tend to weigh short-term benefits over long-term costs (Tice and Baumeister, 1997 ).

However, time delay is just a behavioral representation, and personality traits may be in-depth inducements to procrastination behavior (Ferrari, 1991 ; Ferrari et al., 1995 ). Schouwenburg and Lay ( 1995 ) empirically studied and elaborated upon the relationship between the five-factor model and procrastination facing a sample of students, and their findings showed consistency with research by Ferrari ( 1991 ) which demonstrated that the trait facets of lacking conscientiousness and of neurotic avoidance were associated with procrastination. In addition, Ferrari ( 1992 ) evaluated two popular scales to measure procrastination: the General Procrastination (GP) scale and the Adult Inventory for Procrastination (AIP) scale. Regarding the measurement of procrastination, a variety of scales have been constructed to further enhance the development of procrastination research.

Period II (2000–2009): Investigation of Cognitive and Motivational Facets and Emergence of Various Research Methods

During period II, procrastination research with high citation bursts focused largely on two dimensions: behavioral antecedences and empirical methods. On one hand, discussions about cognitive and motivational antecedents spring up. A series of studies find that cognitive and motivational beliefs, including goal orientation, perceived self-efficacy, self-handicapping, and self-regulated learning strategies, are strongly related to procrastination (Wolters, 2003 ; Howell and Watson, 2007 ; Klassen et al., 2008 ). Specifically, Howell and Watson ( 2007 ) examined the achievement goal framework with two variables, achievement goal orientation and learning strategies usage, in which four types of goal orientation can be derived by the performance vs. mastery dimension and the approach vs. avoidance dimension. Their research found that procrastination was attributed to a mastery-avoidance orientation, whereas it was adversely related to a mastery-approach orientation. Moreover, Chu and Choi ( 2005 ) identified two types of procrastinators, active procrastinators versus passive procrastinators, in terms of the individual's time usage and perception, self-efficacy beliefs, motivational orientation, stress-coping strategies, and final outcomes. This classification of procrastinators has aroused a hot discussion about procrastination research (Zohar et al., 2019 ; Perdomo and Feliciano-Garcia, 2020 ). Cognitive and motivational antecedents are complementary to personality traits, and the antecedents and traits together reveal the complex phenomenon.

In addition, there are various research methods being applied in the research, such as meta-analyses and grounded theory. Having the strongest citation burst in period II, research that was based on a meta-analysis of procrastination by Steel ( 2007 ) elaborated on temporal motivation theory (TMT). Temporal motivational theory provides an innovative foothold for understanding self-regulation failure, using four critical indicators: expectancy, value, sensitivity to delay, and delay itself. Similarly, van Eerde ( 2003 ) conducted a meta-analysis to examine the relationship between procrastination and personality traits, and proposed that procrastination was negatively related to conscientiousness and self-efficacy, but was also actively associated with self-handicapping. Procrastinators commonly set deadlines, but research has found that external deadlines may be more effective than self-imposed ones (Ariely and Wertenbroch, 2002 ). Furthermore, Schraw et al. ( 2007 ) constructed a paradigm model through grounded theory to analyze the phenomenon of academic procrastination, looking at context and situational conditions, antecedents, phenomena, coping strategies, and consequences. These diverse research methods are enhancing our comprehensive and systematical understanding of procrastination.

Period III (2010–2020): Diverse Focuses on Procrastination Research

After nearly two decades of progressive developments, procrastination research has entered a steady track with diverse current bursts, on topics such as type distinction, theoretical perspective, temporal context, and the typical image of procrastinators. Steel ( 2010 ) revisited the trinity of procrastination — arousal procrastinators, avoidant procrastinators, and decisional procrastinators — and using the Pure Procrastination Scale (PPS) and the Irrational Procrastination Scale (IPS), he found that there was no distinct difference among the three types. Regarding research settings, a body of literature has focused on academic procrastination in-depth, and that literature has experienced a significant citation burst (Kim and Seo, 2015 ; Steel and Klingsieck, 2016 ). For example, academic procrastination is associated more highly with performance for secondary school students than for other age groups.

Notably, theoretical discussions and empirical research have been advancing synchronously. Klingsieck ( 2013 ) investigated systematic characteristics of procrastination research and concluded that theoretical perspectives to explain the phenomenon, whereas Steel and Ferrari ( 2013 ) portrayed the “typical procrastinator” using the variables of sex, age, marital status, education, community location, and nationality. Looking beyond the use of time control or time perception to define procrastination, Sirois and Pychyl ( 2013 ) compared the current self and the future self, then proposed that procrastination results from short-term mood repair and emotion regulation with the consequences being borne by the future self. In line with the part of introduction, in the last 10 years, research on procrastination has flourished and knowledge about this complex phenomenon has been emerging and expanding.

Structure Variation Analysis

Structure variation analysis (SVA) can predict the literature that will have potential transformative power in the future. Proposed by Chen ( 2012 ), structure variation analysis includes three primary metrics — the modularity change rate, cluster linkage, and centrality divergence — to monitor and discern the potential of newly published articles in specific domains. The modularity change rate measures the changes in and interconnectivity of the overall structure when newly published articles are introduced into the intellectual network. Cluster linkage focuses on these differences in linkages before and after a new between-cluster link is added by an article, whereas centrality divergence measures the structural variations in the divergence of betweenness centrality that a newly published article causes (Chen, 2012 ; Hou et al., 2020 ). The values of these metrics are higher, and the newly published articles are expected to have more potential to transform the intellectual base (Hou et al., 2020 ). Specifically, cluster linkage is a direct measure of intellectual potential and structural change (Chen, 2012 ). Therefore, we adopted cluster linkage as an indicator by which to recognize and predict the valuable ideas in newly published procrastination research. These top 20 articles with high transformative potential that were published during the period 2016-2020 were listed (see Supplementary Material for details). Research contents primarily consist of four dimensions.

Further Investigations Into Academic Procrastination

Although procrastination research has drawn mostly on samples of students, innovative research contents and methods have been emerging that enhance our understanding of academic procrastination. In the past five years, different language versions of scales have been measured and validated (Garzon Umerenkova and Gil-Flores, 2017a , b ; Svartdal, 2017 ; Guilera et al., 2018 ), and novel research areas and contents have arisen, such as how gender difference influences academic procrastination, what are the effective means of intervention, and what are the associations among academic procrastination, person-environment fit, and academic achievement (Balkis and Duru, 2016 ; Garzon Umerenkova and Gil-Flores, 2017a , b ; Goroshit, 2018 ). Interestingly, research has found that females perform academic procrastination less often and gain better academic achievements than males do (Balkis and Duru, 2017 ; Perdomo and Feliciano-Garcia, 2020 ).

In addition, academic procrastination is viewed as a fluid process. Considering the behavior holistically, three different aspects of task engagement have been discussed: initiation, completion, and pursuit. Vangsness and Young ( 2020 ) proposed the metaphors of “turtles” (steady workers), “task ninjas” (precrastinators), and “time wasters” (procrastinators) to elaborate vividly on task completion strategies when working toward deadlines. Individual differences and task characteristics can influence one's choices of a task-completion strategy. To understand the fluid and multifaceted phenomenon of procrastination, longitudinal research has been appearing. Wessel et al. ( 2019 ) observed behavioral delay longitudinally through tracking an undergraduate assignment over two weeks to reveal how passive and active procrastination each affected assignment completion.

Relationships Between Procrastination and Diverse Personality Traits

In addition to the relationship between procrastination and the five-factor model, other personality traits, such as temperament, character, emotional intelligence, impulsivity, and motivation, have been investigated in connection with procrastination. Because the five-factor model is not effective for distinguishing the earlier developing temperamental tendencies and the later developing character traits, Zohar et al. ( 2019 ) discussed how temperament and character influence procrastination in terms of active and passive procrastinators, and revealed that a dependable temperament profile and well-developed character predicted active procrastination.

Procrastination is commonly defined as a self-regulation failure that includes emotion and behavior. Emotional intelligence (EI) is an indicator with which to monitor one's feelings, thinking, and actions, and hot discussions about its relationship with procrastination have sprung up recently. Sheybani et al. ( 2017 ) elaborated on how the relationship between emotional intelligence and the five-factor model influence decisional procrastination on the basis of a students' sample. As a complement to the research above, Wypych et al. ( 2018 ) explored the roles of impulsivity, motivation, and emotion regulation in procrastination through path analysis. Motivation and impulsivity reflecting a lack of value, along with delay discounting and lack of perseverance, are predicators of procrastination, whereas emotion regulation, especially for suppression of procrastination, has only appeared to be significant in student and other low-age groups. How personality traits influence procrastination remains controversial, and further research is expected.

Procrastination in Different Life-Domains and Settings

Newly published research is paying more attention to procrastination in different sample groups across the entire life span. Not being limited to student samples, discussions about procrastination in groups such as teachers, educated adults, and workers have been emerging. With regard to different life domains, the self-oriented domains including health and leisure time, tend to procrastinate, whereas parenting is low in procrastination among highly educated adults. Although the achievement-oriented life domains of career, education, and finances are found with moderate frequency in conjunction with procrastination, these three domains together with health affect life the most (Hen and Goroshit, 2018 ). Similarly, Tibbett and Ferrari ( 2019 ) investigated the main regret domains facing cross-cultural samples, so as to determine which factors increased the likelihood of identifying oneself as a procrastinator. Their research found that forms of earning potential, such as education, finances, and career, led participants to more easily label themselves as procrastinators. Procrastination can lead to regret, and this research adopted reverse thinking to discuss the antecedents of procrastination.

In addition to academic procrastination, research about the behavior in diverse-context settings has begun to draw scholars' attention. Nauts et al. ( 2019 ) used a qualitative study to investigate why people delay their bedtime, and the study identified three forms of bedtime procrastination: deliberate procrastination, mindless procrastination, and strategic delay. Then, those researchers proposed coached interventions involving time management, priority-setting skills, and reminders according to the characteristics of the bedtime procrastination. Interestingly, novel forms of procrastination have been arising in the attention-shortage situations of the age of the internet, such as social media self-control failure (SMSCF). Du et al. ( 2019 ) found that habitual checking, ubiquity, and notifications were determinants for self-control failures due to social media use, and that finding provided insight into how to better use ICTs in a media-pervasive environment. Moreover, even beyond those life-related-context settings, procrastination in the workplace has been further explored. Hen ( 2018 ) emphasized the factor of professional role ambiguity underlying procrastination. Classification of procrastination context is important for the effectiveness of intervention and provides us with a better understanding of this multifaceted behavior.

Interventions to Procrastination

Overcoming procrastination is a necessary topic for discussion. Procrastination is prevalent and stable across situations, and it is commonly averse to one's performance and general well-being. Various types of interventions are used, such as time management, self-management, and cognitive behavioral therapy. To examine the effectiveness of those interventions, scholars have used longitudinal studies or field experimental designs to investigate these methods of intervention for procrastination. Rozental et al. ( 2017 ) examined the efficacy of internet-based cognitive behavior therapy (ICBT) to relieve procrastination, from the perspective of clinical trials. Through a one-year follow-up in a randomized controlled trial, researchers found that ICBT could be beneficial to relieve severe, chronic procrastination. Taking the temporal context into consideration, Visser et al. ( 2017 ) discussed a strengths-based approach — one element of the cognitive behavioral approach — that showed greater usefulness for students at an early stage of their studies than it did at later ages. Overall, research on the effectiveness of intervention for procrastination is relatively scarce.

Discussion and Conclusion

Discussion on procrastination research.

This article provides a systematic bibliometric analysis of procrastination research over the past 30 years. The study identifies the category distribution, co-occurrence keywords, main research clusters, and intellectual structures, with the help of CiteSpace and VOS viewer. As is shown in Figure 6 , the primary focuses for research themes have been on the definition and classification of procrastination, the relationships between procrastination and personality traits, the influences brought by procrastination, and how to better intervene in this complex phenomenon.

Bibliometric analysis and science map of the literature on procrastination.

Those contents have built the bases for procrastination research, but determining how those bases are constructed is important to the development of future research. Therefore, this article primarily discusses three aspects of intellectual structure of procrastination research: betweenness centrality, burst detection, and structural variation analysis. From the betweenness centrality analysis, three research themes are identifiable and can be generally summarized as: definition and classification of procrastination, procrastination behavior in a temporal context, and causes and interventions for procrastination.

However, procrastination research themes have evolved significantly across the time period from 1990–2020. Through burst detection analysis, we are able to infer that research has paid extraordinary attention to diverse themes at different times. In the initial stage, research is mainly about the antecedents of procrastination from the perspectives of time-management, self-regulation failure, and the five-factor model, which pays more attention to the behavior itself, such as delays in time. Subsequently, further discussions have focused on how cognitive and motivational facets such as goal orientation, perceived self-efficacy, self-handicapping, as well as self-regulated learning strategies influence procrastination. In the most recent 10 years, research has paid significant attention to expanding diverse themes, such as theoretical perspectives, typical images of procrastinators, and procrastination behavior in diverse temporal contexts. Research about procrastination has been gaining more and more attention from scholars and practitioners.

To explore newly published articles and their transformative potential, we conduct structural variation analysis. Beyond traditional research involving academic procrastination, emerging research themes consist of diverse research settings across life-domains, such as bedtime procrastination, social media self-control failure, procrastination in the workplace, and procrastination comparisons between self-oriented and achievement-oriented domains. Furthermore, novel interventions from the perspective of clinical and cognitive orientations to procrastination have been emerging in response to further investigation of procrastination's antecedents, such as internet-based cognitive behavior therapy (ICBT) and the strengths-based approach.

Conclusions and Limitations

In summary, research on procrastination has gained increasing attention during 1990 to 2020. Specifically in Figure 7 , research themes have involved in the definition, classification, antecedents, consequences, interventions, and diverse forms of procrastination across different life-domains and contexts. Furthermore, empirical research has been conducted to understand this complex and multifaceted behavior, including how best to design controlled trial experiments, how to collect and analyze the data, and so on.

Brief conclusions on procrastination research.

From the perspective of knowledge development, related research about procrastination has experienced tremendous expansion in the last 30 years. There are three notable features to describe the evolutionary process.

First, research focuses are moving from broader topics to more specific issues. Prior research mostly explored the definition and antecedents of procrastination, as well as the relationship between personality traits and procrastination. Besides, earlier procrastination research almost drew on students' setting. Based on previous research above, innovative research starts to shed light on procrastination in situation-specific domains, such as work procrastination, bedtime procrastination, as well as the interaction between problematic new media use and procrastination (Hen, 2018 ; Nauts et al., 2019 ; Przepiorka et al., 2021 ). With the evolvement of research aimed at distinct contexts, more details and core contents about procrastination have been elaborated. For example, procrastination in workplace may have association with professional role ambiguity, abusive supervision, workplace ostracism and task characteristics (Hen, 2018 ; He et al., 2021 ; Levin and Lipshits-Braziler, 2021 ). In particular, owing to the use of information and communication technology (ICTs), there currently are ample temptations to distract our attention, and those distractions can exacerbate the severity of procrastination (Du et al., 2019 ; Hong et al., 2021 ). Therefore, how to identify those different forms of procrastination, and then to reduce their adverse outcomes, will be important to discuss.

Second, antecedents and consequences of procrastination are further explored over time. On one hand, how procrastination occurs arises hot discussions from diverse dimensions including time management, personality traits, contextual characteristics, motivational and cognitive factors successively. Interestingly, investigations about neural evidences under procrastination have been emerging, such as the underlying mechanism of hippocampal-striatal and amygdala-insula to procrastination (Zhang et al., 2021 ). Those antecedents can be divided into internal factors and external factors. Internal factors including character traits and cognitive maladjustments have been elucidated fully, but scant discussion has occurred about how external factors, such as task characteristics, peers' situations, and environmental conditions, influence procrastination (Harris and Sutton, 1983 ; He et al., 2021 ). On the other hand, high prevalence of procrastination necessitates the importance to identify the negative consequences including direct and indirect. Prior research paid more attention to direct consequences, such as low performance, poor productivity, stress and illness, but the indirect consequences that can be brought about by procrastination remain to be unclear. For example, “second-hand” procrastination vividly describes the “spillover effect” of procrastination, which is exemplified by another employee often working harder in order to compensate for the lost productivity of a procrastinating coworker (Pychyl and Flett, 2012 ). Although such phenomena are common, adverse outcomes are less well investigated. Combining the contexts and groups involved, targeted discussions about the external antecedents and indirect consequences of procrastination are expected.

Third, empirical research toward procrastination emphasizes more on validity. When it comes to previous research, longitudinal studies are often of small numbers. However, procrastination is dynamic, so when most studies focus on procrastination of students' sample during just one semester or several weeks, can limit the overall viewpoints about procrastination and the effectiveness of conclusions. With the development of research, more and more longitudinal explorations are springing up to discuss long-term effects of procrastination through behavioral observation studies and so on. Besides, how to design the research and collect data evolves gradually. Self-reported was the dominant method to collect data in prior research, and measurements of procrastination usually depended on different scales. However, self-reported data are often distorted by personal processes and may not reflect the actual situation, even to overestimate the level of procrastination (Kim and Seo, 2015 ; Goroshit, 2018 ). Hence, innovative studies start to conduct field experimental designs to get observed information through randomized controlled trials. For the following research, how to combine self-reported data and observed data organically should be investigated and refined.

This bibliometric analysis to procrastination is expected to provide overall perspective for future research. However, certain limitations merit mentioning here. Owing to the limited number of pages allowed, it is difficult to clarify the related articles in detail, so discussion tends to be heuristic. Furthermore, the data for this research comes from the Web of Science database, and applying the same strategy to a different database might have yielded different results. In the future, we will conduct a systematic analysis using diverse databases to detect pivotal articles on procrastination research.

Data Availability Statement

Author contributions.

BY proposed the research question and conducted the research design. XZ analyzed the data and wrote primary manuscript. On the base of that work mentioned above, two authors discussed and adjusted the final manuscript together.

Conflict of Interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's Note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary Material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fpsyg.2022.809044/full#supplementary-material

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Definition of 'academic study' academic study

Definition of 'academic' academic.

Definition of 'study' study

Example sentences academic study

Cobuild collocations academic study, browse alphabetically academic study.

• academic specialist
• academic standard
• academic standing
• academic study
• academic subject
• academic success
• academic thesis
• All ENGLISH words that begin with 'A'

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