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Significance of the Study – Examples and Writing Guide

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Significance of the Study

Definition:

Significance of the study in research refers to the potential importance, relevance, or impact of the research findings. It outlines how the research contributes to the existing body of knowledge, what gaps it fills, or what new understanding it brings to a particular field of study.

In general, the significance of a study can be assessed based on several factors, including:

• Originality : The extent to which the study advances existing knowledge or introduces new ideas and perspectives.
• Practical relevance: The potential implications of the study for real-world situations, such as improving policy or practice.
• Theoretical contribution: The extent to which the study provides new insights or perspectives on theoretical concepts or frameworks.
• Methodological rigor : The extent to which the study employs appropriate and robust methods and techniques to generate reliable and valid data.
• Social or cultural impact : The potential impact of the study on society, culture, or public perception of a particular issue.

Types of Significance of the Study

The significance of the Study can be divided into the following types:

Theoretical Significance

Theoretical significance refers to the contribution that a study makes to the existing body of theories in a specific field. This could be by confirming, refuting, or adding nuance to a currently accepted theory, or by proposing an entirely new theory.

Practical Significance

Practical significance refers to the direct applicability and usefulness of the research findings in real-world contexts. Studies with practical significance often address real-life problems and offer potential solutions or strategies. For example, a study in the field of public health might identify a new intervention that significantly reduces the spread of a certain disease.

Significance for Future Research

This pertains to the potential of a study to inspire further research. A study might open up new areas of investigation, provide new research methodologies, or propose new hypotheses that need to be tested.

How to Write Significance of the Study

Here’s a guide to writing an effective “Significance of the Study” section in research paper, thesis, or dissertation:

• Background : Begin by giving some context about your study. This could include a brief introduction to your subject area, the current state of research in the field, and the specific problem or question your study addresses.
• Identify the Gap : Demonstrate that there’s a gap in the existing literature or knowledge that needs to be filled, which is where your study comes in. The gap could be a lack of research on a particular topic, differing results in existing studies, or a new problem that has arisen and hasn’t yet been studied.
• State the Purpose of Your Study : Clearly state the main objective of your research. You may want to state the purpose as a solution to the problem or gap you’ve previously identified.
• Contributes to the existing body of knowledge.
• Addresses a significant research gap.
• Offers a new or better solution to a problem.
• Impacts policy or practice.
• Leads to improvements in a particular field or sector.
• Identify Beneficiaries : Identify who will benefit from your study. This could include other researchers, practitioners in your field, policy-makers, communities, businesses, or others. Explain how your findings could be used and by whom.
• Future Implications : Discuss the implications of your study for future research. This could involve questions that are left open, new questions that have been raised, or potential future methodologies suggested by your study.

Significance of the Study in Research Paper

The Significance of the Study in a research paper refers to the importance or relevance of the research topic being investigated. It answers the question “Why is this research important?” and highlights the potential contributions and impacts of the study.

The significance of the study can be presented in the introduction or background section of a research paper. It typically includes the following components:

• Importance of the research problem: This describes why the research problem is worth investigating and how it relates to existing knowledge and theories.
• Potential benefits and implications: This explains the potential contributions and impacts of the research on theory, practice, policy, or society.
• Originality and novelty: This highlights how the research adds new insights, approaches, or methods to the existing body of knowledge.
• Scope and limitations: This outlines the boundaries and constraints of the research and clarifies what the study will and will not address.

Suppose a researcher is conducting a study on the “Effects of social media use on the mental health of adolescents”.

The significance of the study may be:

“The present study is significant because it addresses a pressing public health issue of the negative impact of social media use on adolescent mental health. Given the widespread use of social media among this age group, understanding the effects of social media on mental health is critical for developing effective prevention and intervention strategies. This study will contribute to the existing literature by examining the moderating factors that may affect the relationship between social media use and mental health outcomes. It will also shed light on the potential benefits and risks of social media use for adolescents and inform the development of evidence-based guidelines for promoting healthy social media use among this population. The limitations of this study include the use of self-reported measures and the cross-sectional design, which precludes causal inference.”

Significance of the Study In Thesis

The significance of the study in a thesis refers to the importance or relevance of the research topic and the potential impact of the study on the field of study or society as a whole. It explains why the research is worth doing and what contribution it will make to existing knowledge.

For example, the significance of a thesis on “Artificial Intelligence in Healthcare” could be:

• With the increasing availability of healthcare data and the development of advanced machine learning algorithms, AI has the potential to revolutionize the healthcare industry by improving diagnosis, treatment, and patient outcomes. Therefore, this thesis can contribute to the understanding of how AI can be applied in healthcare and how it can benefit patients and healthcare providers.
• AI in healthcare also raises ethical and social issues, such as privacy concerns, bias in algorithms, and the impact on healthcare jobs. By exploring these issues in the thesis, it can provide insights into the potential risks and benefits of AI in healthcare and inform policy decisions.
• Finally, the thesis can also advance the field of computer science by developing new AI algorithms or techniques that can be applied to healthcare data, which can have broader applications in other industries or fields of research.

Significance of the Study in Research Proposal

The significance of a study in a research proposal refers to the importance or relevance of the research question, problem, or objective that the study aims to address. It explains why the research is valuable, relevant, and important to the academic or scientific community, policymakers, or society at large. A strong statement of significance can help to persuade the reviewers or funders of the research proposal that the study is worth funding and conducting.

Here is an example of a significance statement in a research proposal:

Title : The Effects of Gamification on Learning Programming: A Comparative Study

Significance Statement:

This proposed study aims to investigate the effects of gamification on learning programming. With the increasing demand for computer science professionals, programming has become a fundamental skill in the computer field. However, learning programming can be challenging, and students may struggle with motivation and engagement. Gamification has emerged as a promising approach to improve students’ engagement and motivation in learning, but its effects on programming education are not yet fully understood. This study is significant because it can provide valuable insights into the potential benefits of gamification in programming education and inform the development of effective teaching strategies to enhance students’ learning outcomes and interest in programming.

Examples of Significance of the Study

Here are some examples of the significance of a study that indicates how you can write this into your research paper according to your research topic:

Research on an Improved Water Filtration System : This study has the potential to impact millions of people living in water-scarce regions or those with limited access to clean water. A more efficient and affordable water filtration system can reduce water-borne diseases and improve the overall health of communities, enabling them to lead healthier, more productive lives.

Study on the Impact of Remote Work on Employee Productivity : Given the shift towards remote work due to recent events such as the COVID-19 pandemic, this study is of considerable significance. Findings could help organizations better structure their remote work policies and offer insights on how to maximize employee productivity, wellbeing, and job satisfaction.

Investigation into the Use of Solar Power in Developing Countries : With the world increasingly moving towards renewable energy, this study could provide important data on the feasibility and benefits of implementing solar power solutions in developing countries. This could potentially stimulate economic growth, reduce reliance on non-renewable resources, and contribute to global efforts to combat climate change.

Research on New Learning Strategies in Special Education : This study has the potential to greatly impact the field of special education. By understanding the effectiveness of new learning strategies, educators can improve their curriculum to provide better support for students with learning disabilities, fostering their academic growth and social development.

Examination of Mental Health Support in the Workplace : This study could highlight the impact of mental health initiatives on employee wellbeing and productivity. It could influence organizational policies across industries, promoting the implementation of mental health programs in the workplace, ultimately leading to healthier work environments.

Evaluation of a New Cancer Treatment Method : The significance of this study could be lifesaving. The research could lead to the development of more effective cancer treatments, increasing the survival rate and quality of life for patients worldwide.

When to Write Significance of the Study

The Significance of the Study section is an integral part of a research proposal or a thesis. This section is typically written after the introduction and the literature review. In the research process, the structure typically follows this order:

• Title – The name of your research.
• Abstract – A brief summary of the entire research.
• Introduction – A presentation of the problem your research aims to solve.
• Literature Review – A review of existing research on the topic to establish what is already known and where gaps exist.
• Significance of the Study – An explanation of why the research matters and its potential impact.

In the Significance of the Study section, you will discuss why your study is important, who it benefits, and how it adds to existing knowledge or practice in your field. This section is your opportunity to convince readers, and potentially funders or supervisors, that your research is valuable and worth undertaking.

Advantages of Significance of the Study

The Significance of the Study section in a research paper has multiple advantages:

• Establishes Relevance: This section helps to articulate the importance of your research to your field of study, as well as the wider society, by explicitly stating its relevance. This makes it easier for other researchers, funders, and policymakers to understand why your work is necessary and worth supporting.
• Guides the Research: Writing the significance can help you refine your research questions and objectives. This happens as you critically think about why your research is important and how it contributes to your field.
• Attracts Funding: If you are seeking funding or support for your research, having a well-written significance of the study section can be key. It helps to convince potential funders of the value of your work.
• Opens up Further Research: By stating the significance of the study, you’re also indicating what further research could be carried out in the future, based on your work. This helps to pave the way for future studies and demonstrates that your research is a valuable addition to the field.
• Provides Practical Applications: The significance of the study section often outlines how the research can be applied in real-world situations. This can be particularly important in applied sciences, where the practical implications of research are crucial.
• Enhances Understanding: This section can help readers understand how your study fits into the broader context of your field, adding value to the existing literature and contributing new knowledge or insights.

Limitations of Significance of the Study

The Significance of the Study section plays an essential role in any research. However, it is not without potential limitations. Here are some that you should be aware of:

• Subjectivity: The importance and implications of a study can be subjective and may vary from person to person. What one researcher considers significant might be seen as less critical by others. The assessment of significance often depends on personal judgement, biases, and perspectives.
• Predictability of Impact: While you can outline the potential implications of your research in the Significance of the Study section, the actual impact can be unpredictable. Research doesn’t always yield the expected results or have the predicted impact on the field or society.
• Difficulty in Measuring: The significance of a study is often qualitative and can be challenging to measure or quantify. You can explain how you think your research will contribute to your field or society, but measuring these outcomes can be complex.
• Possibility of Overstatement: Researchers may feel pressured to amplify the potential significance of their study to attract funding or interest. This can lead to overstating the potential benefits or implications, which can harm the credibility of the study if these results are not achieved.
• Overshadowing of Limitations: Sometimes, the significance of the study may overshadow the limitations of the research. It is important to balance the potential significance with a thorough discussion of the study’s limitations.
• Dependence on Successful Implementation: The significance of the study relies on the successful implementation of the research. If the research process has flaws or unexpected issues arise, the anticipated significance might not be realized.

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Home / Why the research question is so important

Why the research question is so important

04/05/2018 at 5:42 am

A research question is a sentence that defines what you will examine, within which population, and what the outcome of interest will be. Defining a clear research question is the first and most important part of the project. Though it sounds simple, writing a research question is tricky even for experienced researchers. This video will build your understanding of where to start looking for research questions, how to write them, and why it is important to work with a solid research question from the beginning of the project.

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Additional Content

Links to useful research papers.

Farrugia P, Petrisor BA, Farrokhyar F, Bhandari M. Research questions, hypotheses and objectives. Canadian Journal of Surgery. 2010;53(4):278-281. http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2912019/

Aslam, S., & Emmanuel, P. (2010). Formulating a researchable question: A critical step for facilitating good clinical research. Indian J Sex Transm Dis, 31(1), 47-50. https://www.ncbi.nlm.nih.gov/pubmed/21808439

Beitz, J. M. (2006). Writing the researchable question. J Wound Ostomy Continence Nurs, 33(2), 122-124. https://www.ncbi.nlm.nih.gov/pubmed/16572009

Links to useful websites

Centre for Clinical Effectivenbess

http://www.monashhealth.org/page/Resources

Centre for Evidence Based Medicine

https://www.cebm.net/category/ebm-resources/tools/

Libraries in SWSLHD

https://www.swslhd.health.nsw.gov.au/liverpool/library/default.html

https://www.swslhd.health.nsw.gov.au/ccq/library/

https://www.swslhd.health.nsw.gov.au/Fairfield/library/

https://www.swslhd.health.nsw.gov.au/bankstown/library/

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How To Write Significance of the Study (With Examples) 

Whether you’re writing a research paper or thesis, a portion called Significance of the Study ensures your readers understand the impact of your work. Learn how to effectively write this vital part of your research paper or thesis through our detailed steps, guidelines, and examples.

Related: How to Write a Concept Paper for Academic Research

Table of Contents

What is the significance of the study.

The Significance of the Study presents the importance of your research. It allows you to prove the study’s impact on your field of research, the new knowledge it contributes, and the people who will benefit from it.

Related: How To Write Scope and Delimitation of a Research Paper (With Examples)

Where Should I Put the Significance of the Study?

The Significance of the Study is part of the first chapter or the Introduction. It comes after the research’s rationale, problem statement, and hypothesis.

Related: How to Make Conceptual Framework (with Examples and Templates)

Why Should I Include the Significance of the Study?

The purpose of the Significance of the Study is to give you space to explain to your readers how exactly your research will be contributing to the literature of the field you are studying 1 . It’s where you explain why your research is worth conducting and its significance to the community, the people, and various institutions.

How To Write Significance of the Study: 5 Steps

Below are the steps and guidelines for writing your research’s Significance of the Study.

1. Use Your Research Problem as a Starting Point

Your problem statement can provide clues to your research study’s outcome and who will benefit from it 2 .

Ask yourself, “How will the answers to my research problem be beneficial?”. In this manner, you will know how valuable it is to conduct your study. 

Let’s say your research problem is “What is the level of effectiveness of the lemongrass (Cymbopogon citratus) in lowering the blood glucose level of Swiss mice (Mus musculus)?”

Discovering a positive correlation between the use of lemongrass and lower blood glucose level may lead to the following results:

• Increased public understanding of the plant’s medical properties;
• Higher appreciation of the importance of lemongrass  by the community;
• Adoption of lemongrass tea as a cheap, readily available, and natural remedy to lower their blood glucose level.

Once you’ve zeroed in on the general benefits of your study, it’s time to break it down into specific beneficiaries.

2. State How Your Research Will Contribute to the Existing Literature in the Field

Think of the things that were not explored by previous studies. Then, write how your research tackles those unexplored areas. Through this, you can convince your readers that you are studying something new and adding value to the field.

3. Explain How Your Research Will Benefit Society

In this part, tell how your research will impact society. Think of how the results of your study will change something in your community. 

For example, in the study about using lemongrass tea to lower blood glucose levels, you may indicate that through your research, the community will realize the significance of lemongrass and other herbal plants. As a result, the community will be encouraged to promote the cultivation and use of medicinal plants.

4. Mention the Specific Persons or Institutions Who Will Benefit From Your Study

Using the same example above, you may indicate that this research’s results will benefit those seeking an alternative supplement to prevent high blood glucose levels.

5. Indicate How Your Study May Help Future Studies in the Field

You must also specifically indicate how your research will be part of the literature of your field and how it will benefit future researchers. In our example above, you may indicate that through the data and analysis your research will provide, future researchers may explore other capabilities of herbal plants in preventing different diseases.

Tips and Warnings

• Think ahead . By visualizing your study in its complete form, it will be easier for you to connect the dots and identify the beneficiaries of your research.
• Write concisely. Make it straightforward, clear, and easy to understand so that the readers will appreciate the benefits of your research. Avoid making it too long and wordy.
• Go from general to specific . Like an inverted pyramid, you start from above by discussing the general contribution of your study and become more specific as you go along. For instance, if your research is about the effect of remote learning setup on the mental health of college students of a specific university , you may start by discussing the benefits of the research to society, to the educational institution, to the learning facilitators, and finally, to the students.
• Seek help . For example, you may ask your research adviser for insights on how your research may contribute to the existing literature. If you ask the right questions, your research adviser can point you in the right direction.
• Revise, revise, revise. Be ready to apply necessary changes to your research on the fly. Unexpected things require adaptability, whether it’s the respondents or variables involved in your study. There’s always room for improvement, so never assume your work is done until you have reached the finish line.

Significance of the Study Examples

This section presents examples of the Significance of the Study using the steps and guidelines presented above.

Example 1: STEM-Related Research

Research Topic: Level of Effectiveness of the Lemongrass ( Cymbopogon citratus ) Tea in Lowering the Blood Glucose Level of Swiss Mice ( Mus musculus ).

Significance of the Study .

This research will provide new insights into the medicinal benefit of lemongrass ( Cymbopogon citratus ), specifically on its hypoglycemic ability.

Through this research, the community will further realize promoting medicinal plants, especially lemongrass, as a preventive measure against various diseases. People and medical institutions may also consider lemongrass tea as an alternative supplement against hyperglycemia. 

Moreover, the analysis presented in this study will convey valuable information for future research exploring the medicinal benefits of lemongrass and other medicinal plants.  

Example 2: Business and Management-Related Research

Research Topic: A Comparative Analysis of Traditional and Social Media Marketing of Small Clothing Enterprises.

Significance of the Study:

By comparing the two marketing strategies presented by this research, there will be an expansion on the current understanding of the firms on these marketing strategies in terms of cost, acceptability, and sustainability. This study presents these marketing strategies for small clothing enterprises, giving them insights into which method is more appropriate and valuable for them. 

Specifically, this research will benefit start-up clothing enterprises in deciding which marketing strategy they should employ. Long-time clothing enterprises may also consider the result of this research to review their current marketing strategy.

Furthermore, a detailed presentation on the comparison of the marketing strategies involved in this research may serve as a tool for further studies to innovate the current method employed in the clothing Industry.

Example 3: Social Science -Related Research.

Research Topic:  Divide Et Impera : An Overview of How the Divide-and-Conquer Strategy Prevailed on Philippine Political History.

Significance of the Study :

Through the comprehensive exploration of this study on Philippine political history, the influence of the Divide et Impera, or political decentralization, on the political discernment across the history of the Philippines will be unraveled, emphasized, and scrutinized. Moreover, this research will elucidate how this principle prevailed until the current political theatre of the Philippines.

In this regard, this study will give awareness to society on how this principle might affect the current political context. Moreover, through the analysis made by this study, political entities and institutions will have a new approach to how to deal with this principle by learning about its influence in the past.

In addition, the overview presented in this research will push for new paradigms, which will be helpful for future discussion of the Divide et Impera principle and may lead to a more in-depth analysis.

Example 4: Humanities-Related Research

Research Topic: Effectiveness of Meditation on Reducing the Anxiety Levels of College Students.

Significance of the Study: 

This research will provide new perspectives in approaching anxiety issues of college students through meditation. 

Specifically, this research will benefit the following:

 Community – this study spreads awareness on recognizing anxiety as a mental health concern and how meditation can be a valuable approach to alleviating it.

Academic Institutions and Administrators – through this research, educational institutions and administrators may promote programs and advocacies regarding meditation to help students deal with their anxiety issues.

Mental health advocates – the result of this research will provide valuable information for the advocates to further their campaign on spreading awareness on dealing with various mental health issues, including anxiety, and how to stop stigmatizing those with mental health disorders.

Parents – this research may convince parents to consider programs involving meditation that may help the students deal with their anxiety issues.

Students will benefit directly from this research as its findings may encourage them to consider meditation to lower anxiety levels.

Future researchers – this study covers information involving meditation as an approach to reducing anxiety levels. Thus, the result of this study can be used for future discussions on the capabilities of meditation in alleviating other mental health concerns.

Frequently Asked Questions

1. what is the difference between the significance of the study and the rationale of the study.

Both aim to justify the conduct of the research. However, the Significance of the Study focuses on the specific benefits of your research in the field, society, and various people and institutions. On the other hand, the Rationale of the Study gives context on why the researcher initiated the conduct of the study.

Let’s take the research about the Effectiveness of Meditation in Reducing Anxiety Levels of College Students as an example. Suppose you are writing about the Significance of the Study. In that case, you must explain how your research will help society, the academic institution, and students deal with anxiety issues through meditation. Meanwhile, for the Rationale of the Study, you may state that due to the prevalence of anxiety attacks among college students, you’ve decided to make it the focal point of your research work.

2. What is the difference between Justification and the Significance of the Study?

In Justification, you express the logical reasoning behind the conduct of the study. On the other hand, the Significance of the Study aims to present to your readers the specific benefits your research will contribute to the field you are studying, community, people, and institutions.

Suppose again that your research is about the Effectiveness of Meditation in Reducing the Anxiety Levels of College Students. Suppose you are writing the Significance of the Study. In that case, you may state that your research will provide new insights and evidence regarding meditation’s ability to reduce college students’ anxiety levels. Meanwhile, you may note in the Justification that studies are saying how people used meditation in dealing with their mental health concerns. You may also indicate how meditation is a feasible approach to managing anxiety using the analysis presented by previous literature.

3. How should I start my research’s Significance of the Study section?

– This research will contribute… – The findings of this research… – This study aims to… – This study will provide… – Through the analysis presented in this study… – This study will benefit…

Moreover, you may start the Significance of the Study by elaborating on the contribution of your research in the field you are studying.

4. What is the difference between the Purpose of the Study and the Significance of the Study?

The Purpose of the Study focuses on why your research was conducted, while the Significance of the Study tells how the results of your research will benefit anyone.

Suppose your research is about the Effectiveness of Lemongrass Tea in Lowering the Blood Glucose Level of Swiss Mice . You may include in your Significance of the Study that the research results will provide new information and analysis on the medical ability of lemongrass to solve hyperglycemia. Meanwhile, you may include in your Purpose of the Study that your research wants to provide a cheaper and natural way to lower blood glucose levels since commercial supplements are expensive.

5. What is the Significance of the Study in Tagalog?

In Filipino research, the Significance of the Study is referred to as Kahalagahan ng Pag-aaral.

• Draft your Significance of the Study. Retrieved 18 April 2021, from http://dissertationedd.usc.edu/draft-your-significance-of-the-study.html
• Regoniel, P. (2015). Two Tips on How to Write the Significance of the Study. Retrieved 18 April 2021, from https://simplyeducate.me/2015/02/09/significance-of-the-study/

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Jewel Kyle Fabula

Jewel Kyle Fabula is a Bachelor of Science in Economics student at the University of the Philippines Diliman. His passion for learning mathematics developed as he competed in some mathematics competitions during his Junior High School years. He loves cats, playing video games, and listening to music.

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What is the Significance of a Study? Examples and Guide

If you’re reading this post you’re probably wondering: what is the significance of a study?

No matter where you’re at with a piece of research, it is a good idea to think about the potential significance of your work. And sometimes you’ll have to explicitly write a statement of significance in your papers, it addition to it forming part of your thesis.

In this post I’ll cover what the significance of a study is, how to measure it, how to describe it with examples and add in some of my own experiences having now worked in research for over nine years.

If you’re reading this because you’re writing up your first paper, welcome! You may also like my how-to guide for all aspects of writing your first research paper .

Looking for guidance on writing the statement of significance for a paper or thesis? Click here to skip straight to that section.

What is the Significance of a Study?

For research papers, theses or dissertations it’s common to explicitly write a section describing the significance of the study. We’ll come onto what to include in that section in just a moment.

However the significance of a study can actually refer to several different things.

Working our way from the most technical to the broadest, depending on the context, the significance of a study may refer to:

• Within your study: Statistical significance. Can we trust the findings?
• Wider research field: Research significance. How does your study progress the field?
• Commercial / economic significance: Could there be business opportunities for your findings?
• Societal significance: What impact could your study have on the wider society.
• And probably other domain-specific significance!

We’ll shortly cover each of them in turn, including how they’re measured and some examples for each type of study significance.

But first, let’s touch on why you should consider the significance of your research at an early stage.

Why Care About the Significance of a Study?

No matter what is motivating you to carry out your research, it is sensible to think about the potential significance of your work. In the broadest sense this asks, how does the study contribute to the world?

After all, for many people research is only worth doing if it will result in some expected significance. For the vast majority of us our studies won’t be significant enough to reach the evening news, but most studies will help to enhance knowledge in a particular field and when research has at least some significance it makes for a far more fulfilling longterm pursuit.

Furthermore, a lot of us are carrying out research funded by the public. It therefore makes sense to keep an eye on what benefits the work could bring to the wider community.

Often in research you’ll come to a crossroads where you must decide which path of research to pursue. Thinking about the potential benefits of a strand of research can be useful for deciding how to spend your time, money and resources.

It’s worth noting though, that not all research activities have to work towards obvious significance. This is especially true while you’re a PhD student, where you’re figuring out what you enjoy and may simply be looking for an opportunity to learn a new skill.

However, if you’re trying to decide between two potential projects, it can be useful to weigh up the potential significance of each.

Let’s now dive into the different types of significance, starting with research significance.

Research Significance

What is the research significance of a study.

Unless someone specifies which type of significance they’re referring to, it is fair to assume that they want to know about the research significance of your study.

Research significance describes how your work has contributed to the field, how it could inform future studies and progress research.

Where should I write about my study’s significance in my thesis?

Typically you should write about your study’s significance in the Introduction and Conclusions sections of your thesis.

It’s important to mention it in the Introduction so that the relevance of your work and the potential impact and benefits it could have on the field are immediately apparent. Explaining why your work matters will help to engage readers (and examiners!) early on.

It’s also a good idea to detail the study’s significance in your Conclusions section. This adds weight to your findings and helps explain what your study contributes to the field.

On occasion you may also choose to include a brief description in your Abstract.

What is expected when submitting an article to a journal

It is common for journals to request a statement of significance, although this can sometimes be called other things such as:

• Impact statement
• Significance statement
• Advances in knowledge section

Here is one such example of what is expected:

Impact Statement:  An Impact Statement is required for all submissions.  Your impact statement will be evaluated by the Editor-in-Chief, Global Editors, and appropriate Associate Editor. For your manuscript to receive full review, the editors must be convinced that it is an important advance in for the field. The Impact Statement is not a restating of the abstract. It should address the following: Why is the work submitted important to the field? How does the work submitted advance the field? What new information does this work impart to the field? How does this new information impact the field? Experimental Biology and Medicine journal, author guidelines

Typically the impact statement will be shorter than the Abstract, around 150 words.

Defining the study’s significance is helpful not just for the impact statement (if the journal asks for one) but also for building a more compelling argument throughout your submission. For instance, usually you’ll start the Discussion section of a paper by highlighting the research significance of your work. You’ll also include a short description in your Abstract too.

How to describe the research significance of a study, with examples

Whether you’re writing a thesis or a journal article, the approach to writing about the significance of a study are broadly the same.

I’d therefore suggest using the questions above as a starting point to base your statements on.

• Why is the work submitted important to the field?
• How does the work submitted advance the field?
• What new information does this work impart to the field?
• How does this new information impact the field?

Answer those questions and you’ll have a much clearer idea of the research significance of your work.

When describing it, try to clearly state what is novel about your study’s contribution to the literature. Then go on to discuss what impact it could have on progressing the field along with recommendations for future work.

Potential sentence starters

If you’re not sure where to start, why not set a 10 minute timer and have a go at trying to finish a few of the following sentences. Not sure on what to put? Have a chat to your supervisor or lab mates and they may be able to suggest some ideas.

• This study is important to the field because…
• These findings advance the field by…
• Our results highlight the importance of…
• Our discoveries impact the field by…

Now you’ve had a go let’s have a look at some real life examples.

Statement of significance examples

A statement of significance / impact:

Impact Statement This review highlights the historical development of the concept of “ideal protein” that began in the 1950s and 1980s for poultry and swine diets, respectively, and the major conceptual deficiencies of the long-standing concept of “ideal protein” in animal nutrition based on recent advances in amino acid (AA) metabolism and functions. Nutritionists should move beyond the “ideal protein” concept to consider optimum ratios and amounts of all proteinogenic AAs in animal foods and, in the case of carnivores, also taurine. This will help formulate effective low-protein diets for livestock, poultry, and fish, while sustaining global animal production. Because they are not only species of agricultural importance, but also useful models to study the biology and diseases of humans as well as companion (e.g. dogs and cats), zoo, and extinct animals in the world, our work applies to a more general readership than the nutritionists and producers of farm animals. Wu G, Li P. The “ideal protein” concept is not ideal in animal nutrition.  Experimental Biology and Medicine . 2022;247(13):1191-1201. doi: 10.1177/15353702221082658

And the same type of section but this time called “Advances in knowledge”:

Advances in knowledge: According to the MY-RADs criteria, size measurements of focal lesions in MRI are now of relevance for response assessment in patients with monoclonal plasma cell disorders. Size changes of 1 or 2 mm are frequently observed due to uncertainty of the measurement only, while the actual focal lesion has not undergone any biological change. Size changes of at least 6 mm or more in  T 1  weighted or  T 2  weighted short tau inversion recovery sequences occur in only 5% or less of cases when the focal lesion has not undergone any biological change. Wennmann M, Grözinger M, Weru V, et al. Test-retest, inter- and intra-rater reproducibility of size measurements of focal bone marrow lesions in MRI in patients with multiple myeloma [published online ahead of print, 2023 Apr 12].  Br J Radiol . 2023;20220745. doi: 10.1259/bjr.20220745

Other examples of research significance

Moving beyond the formal statement of significance, here is how you can describe research significance more broadly within your paper.

Describing research impact in an Abstract of a paper:

Three-dimensional visualisation and quantification of the chondrocyte population within articular cartilage can be achieved across a field of view of several millimetres using laboratory-based micro-CT. The ability to map chondrocytes in 3D opens possibilities for research in fields from skeletal development through to medical device design and treatment of cartilage degeneration. Conclusions section of the abstract in my first paper .

In the Discussion section of a paper:

We report for the utility of a standard laboratory micro-CT scanner to visualise and quantify features of the chondrocyte population within intact articular cartilage in 3D. This study represents a complimentary addition to the growing body of evidence supporting the non-destructive imaging of the constituents of articular cartilage. This offers researchers the opportunity to image chondrocyte distributions in 3D without specialised synchrotron equipment, enabling investigations such as chondrocyte morphology across grades of cartilage damage, 3D strain mapping techniques such as digital volume correlation to evaluate mechanical properties  in situ , and models for 3D finite element analysis  in silico  simulations. This enables an objective quantification of chondrocyte distribution and morphology in three dimensions allowing greater insight for investigations into studies of cartilage development, degeneration and repair. One such application of our method, is as a means to provide a 3D pattern in the cartilage which, when combined with digital volume correlation, could determine 3D strain gradient measurements enabling potential treatment and repair of cartilage degeneration. Moreover, the method proposed here will allow evaluation of cartilage implanted with tissue engineered scaffolds designed to promote chondral repair, providing valuable insight into the induced regenerative process. The Discussion section of the paper is laced with references to research significance.

How is longer term research significance measured?

Looking beyond writing impact statements within papers, sometimes you’ll want to quantify the long term research significance of your work. For instance when applying for jobs.

The most obvious measure of a study’s long term research significance is the number of citations it receives from future publications. The thinking is that a study which receives more citations will have had more research impact, and therefore significance , than a study which received less citations. Citations can give a broad indication of how useful the work is to other researchers but citations aren’t really a good measure of significance.

Bear in mind that us researchers can be lazy folks and sometimes are simply looking to cite the first paper which backs up one of our claims. You can find studies which receive a lot of citations simply for packaging up the obvious in a form which can be easily found and referenced, for instance by having a catchy or optimised title.

Likewise, research activity varies wildly between fields. Therefore a certain study may have had a big impact on a particular field but receive a modest number of citations, simply because not many other researchers are working in the field.

Nevertheless, citations are a standard measure of significance and for better or worse it remains impressive for someone to be the first author of a publication receiving lots of citations.

Other measures for the research significance of a study include:

• Accolades: best paper awards at conferences, thesis awards, “most downloaded” titles for articles, press coverage.
• How much follow-on research the study creates. For instance, part of my PhD involved a novel material initially developed by another PhD student in the lab. That PhD student’s research had unlocked lots of potential new studies and now lots of people in the group were using the same material and developing it for different applications. The initial study may not receive a high number of citations yet long term it generated a lot of research activity.

That covers research significance, but you’ll often want to consider other types of significance for your study and we’ll cover those next.

Statistical Significance

What is the statistical significance of a study.

Often as part of a study you’ll carry out statistical tests and then state the statistical significance of your findings: think p-values eg <0.05. It is useful to describe the outcome of these tests within your report or paper, to give a measure of statistical significance.

Effectively you are trying to show whether the performance of your innovation is actually better than a control or baseline and not just chance. Statistical significance deserves a whole other post so I won’t go into a huge amount of depth here.

Things that make publication in  The BMJ  impossible or unlikely Internal validity/robustness of the study • It had insufficient statistical power, making interpretation difficult; • Lack of statistical power; The British Medical Journal’s guide for authors

Calculating statistical significance isn’t always necessary (or valid) for a study, such as if you have a very small number of samples, but it is a very common requirement for scientific articles.

Writing a journal article? Check the journal’s guide for authors to see what they expect. Generally if you have approximately five or more samples or replicates it makes sense to start thinking about statistical tests. Speak to your supervisor and lab mates for advice, and look at other published articles in your field.

How is statistical significance measured?

Statistical significance is quantified using p-values . Depending on your study design you’ll choose different statistical tests to compute the p-value.

A p-value of 0.05 is a common threshold value. The 0.05 means that there is a 1/20 chance that the difference in performance you’re reporting is just down to random chance.

• p-values above 0.05 mean that the result isn’t statistically significant enough to be trusted: it is too likely that the effect you’re showing is just luck.
• p-values less than or equal to 0.05 mean that the result is statistically significant. In other words: unlikely to just be chance, which is usually considered a good outcome.

Low p-values (eg p = 0.001) mean that it is highly unlikely to be random chance (1/1000 in the case of p = 0.001), therefore more statistically significant.

It is important to clarify that, although low p-values mean that your findings are statistically significant, it doesn’t automatically mean that the result is scientifically important. More on that in the next section on research significance.

How to describe the statistical significance of your study, with examples

In the first paper from my PhD I ran some statistical tests to see if different staining techniques (basically dyes) increased how well you could see cells in cow tissue using micro-CT scanning (a 3D imaging technique).

In your methods section you should mention the statistical tests you conducted and then in the results you will have statements such as:

Between mediums for the two scan protocols C/N [contrast to noise ratio] was greater for EtOH than the PBS in both scanning methods (both  p  < 0.0001) with mean differences of 1.243 (95% CI [confidence interval] 0.709 to 1.778) for absorption contrast and 6.231 (95% CI 5.772 to 6.690) for propagation contrast. … Two repeat propagation scans were taken of samples from the PTA-stained groups. No difference in mean C/N was found with either medium: PBS had a mean difference of 0.058 ( p  = 0.852, 95% CI -0.560 to 0.676), EtOH had a mean difference of 1.183 ( p  = 0.112, 95% CI 0.281 to 2.648). From the Results section of my first paper, available here . Square brackets added for this post to aid clarity.

From this text the reader can infer from the first paragraph that there was a statistically significant difference in using EtOH compared to PBS (really small p-value of <0.0001). However, from the second paragraph, the difference between two repeat scans was statistically insignificant for both PBS (p = 0.852) and EtOH (p = 0.112).

By conducting these statistical tests you have then earned your right to make bold statements, such as these from the discussion section:

Propagation phase-contrast increases the contrast of individual chondrocytes [cartilage cells] compared to using absorption contrast. From the Discussion section from the same paper.

Without statistical tests you have no evidence that your results are not just down to random chance.

Beyond describing the statistical significance of a study in the main body text of your work, you can also show it in your figures.

In figures such as bar charts you’ll often see asterisks to represent statistical significance, and “n.s.” to show differences between groups which are not statistically significant. Here is one such figure, with some subplots, from the same paper:

In this example an asterisk (*) between two bars represents p < 0.05. Two asterisks (**) represents p < 0.001 and three asterisks (***) represents p < 0.0001. This should always be stated in the caption of your figure since the values that each asterisk refers to can vary.

Now that we know if a study is showing statistically and research significance, let’s zoom out a little and consider the potential for commercial significance.

Commercial and Industrial Significance

What are commercial and industrial significance.

Moving beyond significance in relation to academia, your research may also have commercial or economic significance.

Simply put:

• Commercial significance: could the research be commercialised as a product or service? Perhaps the underlying technology described in your study could be licensed to a company or you could even start your own business using it.
• Industrial significance: more widely than just providing a product which could be sold, does your research provide insights which may affect a whole industry? Such as: revealing insights or issues with current practices, performance gains you don’t want to commercialise (e.g. solar power efficiency), providing suggested frameworks or improvements which could be employed industry-wide.

I’ve grouped these two together because there can certainly be overlap. For instance, perhaps your new technology could be commercialised whilst providing wider improvements for the whole industry.

Commercial and industrial significance are not relevant to most studies, so only write about it if you and your supervisor can think of reasonable routes to your work having an impact in these ways.

How are commercial and industrial significance measured?

Unlike statistical and research significances, the measures of commercial and industrial significance can be much more broad.

Here are some potential measures of significance:

Commercial significance:

• How much value does your technology bring to potential customers or users?
• How big is the potential market and how much revenue could the product potentially generate?
• Is the intellectual property protectable? i.e. patentable, or if not could the novelty be protected with trade secrets: if so publish your method with caution!
• If commercialised, could the product bring employment to a geographical area?

Industrial significance:

What impact could it have on the industry? For instance if you’re revealing an issue with something, such as unintended negative consequences of a drug , what does that mean for the industry and the public? This could be:

• Reduced overhead costs
• Better safety
• Faster production methods
• Improved scaleability

How to describe the commercial and industrial significance of a study, with examples

Commercial significance.

If your technology could be commercially viable, and you’ve got an interest in commercialising it yourself, it is likely that you and your university may not want to immediately publish the study in a journal.

You’ll probably want to consider routes to exploiting the technology and your university may have a “technology transfer” team to help researchers navigate the various options.

However, if instead of publishing a paper you’re submitting a thesis or dissertation then it can be useful to highlight the commercial significance of your work. In this instance you could include statements of commercial significance such as:

The measurement technology described in this study provides state of the art performance and could enable the development of low cost devices for aerospace applications. An example of commercial significance I invented for this post

Industrial significance

First, think about the industrial sectors who could benefit from the developments described in your study.

For example if you’re working to improve battery efficiency it is easy to think of how it could lead to performance gains for certain industries, like personal electronics or electric vehicles. In these instances you can describe the industrial significance relatively easily, based off your findings.

For example:

By utilising abundant materials in the described battery fabrication process we provide a framework for battery manufacturers to reduce dependence on rare earth components. Again, an invented example

For other technologies there may well be industrial applications but they are less immediately obvious and applicable. In these scenarios the best you can do is to simply reframe your research significance statement in terms of potential commercial applications in a broad way.

As a reminder: not all studies should address industrial significance, so don’t try to invent applications just for the sake of it!

Societal Significance

What is the societal significance of a study.

The most broad category of significance is the societal impact which could stem from it.

If you’re working in an applied field it may be quite easy to see a route for your research to impact society. For others, the route to societal significance may be less immediate or clear.

Studies can help with big issues facing society such as:

• Medical applications : vaccines, surgical implants, drugs, improving patient safety. For instance this medical device and drug combination I worked on which has a very direct route to societal significance.
• Political significance : Your research may provide insights which could contribute towards potential changes in policy or better understanding of issues facing society.
• Public health : for instance COVID-19 transmission and related decisions.
• Climate change : mitigation such as more efficient solar panels and lower cost battery solutions, and studying required adaptation efforts and technologies. Also, better understanding around related societal issues, for instance this study on the effects of temperature on hate speech.

How is societal significance measured?

Societal significance at a high level can be quantified by the size of its potential societal effect. Just like a lab risk assessment, you can think of it in terms of probability (or how many people it could help) and impact magnitude.

Societal impact = How many people it could help x the magnitude of the impact

Think about how widely applicable the findings are: for instance does it affect only certain people? Then think about the potential size of the impact: what kind of difference could it make to those people?

Between these two metrics you can get a pretty good overview of the potential societal significance of your research study.

How to describe the societal significance of a study, with examples

Quite often the broad societal significance of your study is what you’re setting the scene for in your Introduction. In addition to describing the existing literature, it is common to for the study’s motivation to touch on its wider impact for society.

For those of us working in healthcare research it is usually pretty easy to see a path towards societal significance.

Our CLOUT model has state-of-the-art performance in mortality prediction, surpassing other competitive NN models and a logistic regression model … Our results show that the risk factors identified by the CLOUT model agree with physicians’ assessment, suggesting that CLOUT could be used in real-world clinicalsettings. Our results strongly support that CLOUT may be a useful tool to generate clinical prediction models, especially among hospitalized and critically ill patient populations. Learning Latent Space Representations to Predict Patient Outcomes: Model Development and Validation

In other domains the societal significance may either take longer or be more indirect, meaning that it can be more difficult to describe the societal impact.

Even so, here are some examples I’ve found from studies in non-healthcare domains:

We examined food waste as an initial investigation and test of this methodology, and there is clear potential for the examination of not only other policy texts related to food waste (e.g., liability protection, tax incentives, etc.; Broad Leib et al., 2020) but related to sustainable fishing (Worm et al., 2006) and energy use (Hawken, 2017). These other areas are of obvious relevance to climate change… AI-Based Text Analysis for Evaluating Food Waste Policies

The continued development of state-of-the art NLP tools tailored to climate policy will allow climate researchers and policy makers to extract meaningful information from this growing body of text, to monitor trends over time and administrative units, and to identify potential policy improvements. BERT Classification of Paris Agreement Climate Action Plans

Top Tips For Identifying & Writing About the Significance of Your Study

• Writing a thesis? Describe the significance of your study in the Introduction and the Conclusion .
• Submitting a paper? Read the journal’s guidelines. If you’re writing a statement of significance for a journal, make sure you read any guidance they give for what they’re expecting.
• Take a step back from your research and consider your study’s main contributions.
• Read previously published studies in your field . Use this for inspiration and ideas on how to describe the significance of your own study
• Discuss the study with your supervisor and potential co-authors or collaborators and brainstorm potential types of significance for it.

Now you’ve finished reading up on the significance of a study you may also like my how-to guide for all aspects of writing your first research paper .

Writing an academic journal paper

I hope that you’ve learned something useful from this article about the significance of a study. If you have any more research-related questions let me know, I’m here to help.

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Significance of a Study: Revisiting the “So What” Question

• 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))

30k Accesses

Every researcher wants their study to matter—to make a positive difference for their professional communities. To ensure your study matters, you can formulate clear hypotheses and choose methods that will test them well, as described in Chaps. 1, 2, 3 and 4. You can go further, however, by considering some of the terms commonly used to describe the importance of studies, terms like significance, contributions, and implications. As you clarify for yourself the meanings of these terms, you learn that whether your study matters depends on how convincingly you can argue for its importance. Perhaps most surprising is that convincing others of its importance rests with the case you make before the data are ever gathered. The importance of your hypotheses should be apparent before you test them. Are your predictions about things the profession cares about? Can you make them with a striking degree of precision? Are the rationales that support them compelling? You are answering the “So what?” question as you formulate hypotheses and design tests of them. This means you can control the answer. You do not need to cross your fingers and hope as you collect data.

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

Part I. Setting the Groundwork

One of the most common questions asked of researchers is “So what?” What difference does your study make? Why are the findings important? The “so what” question is one of the most basic questions, often perceived by novice researchers as the most difficult question to answer. Indeed, addressing the “so what” question continues to challenge even experienced researchers. It is not always easy to articulate a convincing argument for the importance of your work. It can be especially difficult to describe its importance without falling into the trap of making claims that reach beyond the data.

That this issue is a challenge for researchers is illustrated by our analysis of reviewer comments for JRME . About one-third of the reviews for manuscripts that were ultimately rejected included concerns about the importance of the study. Said another way, reviewers felt the “So what?” question had not been answered. To paraphrase one journal reviewer, “The manuscript left me unsure of what the contribution of this work to the field’s knowledge is, and therefore I doubt its significance.” We expect this is a frequent concern of reviewers for all research journals.

Our goal in this chapter is to help you navigate the pressing demands of journal reviewers, editors, and readers for demonstrating the importance of your work while staying within the bounds of acceptable claims based on your results. We will begin by reviewing what we have said about these issues in previous chapters. We will then clarify one of the confusing aspects of developing appropriate arguments—the absence of consensus definitions of key terms such as significance, contributions, and implications. Based on the definitions we propose, we will examine the critical role of alignment for realizing the potential significance of your study. Because the importance of your study is communicated through your evolving research paper, we will fold suggestions for writing your paper into the discussion of creating and executing your study.

We laid the groundwork in Chap. 1 for what we consider to be important research in education:

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 support the improvement of learning opportunities for all students…. If there is no way to imagine a connection to improving learning opportunities for students, even a distant connection, we recommend you reconsider whether it is an important hypothesis within the education community.

Of course, you might prefer another “ultimate purpose” for research in education. That’s fine. The critical point is that the argument for the importance of the hypotheses you are testing should be connected to the value of a long-term goal you can describe. As long as most of the educational community agrees with this goal, and you can show how testing your hypotheses will move the field forward to achieving this goal, you will have developed a convincing argument for the importance of your work.

In Chap. 2 , we argued the importance of your hypotheses can and should be established before you collect data. Your theoretical framework should carry the weight of your argument because it should describe how your hypotheses will extend what is already known. Your methods should then show that you will test your hypotheses in an appropriate way—in a way that will allow you to detect how the results did, and did not, confirm the hypotheses. This will, in turn, allow you to formulate revised hypotheses. We described establishing the importance of your study by saying, “The importance can come from the fact that, based on the results, you will be able to offer revised hypotheses that help the field better understand an issue relevant for improving all students’ learning opportunities.”

The ideas from Chaps. 1 , 2 , and 3 go a long way toward setting the parameters for what counts as an important study and how its importance can be determined. Chapter 4 focused on ensuring that the importance of a study can be realized. The next section fills in the details by proposing definitions for the most common terms used to claim importance: significance, contributions, and implications.

You might notice that we do not have a chapter dedicated to discussing the presentation of the findings—that is, a “results” chapter. We do not mean to imply that presenting results is trivial. However, we believe that if you follow our recommendations for writing your evolving research paper, presenting the results will be quite straightforward. The key is to present your results so they can be most easily compared with your predictions. This means, among other things, organizing your presentation of results according to your earlier presentation of hypotheses.

Part II. Clarifying Importance by Revisiting the Definitions of Key Terms

What does it mean to say your findings are significant? Statistical significance is clear. There are widely accepted standards for determining the statistical significance of findings. But what about educational significance? Is this the same as claiming that your study makes an important contribution? Or, that your study has important implications? Different researchers might answer these questions in different ways. When key terms like these are overused, their definitions gradually broaden or shift, and they can lose their meaning. That is unfortunate, because it creates confusion about how to develop claims for the importance of a study.

By clarifying the definitions, we hope to clarify what is required to claim that a study is significant , that it makes a contribution , and that it has important implications . Not everyone defines the terms as we do. Our definitions are probably a bit narrower or more targeted than those you may encounter elsewhere. Depending on where you want to publish your study, you may want to adapt your use of these terms to match more closely the expectations of a particular journal. But the way we define and address these terms is not antithetical to common uses. And we believe ridding the terms of unnecessary overlap allows us to discriminate among different key concepts with respect to claims for the importance of research studies. It is not necessary to define the terms exactly as we have, but it is critical that the ideas embedded in our definitions be distinguished and that all of them be taken into account when examining the importance of a study.

We will use the following definitions:

Significance: The importance of the problem, questions, and/or hypotheses for improving the learning opportunities for all students (you can substitute a different long-term goal if its value is widely shared). Significance can be determined before data are gathered. Significance is an attribute of the research problem , not the research findings .

Contributions : The value of the findings for revising the hypotheses, making clear what has been learned, what is now better understood.

Implications : Deductions about what can be concluded from the findings that are not already included in “contributions.” The most common deductions in educational research are for improving educational practice. Deductions for research practice that are not already defined as contributions are often suggestions about research methods that are especially useful or methods to avoid.

Significance

The significance of a study is built by formulating research questions and hypotheses you connect through a careful argument to a long-term goal of widely shared value (e.g., improving learning opportunities for all students). Significance applies both to the domain in which your study is located and to your individual study. The significance of the domain is established by choosing a goal of widely shared value and then identifying a domain you can show is connected to achieving the goal. For example, if the goal to which your study contributes is improving the learning opportunities for all students, your study might aim to understand more fully how things work in a domain such as teaching for conceptual understanding, or preparing teachers to attend to all students, or designing curricula to support all learners, or connecting learning opportunities to particular learning outcomes.

The significance of your individual study is something you build ; it is not predetermined or self-evident. Significance of a study is established by making a case for it, not by simply choosing hypotheses everyone already thinks are important. Although you might believe the significance of your study is obvious, readers will need to be convinced.

Significance is something you develop in your evolving research paper. The theoretical framework you present connects your study to what has been investigated previously. Your argument for significance of the domain comes from the significance of the line of research of which your study is a part. The significance of your study is developed by showing, through the presentation of your framework, how your study advances this line of research. This means the lion’s share of your answer to the “So what?” question will be developed as part of your theoretical framework.

Although defining significance as located in your paper prior to presenting results is not a definition universally shared among educational researchers, it is becoming an increasingly common view. In fact, there is movement toward evaluating the significance of a study based only on the first sections of a research paper—the sections prior to the results (Makel et al., 2021 ).

In addition to addressing the “So what?” question, your theoretical framework can address another common concern often voiced by readers: “What is so interesting? I could have predicted those results.” Predictions do not need to be surprising to be interesting and significant. The significance comes from the rationales that show how the predictions extend what is currently known. It is irrelevant how many researchers could have made the predictions. What makes a study significant is that the theoretical framework and the predictions make clear how the study will increase the field’s understanding toward achieving a goal of shared value.

An important consequence of interpreting significance as a carefully developed argument for the importance of your research study within a larger domain is that it reveals the advantage of conducting a series of connected studies rather than single, disconnected studies. Building the significance of a research study requires time and effort. Once you have established significance for a particular study, you can build on this same argument for related studies. This saves time, allows you to continue to refine your argument across studies, and increases the likelihood your studies will contribute to the field.

Contributions

As we have noted, in fields as complicated as education, it is unlikely that your predictions will be entirely accurate. If the problem you are investigating is significant, the hypotheses will be formulated in such a way that they extend a line of research to understand more deeply phenomena related to students’ learning opportunities or another goal of shared value. Often, this means investigating the conditions under which phenomena occur. This gets complicated very quickly, so the data you gather will likely differ from your predictions in a variety of ways. The contributions your study makes will depend on how you interpret these results in light of the original hypotheses.

Contributions Emerge from Revisions to your Hypotheses

We view interpreting results as a process of comparing the data with the predictions and then examining the way in which hypotheses should be revised to more fully account for the results. Revising will almost always be warranted because, as we noted, predictions are unlikely to be entirely accurate. For example, if researchers expect Outcome A to occur under specified conditions but find that it does not occur to the extent predicted or actually does occur but without all the conditions, they must ask what changes to the hypotheses are needed to predict more accurately the conditions under which Outcome A occurred. Are there, for example, essential conditions that were not anticipated and that should be included in the revised hypotheses?

Consider an example from a recently published study (Wang et al., 2021 ). A team of researchers investigated the following research question: “How are students’ perceptions of their parents’ expectations related to students’ mathematics-related beliefs and their perceived mathematics achievement?” The researchers predicted that students’ perceptions of their parents’ expectations would be highly related to students’ mathematics-related beliefs and their perceived mathematics achievement. The rationale was based largely on prior research that had consistently found parents’ general educational expectations to be highly correlated with students’ achievement.

The findings showed that Chinese high school students’ perceptions of their parents’ educational expectations were positively related to these students’ mathematics-related beliefs. In other words, students who believed their parents expected them to attain higher levels of education had more desirable mathematics-related beliefs.

However, students’ perceptions of their parents’ expectations about mathematics achievement were not related to students’ mathematics-related beliefs in the same way as the more general parental educational expectations. Students who reported that their parents had no specific expectations possessed more desirable mathematics-related beliefs than all other subgroups. In addition, these students tended to perceive their mathematics achievement rank in their class to be higher on average than students who reported that their parents expressed some level of expectation for mathematics achievement.

Because this finding was not predicted, the researchers revised the original hypothesis. Their new prediction was that students who believe their parents have no specific mathematics achievement expectations possess more positive mathematics-related beliefs and higher perceived mathematics achievement than students who believe their parents do have specific expectations. They developed a revised rationale that drew on research on parental pressure and mathematics anxiety, positing that parents’ specific mathematics achievement expectations might increase their children’s sense of pressure and anxiety, thus fostering less positive mathematics-related beliefs. The team then conducted a follow-up study. Their findings aligned more closely with the new predictions and affirmed the better explanatory power of the revised rationale. The contributions of the study are found in this increased explanatory power—in the new understandings of this phenomenon contained in the revisions to the rationale.

Interpreting findings in order to revise hypotheses is not a straightforward task. Usually, the rationales blend multiple constructs or variables and predict multiple outcomes, with different outcomes connected to different research questions and addressed by different sets of data. Nevertheless, the contributions of your study depend on specifying the differences between your original hypotheses and your revised hypotheses. What can you explain now that you could not explain before?

We believe that revising hypotheses is an optimal response to any question of contributions because a researcher’s initial hypotheses plus the revisions suggested by the data are the most productive way to tie a study into the larger chain of research of which it is a part. Revised hypotheses represent growth in knowledge. Building on other researchers’ revised hypotheses and revising them further by more explicitly and precisely describing the conditions that are expected to influence the outcomes in the next study accumulates knowledge in a form that can be recorded, shared, built upon, and improved.

The significance of your study is presented in the opening sections of your evolving research paper whereas the contributions are presented in the final section, after the results. In fact, the central focus in this “Discussion” section should be a specification of the contributions (note, though, that this guidance may not fully align with the requirements of some journals).

Contributions Answer the Question of Generalizability

A common and often contentious, confusing issue that can befuddle novice and experienced researchers alike is the generalizability of results. All researchers prefer to believe the results they report apply to more than the sample of participants in their study. How important would a study be if the results applied only to, say, two fourth-grade classrooms in one school, or to the exact same tasks used as measures? How do you decide to which larger population (of students or tasks) your results could generalize? How can you state your claims so they are precisely those justified by the data?

To illustrate the challenge faced by researchers in answering these questions, we return to the JRME reviewers. We found that 30% of the reviews expressed concerns about the match between the results and the claims. For manuscripts that ultimately received a decision of Reject, the majority of reviewers said the authors had overreached—the claims were not supported by the data. In other words, authors generalized their claims beyond those that could be justified.

The Connection Between Contributions and Generalizability

In our view, claims about contributions can be examined productively alongside considerations of generalizability. To make the case for this view, we need to back up a bit. Recall that the purpose of research is to understand a phenomenon. To understand a phenomenon, you need to determine the conditions under which it occurs. Consequently, productive hypotheses specify the conditions under which the predictions hold and explain why and how these conditions make a difference. And the conditions set the parameters on generalizability. They identify when, where, and for whom the effect or situation will occur. So, hypotheses describe the extent of expected generalizability, and revised hypotheses that contain the contributions recalibrate generalizability and offer new predictions within these parameters.

An Example That Illustrates the Connection

In Chap. 4 , we introduced an example with a research question asking whether second graders improve their understanding of place value after a specially designed instructional intervention. We suggested asking a few second and third graders to complete your tasks to see if they generated the expected variation in performance. Suppose you completed this pilot study and now have satisfactory tasks. What conditions might influence the effect of the intervention? After careful study, you developed rationales that supported three conditions: the entry level of students’ understanding, the way in which the intervention is implemented, and the classroom norms that set expectations for students’ participation.

Suppose your original hypotheses predicted the desired effect of the intervention only if the students possessed an understanding of several concepts on which place value is built, only if the intervention was implemented with fidelity to the detailed instructional guidelines, and only if classroom norms encouraged students to participate in small-group work and whole-class discussions. Your claims of generalizability will apply to second-grade settings with these characteristics.

Now suppose you designed the study so the intervention occurred in five second-grade classrooms that agreed to participate. The pre-intervention assessment showed all students with the minimal level of entry understanding. The same well-trained teacher was employed to teach the intervention in all five classrooms, none of which included her own students. And you learned from prior observations and reports of the classroom teachers that three of the classrooms operated with the desired classroom norms, but two did not. Because of these conditions, your study is now designed to test one of your hypotheses—the desired effect will occur only if classroom norms encouraged students to participate in small-group work and whole-class discussions. This is the only condition that will vary; the other two (prior level of understanding and fidelity of implementation) are the same across classrooms so you will not learn how these affect the results.

Suppose the classrooms performed equally well on the post-intervention assessments. You expected lower performance in the two classrooms with less student participation, so you need to revise your hypotheses. The challenge is to explain the higher-than-expected performance of these students. Because you were interested in understanding the effects of this condition, you observed several lessons in all the classrooms during the intervention. You can now use this information to explain why the intervention worked equally well in classrooms with different norms.

Your revised hypothesis captures this part of your study’s contribution. You can now say more about the ways in which the intervention can help students improve their understanding of place value because you have different information about the role of classroom norms. This, in turn, allows you to specify more precisely the nature and extent of the generalizability of your findings. You now can generalize your findings to classrooms with different norms. However, because you did not learn more about the impact of students’ entry level understandings or of different kinds of implementation, the generalizability along these dimensions remains as limited as before.

This example is simplified. In many studies, the findings will be more complicated, and more conditions will likely be identified, some of which were anticipated and some of which emerged while conducting the study and analyzing the data. Nevertheless, the point is that generalizability should be tied to the conditions that are expected to affect the results. Further, unanticipated conditions almost always appear, so generalizations should be conservative and made with caution and humility. They are likely to change after testing the new predictions.

Contributions Are Assured When Hypotheses Are Significant and Methods Are Appropriate and Aligned

We have argued that the contributions of your study are produced by the revised hypotheses you can formulate based on your results. Will these revisions always represent contributions to the field? What if the revisions are minor? What if your results do not inform revisions to your hypotheses?

We will answer these questions briefly now and then develop them further in Part IV of this chapter. The answer to the primary question is “yes,” your revisions will always be a contribution to the field if (1) your hypotheses are significant and (2) you crafted appropriate methods to test the hypotheses. This is true even if your revisions are minor or if your data are not as informative as you expected. However, this is true only if you meet the two conditions in the earlier sentence. The first condition (significant hypotheses) can be satisfied by following the suggestions in the earlier section on significance. The second condition (appropriate methods) is addressed further in Part III in this chapter.

Implications

Before examining the role of methods in connecting significance with important contributions, we elaborate briefly our definition of “implications.” We reserve implications for the conclusions you can logically deduce from your findings that are not already presented as contributions. This means that, like contributions, implications are presented in the Discussion section of your research paper.

Many educational researchers present two types of implications: implications for future research and implications for practice. Although we are aware of this common usage, we believe our definition of “contributions” cover these implications. Clarifying why we call these “contributions” will explain why we largely reserve the word “implications” for recommendations regarding methods.

Implications for Future Research

Implications for future research often include (1) recommendations for empirical studies that would extend the findings of this study, (2) inferences about the usefulness of theoretical constructs, and (3) conclusions about the advisability of using particular kinds of methods. Given our earlier definitions, we prefer to label the first two types of implications as contributions.

Consider recommendations for empirical studies. After analyzing the data and presenting the results, we have suggested you compare the results with those predicted, revise the rationales for the original predictions to account for the results, and make new predictions based on the revised rationales. It is precisely these new predictions that can form the basis for recommending future research. Testing these new predictions is what would most productively extend this line of research. It can sometimes sound as if researchers are recommending future studies based on hunches about what research might yield useful findings. But researchers can do better than this. It would be more productive to base recommendations on a careful analysis of how the predictions of the original study could be sharpened and improved.

Now consider inferences about the usefulness of theoretical constructs. Our argument for labeling these inferences as contributions is similar. Rationales for predictions are where the relevant theoretical constructs are located. Revisions to these rationales based on the differences between the results and the predictions reveal the theoretical constructs that were affirmed to support accurate predictions and those that must be revised. In our view, usefulness is determined through this revision process.

Implications that do not come under our meaning of contributions are in the third type of implications, namely the appropriateness of methods for generating rich contributions. These kinds of implications are produced by your evaluation of your methods: research design, sampling procedures, tasks, data collection procedures, and data analyses. Although not always included in the discussion of findings, we believe it would be helpful for researchers to identify particular methods that were useful for conducting their study and those that should be modified or avoided. We believe these are appropriately called implications.

Implications for Practice

If the purpose of research is to better understand how to improve learning opportunities for all students, then it is appropriate to consider whether implications for improving educational practice can be drawn from the results of a study. How are these implications formulated? This is an important question because, in our view, these claims often come across as an afterthought, “Oh, I need to add some implications for practice.” But here is the sobering reality facing researchers: By any measure, the history of educational research shows that identifying these implications has had little positive effect on practice.

Perhaps the most challenging task for researchers who attempt to draw implications for practice is to interpret their findings for appropriate settings. A researcher who studied the instructional intervention for second graders on place value and found that average performance in the intervention classrooms improved more than in the textbook classrooms might be tempted to draw implications for practice. What should the researcher say? That second-grade teachers should adopt the intervention? Such an implication would be an overreach because, as we noted earlier, the findings cannot be generalized to all second-grade classrooms. Moreover, an improvement in average performance does not mean the intervention was better for all students.

The challenge is to identify the conditions under which the intervention would improve the learning opportunities for all students. Some of these conditions will be identified as the theoretical framework is built because the predictions need to account for these conditions. But some will be unforeseen, and some that are identified will not be informed by the findings. Recall that, in the study described earlier, a condition of entry level of understanding was hypothesized but the design of the study did not allow the researcher to draw any conclusions about its effect.

What can researchers say about implications for practice given the complexities involved in generalizing findings to other settings? We offer two recommendations. First, because it is difficult to specify all the conditions under which a phenomenon occurs, it is rarely appropriate to prescribe an educational practice. Researchers cannot anticipate the conditions under which individual teachers operate, conditions that often require adaptation of a suggested practice rather than implementation of a practice as prescribed.

Our second recommendation comes from returning to the purpose for educational research—to understand more fully how to improve learning opportunities for all students (or to achieve another goal of widely shared value). As we have described, understanding comes primarily from building and reevaluating rationales for your predictions. If you reach a new understanding related to improving learning opportunities, an understanding that could have practical implications, we recommend you share this understanding as an implication for practice.

For example, suppose the researcher who found better average performance of second graders after the intervention on place value had also studied several conditions under which performance improved. And suppose the researcher found that most students who did not improve their performance misunderstood a concept that appeared early in the intervention (e.g., the multiplicative relationship between positional values of a numeral). An implication for practice the researcher might share would be to describe the potential importance of understanding this concept early in the sequence of activities if teachers try out this intervention.

If you use our definitions, these implications for practice would be presented as contributions because they emerge directly from reevaluating and revising your rationales. We believe it is appropriate to use “Contributions” as the heading for this section in the Discussion section of your research paper. However, if editors prefer “Implications” we recommend following their suggestion.

We want to be clear that the terms you use for the different ways your study is important is not critical. We chose to define the terms significance, contributions, and implications in very specific and not universally shared ways to distinguish all the meanings of importance you should consider. Some of these can be established through your theoretical framework, some by the revisions of your hypotheses, and some by reflecting on the value of particular methods. The important thing, from our point of view, is that the ideas we defined for each of these terms are distinguished and recognized as specific ways of determining the importance of your study.

Part III. The Role of Methods in Determining Contributions

We have argued that every part of the study (and of the evolving research paper) should be aligned. All parts should be connected through a coherent chain of reasoning. In this chapter, we argue that the chain of reasoning is not complete until the methods are presented and the results are interpreted and discussed. The methods of the study create a bridge that connects the introductory material (research questions, theoretical framework, literature review, hypotheses) with the results and interpretations.

The role that methods play in scientific inquiry is to ensure that your hypotheses will be tested appropriately so the significance of your study will yield its potential contributions. To do this, the methods must do more than follow the standard guidelines and be technically correct (see Chap. 4 ). They must also fit with the surrounding parts of the study. We call this coherence.

Coherence Across the Phases of Scientific Inquiry

Coherence means the parts of a whole are fully aligned. When doing scientific inquiry, the early parts or phases should motivate the later phases. The methods you use should be motivated or explained by the earlier phases (e.g., research questions, theoretical framework, hypotheses). Your methods, in turn, should produce results that can be interpreted by comparing them with your predictions. Methods are aligned with earlier phases when you can use the rationales contained in your hypotheses to decide what kinds of data are needed to test your predictions, how best to gather these kinds of data, and what analyses should be performed (see Chap. 4 and Cai et al., 2019a ).

For a visual representation of this coherence, see Fig. 5.1 . Each box identifies an aspect of scientific inquiry. Hypotheses (shown in Box 1) include the rationales and predictions. Because the rationales encompass the theoretical framework and the literature review, Box 1 establishes the significance of the study. Box 2 represents the methods, which we defined in Chap. 4 as the entire set of procedures you will use, including the basic design, measures for collecting data, and analytic approaches. In Fig. 5.1 , the hypothesis in Box 1 points you to the methods you will use. That is, you will choose methods that provide data for analyses that will generate results or findings (Box 3) that allow you to make comparisons against your predictions. Based on those comparisons, you will revise your hypotheses and derive the contributions and implications of your study (Box 4).

The Chain of Coherence That Runs Through All Parts of a Research Study

We intend Fig. 5.1 to carry several messages. One is that coherence of a study and the associated research paper require all aspects of the study to flow from one into the other. Each set of prior entries must motivate and justify the next one. For example, the data and analyses you intend to gather and use in Box 2 (Methods) must be those that are motivated and explained by the research question and hypothesis (prediction and rationale) in Box 1.

A second message in the figure is that coherence includes Box 4, “Discussion.” Aligned with the first three boxes, the fourth box flows from these boxes but is also constrained by them. The contributions and implications authors describe in the Discussion section of the paper cannot go beyond what is allowed by the original hypotheses and the revisions to these hypotheses indicated by the findings.

Methods Enable Significance to Yield Contributions

We begin this section by identifying a third message conveyed in Fig. 5.1 . The methods of the study, represented by Box 2, provide a bridge that connects the significance of the study (Box 1) with the contributions of the study (Box 4). The results (Box 3) indicate the nature of the contributions by determining the revisions to the original hypotheses.

In our view, the connecting role played by the methods is often underappreciated. Crafting appropriate methods aligned with the significance of the study, on one hand, and the interpretations, on the other, can determine whether a study is judged to make a contribution.

If the hypotheses are established as significant, and if appropriate methods are used to test the predictions, the study will make important contributions even if the data are not statistically significant. We can say this another way. When researchers establish the significance of the hypotheses (i.e., convince readers they are of interest to the field) and use methods that provide a sound test of these hypotheses, the data they present will be of interest regardless of how they turn out. This is why Makel et al. ( 2021 ) endorse a review process for publication that emphasizes the significance of the study as presented in the first sections of a research paper.

Treating the methods as connecting the introductory arguments to the interpretations of data prevent researchers from making a common mistake: When writing the research paper, some researchers lose track of the research questions and/or the predictions. In other words, results are presented but are not interpreted as answers to the research questions or compared with the predictions. It is as if the introductory material of the paper begins one story, and the interpretations of results ends a different story. Lack of alignment makes it impossible to tell one coherent story.

A final point is that the alignment of a study cannot be evaluated and appreciated if the methods are not fully described. Methods must be described clearly and completely in the research paper so readers can see how they flow from the earlier phases of the study and how they yield the data presented. We suggested in Chap. 4 a rule of thumb for deciding whether the methods have been fully described: “Readers should be able to replicate the study if they wish.”

Part IV. Special Considerations that Affect a Study’s Contributions

We conclude Chap. 5 by addressing two additional issues that can affect how researchers interpret the results and make claims about the contributions of a study. Usually, researchers deal with these issues in the Discussion section of their research paper, but we believe it is useful to consider them as you plan and conduct your study. The issues can be posed as questions: How should I treat the limitations of my study? How should I deal with findings that are completely unexpected?

Limitations of a Study

We can identify two kinds of limitations: (1) limitations that constrain your ability to interpret your results because of unfortunate choices you made, and (2) limitations that constrain your ability to generalize your results because of missing variables you could not fit into the scope of your study or did not anticipate. We recommend different ways of dealing with these.

Limitations Due to Unfortunate Choices

All researchers make unfortunate choices. These are mistakes that could have been prevented. Often, they are choices in how a study was designed and/or executed. Maybe the sample did not have the characteristics assumed, or a task did not assess what was expected, or the intervention was not implemented as planned. Although many unfortunate choices can be prevented by thinking through the consequences of every decision or by conducting a well-designed pilot study or two, some will occur anyway. How should you deal with them?

The consequence of unfortunate choices is that the data do not test the hypotheses as precisely or completely as hoped. When this happens, the data must be interpreted with these constraints in mind. Almost always, this limits the researcher to making fewer or narrower claims than desired about differences and similarities between the results and the predictions. Usually this means conclusions about the ways in which the rationales must be revised require extra qualifications. In other words, claims about contributions of the study must be made with extra caution.

Research papers frequently include a subsection in the Discussion called “Limitations of the Study.” Researchers often use this subsection to identify the study’s limitations by describing the unfortunate choices, but they do not always spell out how these limitations should affect the contributions of the paper. Sometimes, it appears that researchers are simply checking off a requirement to identify the limitations by saying something like “The results should be interpreted with caution.” But this does not help readers understand exactly what cautions should be applied and it does not hold researchers accountable for the limitations.

We recommend something different. We suggest you do the hard work of figuring out how the data should be interpreted in light of the limitations and share these details with the readers. You might do this when the results are presented or when you interpret them. Rather than presenting your claims about the contributions of the study and then saying readers should interpret these with “caution” because of the study’s limitations, we suggest presenting only those interpretations and claims of contributions that can be made with the limitations in mind.

One way to think about the constraints you will likely need to impose on your interpretations is in terms of generalizability. Recall that earlier in this chapter, we described the close relationship between contributions and generalizability. When generalizability is restricted, so are contributions.

Limitations Due to Missing Variables

Because of the complexity of problems, questions, and hypotheses explored in educational research, researchers are unlikely to anticipate in their studies all the variables that affect the data and results. In addition, tradeoffs often must be made. Researchers cannot study everything at once, so decisions must be made about which variables to study carefully and which to either control or ignore.

In the earlier example of studying whether second graders improve their understanding of place value after a specially designed instructional intervention, the researcher identified three variables that were expected to influence the effect of the intervention: students’ entry level of understanding, implementation of the intervention, and norms of the classrooms in which the intervention was implemented. The researcher decided to control the implementation variable by hiring one experienced teacher to implement the intervention in all the classrooms. This meant the variable of individual teacher differences was not included in the study and the researcher could not generalize to classrooms with these differences.

Some researchers might see controlling the implementation of the intervention as a limitation. We do not. As a factor that is not allowed to vary, it constrains the generalizations a researcher can make, but we believe these kinds of controlled variables are better treated as opportunities for future research. Perhaps the researcher’s observations in the classroom provided information that could be used to make some predictions about which elements of the intervention are essential and which are optional—about which aspects of the intervention must be implemented as written and which can vary with different teachers. When revising the rationales to show what was learned in this study, the researcher could include rationales for new, tentative predictions about the effects of the intervention in classrooms where implementation differed in specified ways. These predictions create a genuine contribution of the study. If you use our definitions, these new predictions, often presented under “implications for future research,” would be presented as “contributions.”

Notice that if you follow our advice, you would not need to include a separate section in the Discussion of your paper labeled “Limitations.” We acknowledge, however, that some journal editors recommend such a subsection. In this case, we suggest you include this subsection along with treating the two different kinds of limitations as we recommend. You can do both.

Dealing with Unexpected Findings

Researchers are often faced with unexpected and perhaps surprising results, even when they have developed a convincing theoretical framework, posed research questions tightly connected to this framework, presented predictions about expected outcomes, and selected methods that appropriately test these predictions. Indeed, the unexpected findings can be the most interesting and valuable products of the study. They can range from mildly surprising to “Wow. I didn’t expect that.” How should researchers treat such findings? Our answer is based on two principles.

The first principle is that the value of research does not lie in whether the predictions are completely accurate but in helping the field learn more about the explanatory power of theoretical frameworks. That is, the value lies in the increased understanding of phenomena generated by examining the ability of theoretical frameworks (or rationales) to predict outcomes and explain results. The second principle, a corollary to the first, is to treat unexpected findings in a way that is most educative for the reader.

Based on our arguments to this point, you could guess we will say there will always be unexpected findings. Predicted answers to significant research questions in education will rarely, if ever, be entirely accurate. So, you can count on dealing with unexpected findings.

Consistent with the two principles above, your goal should be to use unexpected findings to understand more fully the phenomenon under investigation. We recommend one of three different paths. The choice of which path to take depends on what you decide after reflecting again on the decisions you made at each phase of the study.

The first path is appropriate when researchers reexamine their theoretical framework in light of the unexpected findings and decide that it is still a compelling framework based on previous work. They reason that readers are likely to have been convinced by this framework and would likely have made similar predictions. In this case, we believe that it is educative for researchers to (a) summarize their initial framework, (b) present the findings and distinguish those that were aligned with the predictions from those that were not, and (c) explain why the theoretical framework was inadequate and propose changes to the framework that would have created more alignment with the unexpected findings.

Revisions to initial hypotheses are especially useful if they include explanations for why a researcher might have been wrong (and researchers who ask significant questions in domains as complex as education are almost always wrong in some way). Depending on the ways in which the revised framework differs from the original, the authors have two options. If the revised framework is an expansion of the original, it would be appropriate for the authors to propose directions for future research that would extend this study. Alternatively, if the revised framework is still largely within the scope of the original study and consists of revisions to the original hypotheses, the revisions could guide a second study to check the adequacy of the revisions. This second study could be conducted by the same researchers (perhaps before the final manuscript is written and presented as two parts of the same report) or it could be proposed in the Discussion as a specific study that could be conducted by other researchers.

The second path is appropriate when researchers reexamine their theoretical framework in light of the unexpected findings and recognize serious flaws in the framework. The flaws could result from a number of factors, including defining elements of the framework in too general a way to formulate well-grounded hypotheses, failing to include a variable, or not accounting carefully enough for the previous work in this domain, both theoretical and empirical. In many of these cases, readers would not be well served by reading a poorly developed framework and then learning that the framework, which had not been convincing, did not accurately predict the results. Before scrapping the study and starting over, we suggest stepping back and reexamining the framework. Is it possible to develop a more coherent, complete, and convincing framework? Would this framework predict the results more accurately? If the findings remain unexpected based on the predictions generated by this revised, more compelling framework, then the first path applies.

It is likely that the new framework will better predict the findings. After all, the researchers now know the findings they will report. However, it is unlikely that the framework will accurately predict all the findings. This is because the framework is not built around the findings of this study of which authors are now aware (but have not yet been presented). Frameworks are built on research and theory already published. This means the redesigned framework is built from exactly the same empirical findings and theoretical arguments available before the study was conducted. The redesigned framework also is constrained by needing to justify exactly those methods used in the study. The redesigned framework cannot justify different methods or even slightly altered methods. The task for researchers is to show how the new theoretical framework necessarily generates, using the same methods, the predictions they present in the research paper. Just as before, it is unlikely this framework can account for all the findings. Just as before, after presenting the results the researchers should explain why they believe particular hypotheses were confirmed and why others should be revised, even in small ways, based on the findings reported. Researchers can now use these findings to revise the hypotheses presented in the paper. The point we are making is that we believe it is acceptable to reconstruct frameworks before writing research reports if doing so would be more educative for the reader.

Finally, the third path becomes appropriate when researchers, in reexamining their theoretical framework, trace the problem to a misalignment between the methods they used and the theoretical framework or the research questions. Perhaps the researchers recognize that the tasks they used did not yield data that could test the predictions and address the research questions. Or perhaps the researchers realize that the sample they selected would likely have been heavily influenced by a factor they failed to take into account. In other words, the researchers decide that the unexpected findings were due to a problem with the methods they used, not with the framework or the accompanying predictions. In this case, we recommend that the researchers correct the methodological problems and conduct the study again.

Part V. A Few Suggestions for Structuring Your Discussion Section

Writing the Discussion section of your research paper can be overwhelming given all our suggestions about what to include in this section. Here are a few tips that might help you create a simple template for this section.

We recommend the Discussion begin with a brief summary of the main results, especially those you will interpret in this section. This summary should not contain new data or results not previously presented in the paper.

The Discussion could then move to presenting the contributions in the ways we have described. To do this you could point out the ways in which the results differed from the predictions and suggest revisions to your rationales that would have better predicted the results. Doing this will show how the contributions of your study extend what is known beyond the research you drew on to build your original rationale. You can then propose how to extend your contributions to research by proposing future research studies that would test your new predictions. If you believe the revisions you make to your rationales produce new insights or understandings that could be helpful for educational practitioners, you can identify these contributions to practice as well. This comprises the bulk of the Discussion section.

If you have embedded the limitations in earlier sections of the paper, you will have presented your results and interpreted your findings constrained by these limitations. If you choose (or are asked) to describe limitations in the Discussion, you could identify the limitations and then point to the ways they affected your interpretations of the findings. Finally, the Discussion could conclude with the implications of the study for methodological choices that could improve research in the domain in which your study is located or how future studies could overcome the limitations you identified.

Because we are providing guidance on writing your research paper for publication, we will reiterate here that you should investigate the expectations and conventions of the journal to which you will submit your paper. Usually, it will be acceptable to use the terms “significance,” “contributions,” and “implications” as we have defined them. However, if the editors expect you to use the terms differently, follow the editors’ expectations. Our definitions in this chapter are meant to help you think clearly about the different ways you can make a case for the importance of your research. What matters is that you have carefully built and described a coherent chain of scientific inquiry that allows your study to translate the significance of your research problem into contributions to the field.

We began the chapter with the “So what?” question. The question looks simple and straightforward but is challenging and complicated. Its simple appearance can lead researchers to believe it should have a simple answer. But it almost never does. In this chapter, we tried to address the many complications that arise when answering the question. We hope you now have some new insights and new tools for answering the question in your next study.

Cai, J., Morris, A., Hohensee, C., Hwang, S., Robison, V., Cirillo, M., Kramer, S. L., & Hiebert, J. (2019a). Choosing and justifying robust methods for educational research. Journal for Research in Mathematics Education, 50 (4), 342–348. https://doi.org/10.5951/jresematheduc.50.2.0114

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Hiebert, J., Cai, J., Hwang, S., Morris, A.K., Hohensee, C. (2023). Significance of a Study: Revisiting the “So What” Question. In: Doing Research: A New Researcher’s Guide. Research in Mathematics Education. Springer, Cham. https://doi.org/10.1007/978-3-031-19078-0_5

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A research problem is a definite or clear expression [statement] about an area of concern, a condition to be improved upon, a difficulty to be eliminated, or a troubling question that exists in scholarly literature, in theory, or within existing practice that points to a need for meaningful understanding and deliberate investigation. A research problem does not state how to do something, offer a vague or broad proposition, or present a value question. In the social and behavioral sciences, studies are most often framed around examining a problem that needs to be understood and resolved in order to improve society and the human condition.

Bryman, Alan. “The Research Question in Social Research: What is its Role?” International Journal of Social Research Methodology 10 (2007): 5-20; Guba, Egon G., and Yvonna S. Lincoln. “Competing Paradigms in Qualitative Research.” In Handbook of Qualitative Research . Norman K. Denzin and Yvonna S. Lincoln, editors. (Thousand Oaks, CA: Sage, 1994), pp. 105-117; Pardede, Parlindungan. “Identifying and Formulating the Research Problem." Research in ELT: Module 4 (October 2018): 1-13; Li, Yanmei, and Sumei Zhang. "Identifying the Research Problem." In Applied Research Methods in Urban and Regional Planning . (Cham, Switzerland: Springer International Publishing, 2022), pp. 13-21.

Importance of...

The purpose of a problem statement is to:

• Introduce the reader to the importance of the topic being studied . The reader is oriented to the significance of the study.
• Anchors the research questions, hypotheses, or assumptions to follow . It offers a concise statement about the purpose of your paper.
• Place the topic into a particular context that defines the parameters of what is to be investigated.
• Provide the framework for reporting the results and indicates what is probably necessary to conduct the study and explain how the findings will present this information.

In the social sciences, the research problem establishes the means by which you must answer the "So What?" question. This declarative question refers to a research problem surviving the relevancy test [the quality of a measurement procedure that provides repeatability and accuracy]. Note that answering the "So What?" question requires a commitment on your part to not only show that you have reviewed the literature, but that you have thoroughly considered the significance of the research problem and its implications applied to creating new knowledge and understanding or informing practice.

To survive the "So What" question, problem statements should possess the following attributes:

• Clarity and precision [a well-written statement does not make sweeping generalizations and irresponsible pronouncements; it also does include unspecific determinates like "very" or "giant"],
• Demonstrate a researchable topic or issue [i.e., feasibility of conducting the study is based upon access to information that can be effectively acquired, gathered, interpreted, synthesized, and understood],
• Identification of what would be studied, while avoiding the use of value-laden words and terms,
• Identification of an overarching question or small set of questions accompanied by key factors or variables,
• Identification of key concepts and terms,
• Articulation of the study's conceptual boundaries or parameters or limitations,
• Some generalizability in regards to applicability and bringing results into general use,
• Conveyance of the study's importance, benefits, and justification [i.e., regardless of the type of research, it is important to demonstrate that the research is not trivial],
• Does not have unnecessary jargon or overly complex sentence constructions; and,
• Conveyance of more than the mere gathering of descriptive data providing only a snapshot of the issue or phenomenon under investigation.

Bryman, Alan. “The Research Question in Social Research: What is its Role?” International Journal of Social Research Methodology 10 (2007): 5-20; Brown, Perry J., Allen Dyer, and Ross S. Whaley. "Recreation Research—So What?" Journal of Leisure Research 5 (1973): 16-24; Castellanos, Susie. Critical Writing and Thinking. The Writing Center. Dean of the College. Brown University; Ellis, Timothy J. and Yair Levy Nova. "Framework of Problem-Based Research: A Guide for Novice Researchers on the Development of a Research-Worthy Problem." Informing Science: the International Journal of an Emerging Transdiscipline 11 (2008); Thesis and Purpose Statements. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Thesis Statements. The Writing Center. University of North Carolina; Tips and Examples for Writing Thesis Statements. The Writing Lab and The OWL. Purdue University; Selwyn, Neil. "‘So What?’…A Question that Every Journal Article Needs to Answer." Learning, Media, and Technology 39 (2014): 1-5; Shoket, Mohd. "Research Problem: Identification and Formulation." International Journal of Research 1 (May 2014): 512-518.

Structure and Writing Style

I.  Types and Content

There are four general conceptualizations of a research problem in the social sciences:

• Casuist Research Problem -- this type of problem relates to the determination of right and wrong in questions of conduct or conscience by analyzing moral dilemmas through the application of general rules and the careful distinction of special cases.
• Difference Research Problem -- typically asks the question, “Is there a difference between two or more groups or treatments?” This type of problem statement is used when the researcher compares or contrasts two or more phenomena. This a common approach to defining a problem in the clinical social sciences or behavioral sciences.
• Descriptive Research Problem -- typically asks the question, "what is...?" with the underlying purpose to describe the significance of a situation, state, or existence of a specific phenomenon. This problem is often associated with revealing hidden or understudied issues.
• Relational Research Problem -- suggests a relationship of some sort between two or more variables to be investigated. The underlying purpose is to investigate specific qualities or characteristics that may be connected in some way.

A problem statement in the social sciences should contain :

• A lead-in that helps ensure the reader will maintain interest over the study,
• A declaration of originality [e.g., mentioning a knowledge void or a lack of clarity about a topic that will be revealed in the literature review of prior research],
• An indication of the central focus of the study [establishing the boundaries of analysis], and
• An explanation of the study's significance or the benefits to be derived from investigating the research problem.

NOTE:   A statement describing the research problem of your paper should not be viewed as a thesis statement that you may be familiar with from high school. Given the content listed above, a description of the research problem is usually a short paragraph in length.

II.  Sources of Problems for Investigation

The identification of a problem to study can be challenging, not because there's a lack of issues that could be investigated, but due to the challenge of formulating an academically relevant and researchable problem which is unique and does not simply duplicate the work of others. To facilitate how you might select a problem from which to build a research study, consider these sources of inspiration:

Deductions from Theory This relates to deductions made from social philosophy or generalizations embodied in life and in society that the researcher is familiar with. These deductions from human behavior are then placed within an empirical frame of reference through research. From a theory, the researcher can formulate a research problem or hypothesis stating the expected findings in certain empirical situations. The research asks the question: “What relationship between variables will be observed if theory aptly summarizes the state of affairs?” One can then design and carry out a systematic investigation to assess whether empirical data confirm or reject the hypothesis, and hence, the theory.

Interdisciplinary Perspectives Identifying a problem that forms the basis for a research study can come from academic movements and scholarship originating in disciplines outside of your primary area of study. This can be an intellectually stimulating exercise. A review of pertinent literature should include examining research from related disciplines that can reveal new avenues of exploration and analysis. An interdisciplinary approach to selecting a research problem offers an opportunity to construct a more comprehensive understanding of a very complex issue that any single discipline may be able to provide.

Interviewing Practitioners The identification of research problems about particular topics can arise from formal interviews or informal discussions with practitioners who provide insight into new directions for future research and how to make research findings more relevant to practice. Discussions with experts in the field, such as, teachers, social workers, health care providers, lawyers, business leaders, etc., offers the chance to identify practical, “real world” problems that may be understudied or ignored within academic circles. This approach also provides some practical knowledge which may help in the process of designing and conducting your study.

Personal Experience Don't undervalue your everyday experiences or encounters as worthwhile problems for investigation. Think critically about your own experiences and/or frustrations with an issue facing society or related to your community, your neighborhood, your family, or your personal life. This can be derived, for example, from deliberate observations of certain relationships for which there is no clear explanation or witnessing an event that appears harmful to a person or group or that is out of the ordinary.

Relevant Literature The selection of a research problem can be derived from a thorough review of pertinent research associated with your overall area of interest. This may reveal where gaps exist in understanding a topic or where an issue has been understudied. Research may be conducted to: 1) fill such gaps in knowledge; 2) evaluate if the methodologies employed in prior studies can be adapted to solve other problems; or, 3) determine if a similar study could be conducted in a different subject area or applied in a different context or to different study sample [i.e., different setting or different group of people]. Also, authors frequently conclude their studies by noting implications for further research; read the conclusion of pertinent studies because statements about further research can be a valuable source for identifying new problems to investigate. The fact that a researcher has identified a topic worthy of further exploration validates the fact it is worth pursuing.

III.  What Makes a Good Research Statement?

A good problem statement begins by introducing the broad area in which your research is centered, gradually leading the reader to the more specific issues you are investigating. The statement need not be lengthy, but a good research problem should incorporate the following features:

1.  Compelling Topic The problem chosen should be one that motivates you to address it but simple curiosity is not a good enough reason to pursue a research study because this does not indicate significance. The problem that you choose to explore must be important to you, but it must also be viewed as important by your readers and to a the larger academic and/or social community that could be impacted by the results of your study. 2.  Supports Multiple Perspectives The problem must be phrased in a way that avoids dichotomies and instead supports the generation and exploration of multiple perspectives. A general rule of thumb in the social sciences is that a good research problem is one that would generate a variety of viewpoints from a composite audience made up of reasonable people. 3.  Researchability This isn't a real word but it represents an important aspect of creating a good research statement. It seems a bit obvious, but you don't want to find yourself in the midst of investigating a complex research project and realize that you don't have enough prior research to draw from for your analysis. There's nothing inherently wrong with original research, but you must choose research problems that can be supported, in some way, by the resources available to you. If you are not sure if something is researchable, don't assume that it isn't if you don't find information right away--seek help from a librarian !

NOTE:   Do not confuse a research problem with a research topic. A topic is something to read and obtain information about, whereas a problem is something to be solved or framed as a question raised for inquiry, consideration, or solution, or explained as a source of perplexity, distress, or vexation. In short, a research topic is something to be understood; a research problem is something that needs to be investigated.

IV.  Asking Analytical Questions about the Research Problem

Research problems in the social and behavioral sciences are often analyzed around critical questions that must be investigated. These questions can be explicitly listed in the introduction [i.e., "This study addresses three research questions about women's psychological recovery from domestic abuse in multi-generational home settings..."], or, the questions are implied in the text as specific areas of study related to the research problem. Explicitly listing your research questions at the end of your introduction can help in designing a clear roadmap of what you plan to address in your study, whereas, implicitly integrating them into the text of the introduction allows you to create a more compelling narrative around the key issues under investigation. Either approach is appropriate.

The number of questions you attempt to address should be based on the complexity of the problem you are investigating and what areas of inquiry you find most critical to study. Practical considerations, such as, the length of the paper you are writing or the availability of resources to analyze the issue can also factor in how many questions to ask. In general, however, there should be no more than four research questions underpinning a single research problem.

Given this, well-developed analytical questions can focus on any of the following:

• Highlights a genuine dilemma, area of ambiguity, or point of confusion about a topic open to interpretation by your readers;
• Yields an answer that is unexpected and not obvious rather than inevitable and self-evident;
• Provokes meaningful thought or discussion;
• Raises the visibility of the key ideas or concepts that may be understudied or hidden;
• Suggests the need for complex analysis or argument rather than a basic description or summary; and,
• Offers a specific path of inquiry that avoids eliciting generalizations about the problem.

NOTE:   Questions of how and why concerning a research problem often require more analysis than questions about who, what, where, and when. You should still ask yourself these latter questions, however. Thinking introspectively about the who, what, where, and when of a research problem can help ensure that you have thoroughly considered all aspects of the problem under investigation and helps define the scope of the study in relation to the problem.

V.  Mistakes to Avoid

Beware of circular reasoning! Do not state the research problem as simply the absence of the thing you are suggesting. For example, if you propose the following, "The problem in this community is that there is no hospital," this only leads to a research problem where:

• The need is for a hospital
• The objective is to create a hospital
• The method is to plan for building a hospital, and
• The evaluation is to measure if there is a hospital or not.

This is an example of a research problem that fails the "So What?" test . In this example, the problem does not reveal the relevance of why you are investigating the fact there is no hospital in the community [e.g., perhaps there's a hospital in the community ten miles away]; it does not elucidate the significance of why one should study the fact there is no hospital in the community [e.g., that hospital in the community ten miles away has no emergency room]; the research problem does not offer an intellectual pathway towards adding new knowledge or clarifying prior knowledge [e.g., the county in which there is no hospital already conducted a study about the need for a hospital, but it was conducted ten years ago]; and, the problem does not offer meaningful outcomes that lead to recommendations that can be generalized for other situations or that could suggest areas for further research [e.g., the challenges of building a new hospital serves as a case study for other communities].

Alvesson, Mats and Jörgen Sandberg. “Generating Research Questions Through Problematization.” Academy of Management Review 36 (April 2011): 247-271 ; Choosing and Refining Topics. Writing@CSU. Colorado State University; D'Souza, Victor S. "Use of Induction and Deduction in Research in Social Sciences: An Illustration." Journal of the Indian Law Institute 24 (1982): 655-661; Ellis, Timothy J. and Yair Levy Nova. "Framework of Problem-Based Research: A Guide for Novice Researchers on the Development of a Research-Worthy Problem." Informing Science: the International Journal of an Emerging Transdiscipline 11 (2008); How to Write a Research Question. The Writing Center. George Mason University; Invention: Developing a Thesis Statement. The Reading/Writing Center. Hunter College; Problem Statements PowerPoint Presentation. The Writing Lab and The OWL. Purdue University; Procter, Margaret. Using Thesis Statements. University College Writing Centre. University of Toronto; Shoket, Mohd. "Research Problem: Identification and Formulation." International Journal of Research 1 (May 2014): 512-518; Trochim, William M.K. Problem Formulation. Research Methods Knowledge Base. 2006; Thesis and Purpose Statements. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Thesis Statements. The Writing Center. University of North Carolina; Tips and Examples for Writing Thesis Statements. The Writing Lab and The OWL. Purdue University; Pardede, Parlindungan. “Identifying and Formulating the Research Problem." Research in ELT: Module 4 (October 2018): 1-13; Walk, Kerry. Asking an Analytical Question. [Class handout or worksheet]. Princeton University; White, Patrick. Developing Research Questions: A Guide for Social Scientists . New York: Palgrave McMillan, 2009; Li, Yanmei, and Sumei Zhang. "Identifying the Research Problem." In Applied Research Methods in Urban and Regional Planning . (Cham, Switzerland: Springer International Publishing, 2022), pp. 13-21.

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• J Indian Assoc Pediatr Surg
• v.24(1); Jan-Mar 2019

Formulation of Research Question – Stepwise Approach

Simmi k. ratan.

Department of Pediatric Surgery, Maulana Azad Medical College, New Delhi, India

1 Department of Community Medicine, North Delhi Municipal Corporation Medical College, New Delhi, India

2 Department of Pediatric Surgery, Batra Hospital and Research Centre, New Delhi, India

Formulation of research question (RQ) is an essentiality before starting any research. It aims to explore an existing uncertainty in an area of concern and points to a need for deliberate investigation. It is, therefore, pertinent to formulate a good RQ. The present paper aims to discuss the process of formulation of RQ with stepwise approach. The characteristics of good RQ are expressed by acronym “FINERMAPS” expanded as feasible, interesting, novel, ethical, relevant, manageable, appropriate, potential value, publishability, and systematic. A RQ can address different formats depending on the aspect to be evaluated. Based on this, there can be different types of RQ such as based on the existence of the phenomenon, description and classification, composition, relationship, comparative, and causality. To develop a RQ, one needs to begin by identifying the subject of interest and then do preliminary research on that subject. The researcher then defines what still needs to be known in that particular subject and assesses the implied questions. After narrowing the focus and scope of the research subject, researcher frames a RQ and then evaluates it. Thus, conception to formulation of RQ is very systematic process and has to be performed meticulously as research guided by such question can have wider impact in the field of social and health research by leading to formulation of policies for the benefit of larger population.

I NTRODUCTION

A good research question (RQ) forms backbone of a good research, which in turn is vital in unraveling mysteries of nature and giving insight into a problem.[ 1 , 2 , 3 , 4 ] RQ identifies the problem to be studied and guides to the methodology. It leads to building up of an appropriate hypothesis (Hs). Hence, RQ aims to explore an existing uncertainty in an area of concern and points to a need for deliberate investigation. A good RQ helps support a focused arguable thesis and construction of a logical argument. Hence, formulation of a good RQ is undoubtedly one of the first critical steps in the research process, especially in the field of social and health research, where the systematic generation of knowledge that can be used to promote, restore, maintain, and/or protect health of individuals and populations.[ 1 , 3 , 4 ] Basically, the research can be classified as action, applied, basic, clinical, empirical, administrative, theoretical, or qualitative or quantitative research, depending on its purpose.[ 2 ]

Research plays an important role in developing clinical practices and instituting new health policies. Hence, there is a need for a logical scientific approach as research has an important goal of generating new claims.[ 1 ]

C HARACTERISTICS OF G OOD R ESEARCH Q UESTION

“The most successful research topics are narrowly focused and carefully defined but are important parts of a broad-ranging, complex problem.”

A good RQ is an asset as it:

• Details the problem statement
• Further describes and refines the issue under study
• Adds focus to the problem statement
• Guides data collection and analysis
• Sets context of research.

Hence, while writing RQ, it is important to see if it is relevant to the existing time frame and conditions. For example, the impact of “odd-even” vehicle formula in decreasing the level of air particulate pollution in various districts of Delhi.

A good research is represented by acronym FINERMAPS[ 5 ]

Interesting.

• Appropriate
• Potential value and publishability
• Systematic.

Feasibility means that it is within the ability of the investigator to carry out. It should be backed by an appropriate number of subjects and methodology as well as time and funds to reach the conclusions. One needs to be realistic about the scope and scale of the project. One has to have access to the people, gadgets, documents, statistics, etc. One should be able to relate the concepts of the RQ to the observations, phenomena, indicators, or variables that one can access. One should be clear that the collection of data and the proceedings of project can be completed within the limited time and resources available to the investigator. Sometimes, a RQ appears feasible, but when fieldwork or study gets started, it proves otherwise. In this situation, it is important to write up the problems honestly and to reflect on what has been learned. One should try to discuss with more experienced colleagues or the supervisor so as to develop a contingency plan to anticipate possible problems while working on a RQ and find possible solutions in such situations.

This is essential that one has a real grounded interest in one's RQ and one can explore this and back it up with academic and intellectual debate. This interest will motivate one to keep going with RQ.

The question should not simply copy questions investigated by other workers but should have scope to be investigated. It may aim at confirming or refuting the already established findings, establish new facts, or find new aspects of the established facts. It should show imagination of the researcher. Above all, the question has to be simple and clear. The complexity of a question can frequently hide unclear thoughts and lead to a confused research process. A very elaborate RQ, or a question which is not differentiated into different parts, may hide concepts that are contradictory or not relevant. This needs to be clear and thought-through. Having one key question with several subcomponents will guide your research.

This is the foremost requirement of any RQ and is mandatory to get clearance from appropriate authorities before stating research on the question. Further, the RQ should be such that it minimizes the risk of harm to the participants in the research, protect the privacy and maintain their confidentiality, and provide the participants right to withdraw from research. It should also guide in avoiding deceptive practices in research.

The question should of academic and intellectual interest to people in the field you have chosen to study. The question preferably should arise from issues raised in the current situation, literature, or in practice. It should establish a clear purpose for the research in relation to the chosen field. For example, filling a gap in knowledge, analyzing academic assumptions or professional practice, monitoring a development in practice, comparing different approaches, or testing theories within a specific population are some of the relevant RQs.

Manageable (M): It has the similar essence as of feasibility but mainly means that the following research can be managed by the researcher.

Appropriate (A): RQ should be appropriate logically and scientifically for the community and institution.

Potential value and publishability (P): The study can make significant health impact in clinical and community practices. Therefore, research should aim for significant economic impact to reduce unnecessary or excessive costs. Furthermore, the proposed study should exist within a clinical, consumer, or policy-making context that is amenable to evidence-based change. Above all, a good RQ must address a topic that has clear implications for resolving important dilemmas in health and health-care decisions made by one or more stakeholder groups.

Systematic (S): Research is structured with specified steps to be taken in a specified sequence in accordance with the well-defined set of rules though it does not rule out creative thinking.

Example of RQ: Would the topical skin application of oil as a skin barrier reduces hypothermia in preterm infants? This question fulfills the criteria of a good RQ, that is, feasible, interesting, novel, ethical, and relevant.

Types of research question

A RQ can address different formats depending on the aspect to be evaluated.[ 6 ] For example:

• Existence: This is designed to uphold the existence of a particular phenomenon or to rule out rival explanation, for example, can neonates perceive pain?
• Description and classification: This type of question encompasses statement of uniqueness, for example, what are characteristics and types of neuropathic bladders?
• Composition: It calls for breakdown of whole into components, for example, what are stages of reflux nephropathy?
• Relationship: Evaluate relation between variables, for example, association between tumor rupture and recurrence rates in Wilm's tumor
• Descriptive—comparative: Expected that researcher will ensure that all is same between groups except issue in question, for example, Are germ cell tumors occurring in gonads more aggressive than those occurring in extragonadal sites?
• Causality: Does deletion of p53 leads to worse outcome in patients with neuroblastoma?
• Causality—comparative: Such questions frequently aim to see effect of two rival treatments, for example, does adding surgical resection improves survival rate outcome in children with neuroblastoma than with chemotherapy alone?
• Causality–Comparative interactions: Does immunotherapy leads to better survival outcome in neuroblastoma Stage IV S than with chemotherapy in the setting of adverse genetic profile than without it? (Does X cause more changes in Y than those caused by Z under certain condition and not under other conditions).

How to develop a research question

• Begin by identifying a broader subject of interest that lends itself to investigate, for example, hormone levels among hypospadias
• Do preliminary research on the general topic to find out what research has already been done and what literature already exists.[ 7 ] Therefore, one should begin with “information gaps” (What do you already know about the problem? For example, studies with results on testosterone levels among hypospadias
• What do you still need to know? (e.g., levels of other reproductive hormones among hypospadias)
• What are the implied questions: The need to know about a problem will lead to few implied questions. Each general question should lead to more specific questions (e.g., how hormone levels differ among isolated hypospadias with respect to that in normal population)
• Narrow the scope and focus of research (e.g., assessment of reproductive hormone levels among isolated hypospadias and hypospadias those with associated anomalies)
• Is RQ clear? With so much research available on any given topic, RQs must be as clear as possible in order to be effective in helping the writer direct his or her research
• Is the RQ focused? RQs must be specific enough to be well covered in the space available
• Is the RQ complex? RQs should not be answerable with a simple “yes” or “no” or by easily found facts. They should, instead, require both research and analysis on the part of the writer
• Is the RQ one that is of interest to the researcher and potentially useful to others? Is it a new issue or problem that needs to be solved or is it attempting to shed light on previously researched topic
• Is the RQ researchable? Consider the available time frame and the required resources. Is the methodology to conduct the research feasible?
• Is the RQ measurable and will the process produce data that can be supported or contradicted?
• Is the RQ too broad or too narrow?
• Create Hs: After formulating RQ, think where research is likely to be progressing? What kind of argument is likely to be made/supported? What would it mean if the research disputed the planned argument? At this step, one can well be on the way to have a focus for the research and construction of a thesis. Hs consists of more specific predictions about the nature and direction of the relationship between two variables. It is a predictive statement about the outcome of the research, dictate the method, and design of the research[ 1 ]
• Understand implications of your research: This is important for application: whether one achieves to fill gap in knowledge and how the results of the research have practical implications, for example, to develop health policies or improve educational policies.[ 1 , 8 ]

Brainstorm/Concept map for formulating research question

• First, identify what types of studies have been done in the past?
• Is there a unique area that is yet to be investigated or is there a particular question that may be worth replicating?
• Begin to narrow the topic by asking open-ended “how” and “why” questions
• Evaluate the question
• Develop a Hypothesis (Hs)
• Write down the RQ.

Writing down the research question

• State the question in your own words
• Write down the RQ as completely as possible.

For example, Evaluation of reproductive hormonal profile in children presenting with isolated hypospadias)

• Divide your question into concepts. Narrow to two or three concepts (reproductive hormonal profile, isolated hypospadias, compare with normal/not isolated hypospadias–implied)
• Specify the population to be studied (children with isolated hypospadias)
• Refer to the exposure or intervention to be investigated, if any
• Reflect the outcome of interest (hormonal profile).

Another example of a research question

Would the topical skin application of oil as a skin barrier reduces hypothermia in preterm infants? Apart from fulfilling the criteria of a good RQ, that is, feasible, interesting, novel, ethical, and relevant, it also details about the intervention done (topical skin application of oil), rationale of intervention (as a skin barrier), population to be studied (preterm infants), and outcome (reduces hypothermia).

Other important points to be heeded to while framing research question

• Make reference to a population when a relationship is expected among a certain type of subjects
• RQs and Hs should be made as specific as possible
• Avoid words or terms that do not add to the meaning of RQs and Hs
• Stick to what will be studied, not implications
• Name the variables in the order in which they occur/will be measured
• Avoid the words significant/”prove”
• Avoid using two different terms to refer to the same variable.

Some of the other problems and their possible solutions have been discussed in Table 1 .

Potential problems and solutions while making research question

G OING B EYOND F ORMULATION OF R ESEARCH Q UESTION–THE P ATH A HEAD

Once RQ is formulated, a Hs can be developed. Hs means transformation of a RQ into an operational analog.[ 1 ] It means a statement as to what prediction one makes about the phenomenon to be examined.[ 4 ] More often, for case–control trial, null Hs is generated which is later accepted or refuted.

A strong Hs should have following characteristics:

• Give insight into a RQ
• Are testable and measurable by the proposed experiments
• Have logical basis
• Follows the most likely outcome, not the exceptional outcome.

E XAMPLES OF R ESEARCH Q UESTION AND H YPOTHESIS

Research question-1.

• Does reduced gap between the two segments of the esophagus in patients of esophageal atresia reduces the mortality and morbidity of such patients?

Hypothesis-1

• Reduced gap between the two segments of the esophagus in patients of esophageal atresia reduces the mortality and morbidity of such patients
• In pediatric patients with esophageal atresia, gap of <2 cm between two segments of the esophagus and proper mobilization of proximal pouch reduces the morbidity and mortality among such patients.

Research question-2

• Does application of mitomycin C improves the outcome in patient of corrosive esophageal strictures?

Hypothesis-2

In patients aged 2–9 years with corrosive esophageal strictures, 34 applications of mitomycin C in dosage of 0.4 mg/ml for 5 min over a period of 6 months improve the outcome in terms of symptomatic and radiological relief. Some other examples of good and bad RQs have been shown in Table 2 .

Examples of few bad (left-hand side column) and few good (right-hand side) research questions

R ESEARCH Q UESTION AND S TUDY D ESIGN

RQ determines study design, for example, the question aimed to find the incidence of a disease in population will lead to conducting a survey; to find risk factors for a disease will need case–control study or a cohort study. RQ may also culminate into clinical trial.[ 9 , 10 ] For example, effect of administration of folic acid tablet in the perinatal period in decreasing incidence of neural tube defect. Accordingly, Hs is framed.

Appropriate statistical calculations are instituted to generate sample size. The subject inclusion, exclusion criteria and time frame of research are carefully defined. The detailed subject information sheet and pro forma are carefully defined. Moreover, research is set off few examples of research methodology guided by RQ:

• Incidence of anorectal malformations among adolescent females (hospital-based survey)
• Risk factors for the development of spontaneous pneumoperitoneum in pediatric patients (case–control design and cohort study)
• Effect of technique of extramucosal ureteric reimplantation without the creation of submucosal tunnel for the preservation of upper tract in bladder exstrophy (clinical trial).

The results of the research are then be available for wider applications for health and social life

C ONCLUSION

A good RQ needs thorough literature search and deep insight into the specific area/problem to be investigated. A RQ has to be focused yet simple. Research guided by such question can have wider impact in the field of social and health research by leading to formulation of policies for the benefit of larger population.

Financial support and sponsorship

Conflicts of interest.

There are no conflicts of interest.

R EFERENCES

Research Aims, Objectives & Questions

By: David Phair (PhD) and Alexandra Shaeffer (PhD) | June 2022

T he research aims , objectives and research questions (collectively called the “golden thread”) are arguably the most important thing you need to get right when you’re crafting a research proposal , dissertation or thesis . We receive questions almost every day about this “holy trinity” of research and there’s certainly a lot of confusion out there, so we’ve crafted this post to help you navigate your way through the fog.

Overview: The Golden Thread

• What is the golden thread
• What are research aims ( examples )
• What are research objectives ( examples )
• What are research questions ( examples )
• The importance of alignment in the golden thread

What is the “golden thread”?

The golden thread simply refers to the collective research aims , research objectives , and research questions for any given project (i.e., a dissertation, thesis, or research paper ). These three elements are bundled together because it’s extremely important that they align with each other, and that the entire research project aligns with them.

Importantly, the golden thread needs to weave its way through the entirety of any research project , from start to end. In other words, it needs to be very clearly defined right at the beginning of the project (the topic ideation and proposal stage) and it needs to inform almost every decision throughout the rest of the project. For example, your research design and methodology will be heavily influenced by the golden thread (we’ll explain this in more detail later), as well as your literature review.

The research aims, objectives and research questions (the golden thread) define the focus and scope ( the delimitations ) of your research project. In other words, they help ringfence your dissertation or thesis to a relatively narrow domain, so that you can “go deep” and really dig into a specific problem or opportunity. They also help keep you on track , as they act as a litmus test for relevance. In other words, if you’re ever unsure whether to include something in your document, simply ask yourself the question, “does this contribute toward my research aims, objectives or questions?”. If it doesn’t, chances are you can drop it.

Alright, enough of the fluffy, conceptual stuff. Let’s get down to business and look at what exactly the research aims, objectives and questions are and outline a few examples to bring these concepts to life.

Research Aims: What are they?

Simply put, the research aim(s) is a statement that reflects the broad overarching goal (s) of the research project. Research aims are fairly high-level (low resolution) as they outline the general direction of the research and what it’s trying to achieve .

Research Aims: Examples

True to the name, research aims usually start with the wording “this research aims to…”, “this research seeks to…”, and so on. For example:

“This research aims to explore employee experiences of digital transformation in retail HR.”   “This study sets out to assess the interaction between student support and self-care on well-being in engineering graduate students”  

As you can see, these research aims provide a high-level description of what the study is about and what it seeks to achieve. They’re not hyper-specific or action-oriented, but they’re clear about what the study’s focus is and what is being investigated.

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Research Objectives: What are they?

The research objectives take the research aims and make them more practical and actionable . In other words, the research objectives showcase the steps that the researcher will take to achieve the research aims.

The research objectives need to be far more specific (higher resolution) and actionable than the research aims. In fact, it’s always a good idea to craft your research objectives using the “SMART” criteria. In other words, they should be specific, measurable, achievable, relevant and time-bound”.

Research Objectives: Examples

Let’s look at two examples of research objectives. We’ll stick with the topic and research aims we mentioned previously.  

For the digital transformation topic:

To observe the retail HR employees throughout the digital transformation. To assess employee perceptions of digital transformation in retail HR. To identify the barriers and facilitators of digital transformation in retail HR.

And for the student wellness topic:

To determine whether student self-care predicts the well-being score of engineering graduate students. To determine whether student support predicts the well-being score of engineering students. To assess the interaction between student self-care and student support when predicting well-being in engineering graduate students.

  As you can see, these research objectives clearly align with the previously mentioned research aims and effectively translate the low-resolution aims into (comparatively) higher-resolution objectives and action points . They give the research project a clear focus and present something that resembles a research-based “to-do” list.

Research Questions: What are they?

Finally, we arrive at the all-important research questions. The research questions are, as the name suggests, the key questions that your study will seek to answer . Simply put, they are the core purpose of your dissertation, thesis, or research project. You’ll present them at the beginning of your document (either in the introduction chapter or literature review chapter) and you’ll answer them at the end of your document (typically in the discussion and conclusion chapters).

The research questions will be the driving force throughout the research process. For example, in the literature review chapter, you’ll assess the relevance of any given resource based on whether it helps you move towards answering your research questions. Similarly, your methodology and research design will be heavily influenced by the nature of your research questions. For instance, research questions that are exploratory in nature will usually make use of a qualitative approach, whereas questions that relate to measurement or relationship testing will make use of a quantitative approach.  

Let’s look at some examples of research questions to make this more tangible.

Research Questions: Examples 

Again, we’ll stick with the research aims and research objectives we mentioned previously.  

For the digital transformation topic (which would be qualitative in nature):

How do employees perceive digital transformation in retail HR? What are the barriers and facilitators of digital transformation in retail HR?  

And for the student wellness topic (which would be quantitative in nature):

Does student self-care predict the well-being scores of engineering graduate students? Does student support predict the well-being scores of engineering students? Do student self-care and student support interact when predicting well-being in engineering graduate students?  

You’ll probably notice that there’s quite a formulaic approach to this. In other words, the research questions are basically the research objectives “converted” into question format. While that is true most of the time, it’s not always the case. For example, the first research objective for the digital transformation topic was more or less a step on the path toward the other objectives, and as such, it didn’t warrant its own research question.

So, don’t rush your research questions and sloppily reword your objectives as questions. Carefully think about what exactly you’re trying to achieve (i.e. your research aim) and the objectives you’ve set out, then craft a set of well-aligned research questions . Also, keep in mind that this can be a somewhat iterative process , where you go back and tweak research objectives and aims to ensure tight alignment throughout the golden thread.

The importance of strong alignment

Alignment is the keyword here and we have to stress its importance . Simply put, you need to make sure that there is a very tight alignment between all three pieces of the golden thread. If your research aims and research questions don’t align, for example, your project will be pulling in different directions and will lack focus . This is a common problem students face and can cause many headaches (and tears), so be warned.

Take the time to carefully craft your research aims, objectives and research questions before you run off down the research path. Ideally, get your research supervisor/advisor to review and comment on your golden thread before you invest significant time into your project, and certainly before you start collecting data .  

Recap: The golden thread

In this post, we unpacked the golden thread of research, consisting of the research aims , research objectives and research questions . You can jump back to any section using the links below.

As always, feel free to leave a comment below – we always love to hear from you. Also, if you’re interested in 1-on-1 support, take a look at our private coaching service here.

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41 Comments

Thank you very much for your great effort put. As an Undergraduate taking Demographic Research & Methodology, I’ve been trying so hard to understand clearly what is a Research Question, Research Aim and the Objectives in a research and the relationship between them etc. But as for now I’m thankful that you’ve solved my problem.

Well appreciated. This has helped me greatly in doing my dissertation.

An so delighted with this wonderful information thank you a lot.

so impressive i have benefited a lot looking forward to learn more on research.

I am very happy to have carefully gone through this well researched article.

Infact,I used to be phobia about anything research, because of my poor understanding of the concepts.

Now,I get to know that my research question is the same as my research objective(s) rephrased in question format.

I please I would need a follow up on the subject,as I intends to join the team of researchers. Thanks once again.

Thanks so much. This was really helpful.

I know you pepole have tried to break things into more understandable and easy format. And God bless you. Keep it up

i found this document so useful towards my study in research methods. thanks so much.

This is my 2nd read topic in your course and I should commend the simplified explanations of each part. I’m beginning to understand and absorb the use of each part of a dissertation/thesis. I’ll keep on reading your free course and might be able to avail the training course! Kudos!

Thank you! Better put that my lecture and helped to easily understand the basics which I feel often get brushed over when beginning dissertation work.

This is quite helpful. I like how the Golden thread has been explained and the needed alignment.

This is quite helpful. I really appreciate!

The article made it simple for researcher students to differentiate between three concepts.

Very innovative and educational in approach to conducting research.

I am very impressed with all these terminology, as I am a fresh student for post graduate, I am highly guided and I promised to continue making consultation when the need arise. Thanks a lot.

A very helpful piece. thanks, I really appreciate it .

Very well explained, and it might be helpful to many people like me.

Wish i had found this (and other) resource(s) at the beginning of my PhD journey… not in my writing up year… 😩 Anyways… just a quick question as i’m having some issues ordering my “golden thread”…. does it matter in what order you mention them? i.e., is it always first aims, then objectives, and finally the questions? or can you first mention the research questions and then the aims and objectives?

Thank you for a very simple explanation that builds upon the concepts in a very logical manner. Just prior to this, I read the research hypothesis article, which was equally very good. This met my primary objective.

My secondary objective was to understand the difference between research questions and research hypothesis, and in which context to use which one. However, I am still not clear on this. Can you kindly please guide?

In research, a research question is a clear and specific inquiry that the researcher wants to answer, while a research hypothesis is a tentative statement or prediction about the relationship between variables or the expected outcome of the study. Research questions are broader and guide the overall study, while hypotheses are specific and testable statements used in quantitative research. Research questions identify the problem, while hypotheses provide a focus for testing in the study.

Exactly what I need in this research journey, I look forward to more of your coaching videos.

This helped a lot. Thanks so much for the effort put into explaining it.

What data source in writing dissertation/Thesis requires?

What is data source covers when writing dessertation/thesis

This is quite useful thanks

I’m excited and thankful. I got so much value which will help me progress in my thesis.

where are the locations of the reserch statement, research objective and research question in a reserach paper? Can you write an ouline that defines their places in the researh paper?

Very helpful and important tips on Aims, Objectives and Questions.

Thank you so much for making research aim, research objectives and research question so clear. This will be helpful to me as i continue with my thesis.

Thanks much for this content. I learned a lot. And I am inspired to learn more. I am still struggling with my preparation for dissertation outline/proposal. But I consistently follow contents and tutorials and the new FB of GRAD Coach. Hope to really become confident in writing my dissertation and successfully defend it.

As a researcher and lecturer, I find splitting research goals into research aims, objectives, and questions is unnecessarily bureaucratic and confusing for students. For most biomedical research projects, including ‘real research’, 1-3 research questions will suffice (numbers may differ by discipline).

Awesome! Very important resources and presented in an informative way to easily understand the golden thread. Indeed, thank you so much.

Well explained

The blog article on research aims, objectives, and questions by Grad Coach is a clear and insightful guide that aligns with my experiences in academic research. The article effectively breaks down the often complex concepts of research aims and objectives, providing a straightforward and accessible explanation. Drawing from my own research endeavors, I appreciate the practical tips offered, such as the need for specificity and clarity when formulating research questions. The article serves as a valuable resource for students and researchers, offering a concise roadmap for crafting well-defined research goals and objectives. Whether you’re a novice or an experienced researcher, this article provides practical insights that contribute to the foundational aspects of a successful research endeavor.

A great thanks for you. it is really amazing explanation. I grasp a lot and one step up to research knowledge.

I really found these tips helpful. Thank you very much Grad Coach.

I found this article helpful. Thanks for sharing this.

thank you so much, the explanation and examples are really helpful

This is a well researched and superbly written article for learners of research methods at all levels in the research topic from conceptualization to research findings and conclusions. I highly recommend this material to university graduate students. As an instructor of advanced research methods for PhD students, I have confirmed that I was giving the right guidelines for the degree they are undertaking.

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