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Guide to writing your thesis/dissertation, definition of dissertation and thesis.

The dissertation or thesis is a scholarly treatise that substantiates a specific point of view as a result of original research that is conducted by students during their graduate study. At Cornell, the thesis is a requirement for the receipt of the M.A. and M.S. degrees and some professional master’s degrees. The dissertation is a requirement of the Ph.D. degree.

Formatting Requirement and Standards

The Graduate School sets the minimum format for your thesis or dissertation, while you, your special committee, and your advisor/chair decide upon the content and length. Grammar, punctuation, spelling, and other mechanical issues are your sole responsibility. Generally, the thesis and dissertation should conform to the standards of leading academic journals in your field. The Graduate School does not monitor the thesis or dissertation for mechanics, content, or style.

“Papers Option” Dissertation or Thesis

A “papers option” is available only to students in certain fields, which are listed on the Fields Permitting the Use of Papers Option page , or by approved petition. If you choose the papers option, your dissertation or thesis is organized as a series of relatively independent chapters or papers that you have submitted or will be submitting to journals in the field. You must be the only author or the first author of the papers to be used in the dissertation. The papers-option dissertation or thesis must meet all format and submission requirements, and a singular referencing convention must be used throughout.

ProQuest Electronic Submissions

The dissertation and thesis become permanent records of your original research, and in the case of doctoral research, the Graduate School requires publication of the dissertation and abstract in its original form. All Cornell master’s theses and doctoral dissertations require an electronic submission through ProQuest, which fills orders for paper or digital copies of the thesis and dissertation and makes a digital version available online via their subscription database, ProQuest Dissertations & Theses . For master’s theses, only the abstract is available. ProQuest provides worldwide distribution of your work from the master copy. You retain control over your dissertation and are free to grant publishing rights as you see fit. The formatting requirements contained in this guide meet all ProQuest specifications.

Copies of Dissertation and Thesis

Copies of Ph.D. dissertations and master’s theses are also uploaded in PDF format to the Cornell Library Repository, eCommons . A print copy of each master’s thesis and doctoral dissertation is submitted to Cornell University Library by ProQuest.

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What is a Dissertation? Everything You Need to Know 

dissertation academic or professional

Cait Williams is a Content Writer at Scholarships360. Cait recently graduated from Ohio University with a degree in Journalism and Strategic Communications. During her time at OU, was active in the outdoor recreation community.

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dissertation academic or professional

Cari Schultz is an Educational Review Board Advisor at Scholarships360, where she reviews content featured on the site. For over 20 years, Cari has worked in college admissions (Baldwin Wallace University, The Ohio State University, University of Kentucky) and as a college counselor (Columbus School for Girls).

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Maria Geiger is Director of Content at Scholarships360. She is a former online educational technology instructor and adjunct writing instructor. In addition to education reform, Maria’s interests include viewpoint diversity, blended/flipped learning, digital communication, and integrating media/web tools into the curriculum to better facilitate student engagement. Maria earned both a B.A. and an M.A. in English Literature from Monmouth University, an M. Ed. in Education from Monmouth University, and a Virtual Online Teaching Certificate (VOLT) from the University of Pennsylvania.

What is a Dissertation? Everything You Need to Know 

Your dissertation, the final piece of the puzzle that stands between you and the completion of your doctoral degree . Okay, so that’s not the actual definition of the word “dissertation,” but when you’re writing one, that can feel true at times! Keep reading to learn the academic definition and take a more in depth look at what a dissertation is and how to navigate writing one. So, let’s go!  

Related : Top fully funded PhD programs

Dissertation vs. thesis  

While dissertation and thesis are sometimes used interchangeably, they actually refer to two different pieces of writing. A thesis is traditionally completed at the end of a masters program . It is based on pre-existing research and showcases your ability to understand the information you have been learning about in your program.   

A dissertation is much longer than a thesis and is completed at the end of a PhD or doctorate program . It is the last thing you need to complete in order to earn your doctorate in your chosen field. It will be about a topic of your choosing that is within your field of study. Instead of using all pre-existing information though, you will conduct a portion of your own research and propose new ideas.

See also : Top scholarships for graduate students   

What do you write about when completing a dissertation?

What you write about will depend on what field of study you are in. A dissertation is designed to be your own. Meaning that what you write about should be a new idea, a new topic, or question that is still unanswered in your field. Something that you will need to collect new data on, potentially interview people for and explore what information is already available.  

Generally, an idea will need to be approved or at least discussed with whoever is overseeing your dissertation before you begin writing. It’s important to put time and effort into choosing a topic that you will be able to find either existing research for and add to, or a topic that you will be able to establish your own methods of data collection for. Again, the goal of your dissertation is to add to your field.   

How long does a dissertation need to be?  

Your dissertation length will vary, but you can generally count on it to be around 2-3 times the length of your thesis. A standard thesis is roughly 80 to 100 pages. So, on the short end you’re looking at a 200 pages dissertation, while the longer end can reach as high as 400 pages.  

How long does it take to write?  

The page count for a dissertation is enough to scare even the best writers away, but take a breath and rest easy knowing that this is not something you complete in just one semester or even two. On the short end you will have a year to write your dissertation, while the longer end can offer as much as two years to complete your dissertation. During this time, you will work with an advisor who can watch over you and help you along the way.  

The parts of a dissertation   

A dissertation is not just one long paper you must write. Thankfully, it is broken down into manageable pieces that you complete over time.  

Choosing a topic  

The first thing you will do is come up with your topic. Again, your topic will need to be approved by whoever is overseeing your dissertation. If they think that it may not be a strong topic, they will let you know. Even if a topic is approved though, you’ll need to do research around that topic first to make sure that it has not already been covered, or if it has that you take into consideration what has been done and add to the topic in a new way.  

Research  

Research can mean looking at what already exists, as well as conducting your own research to add to a proposed idea of yours. Your research can take many different forms depending on what field you are in. Research can be costly at times, so be sure to check out what funding opportunities are available for doctoral research. There are even post PhD research grants you should be familiar with if you intend to continue researching.  

Chapter break down  

A dissertation generally consists of five chapters. We’ve written them out below with a brief description of each and what they include.   

Introduction – Just as you would expect, this is where you will introduce your topic and what you plan to discuss  

Literature review – This section will address the research you have found that has already been done, or found has not been done, that pertains to your topic  

Methodology – How you go about collecting information for your dissertation, whether it be conducting your own research or delving deep into what has already been done, will be discussed in the methodology section 

Results – Your results will analyze the information you gathered  in regard to your topic 

Discussion – Finally, your discussion section will assess the meaning of your results and it is also where you will add your own ideas, rooted in research, about what those results mean in a broader context in regard to your field 

There will be more parts of your dissertation that are not included in the chapters, but the bulk of your dissertation will be made up by these five chapters. Things like title pages, references, appendices, and table of contents will also be included.  

Defending your dissertation  

Believe it or not, it’s not enough just to write your dissertation–you also have to defend your dissertation. This is another reason why taking a thorough amount of time to choose your topic is so important. You’ll likely need to propose your initial dissertation idea, but that will be much simpler and shorter. Your final defense will be much lengthier and in depth.  

During your defense, you will present your dissertation to a committee. It’s likely that you’ll be at least somewhat familiar with those on the committee; they are not just randomly picked. They will ask you questions about your research, and you will need to respond to each question. A defense generally takes around two hours. The point of a defense is not to have people try to undermine your work, but for you to exemplify your expertise in your field.  

Failing your dissertation  

Nobody wants to think about failing, but unfortunately, you can fail your dissertation. However, let’s talk about a few things before we just leave it at that. First, if you are afraid of failing your dissertation, this is something that you should speak to your advisor about. They can help you determine if there should be legitimate concerns or if you are getting in your own head.  

Second, even if you do fail your dissertation, you are usually allowed to resubmit one time. This of course is not ideal, but it does give you a little room to breathe. Your goal is to do great from the start, but remember this is not an easy task. You’ll likely have plenty of bumps along the way! 

Again, if you have concerns about failing, address them sooner rather than later and seek help. There are bound to be plenty of people and services around you, as well as additional services that you can pay for which will help review your materials and guide you along.

Key Takeaways

  • Dissertations are completed as the last step of your PhD or doctorate degree 
  • Your dissertation will be related to a topic or question in your field of study that you choose 
  • Dissertations take anywhere from one to two years to complete and can be upwards of three hundred pages long 
  • Your dissertation is designed to showcase your expertise in your field and your addition of new ideas to the field about a particular question or area 

Frequently asked questions about dissertations  

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Dissertation Explained: A Grad Student’s Guide

Updated: August 7, 2023

Published: March 10, 2020

Dissertation-Explained-A-Grad-Student's-Guide

Higher education is filled with milestones. When completing your PhD , you will be required to complete a dissertation. Even if you’ve heard this word thrown around before, you still may be questioning “What is a dissertation?” It’s a common question, especially for those considering to join or are already in a graduate program. As such, here’s everything you need to know about dissertations.

What is a Dissertation?

A dissertation is a written document that details research. A dissertation also signifies the completion of your PhD program. It is required to earn a PhD degree, which stands for Doctor of Philosophy.

A PhD is created from knowledge acquired from:

1. Coursework:

A PhD program consists of academic courses that are usually small in size and challenging in content. Most PhD courses consist of a high amount and level of reading and writing per week. These courses will help prepare you for your dissertation as they will teach research methodology.

2. Research:

For your dissertation, it is likely that you will have the choice between performing your own research on a subject , or expanding on existing research. Likely, you will complete a mixture of the two. For those in the hard sciences, you will perform research in a lab. For those in humanities and social sciences, research may mean gathering data from surveys or existing research.

3. Analysis:

Once you have collected the data you need to prove your point, you will have to analyze and interpret the information. PhD programs will prepare you for how to conduct analysis, as well as for how to position your research into the existing body of work on the subject matter.

4. Support:

The process of writing and completing a dissertation is bigger than the work itself. It can lead to research positions within the university or outside companies. It may mean that you will teach and share your findings with current undergraduates, or even be published in academic journals. How far you plan to take your dissertation is your choice to make and will require the relevant effort to accomplish your goals.

Moving from Student to Scholar

In essence, a dissertation is what moves a doctoral student into becoming a scholar. Their research may be published, shared, and used as educational material moving forwards.

Thesis vs. Dissertation

Basic differences.

Grad students may conflate the differences between a thesis and a dissertation.

Simply put, a thesis is what you write to complete a master’s degree. It summarizes existing research and signifies that you understand the subject matter deeply.

On the other hand, a dissertation is the culmination of a doctoral program. It will likely require your own research and it can contribute an entirely new idea into your field.

Structural Differences

When it comes to the structure, a thesis and dissertation are also different. A thesis is like the research papers you complete during undergraduate studies. A thesis displays your ability to think critically and analyze information. It’s less based on research that you’ve completed yourself and more about interpreting and analyzing existing material. They are generally around 100 pages in length.

A dissertation is generally two to three times longer compared to a thesis. This is because the bulk of the information is garnered from research you’ve performed yourself. Also, if you are providing something new in your field, it means that existing information is lacking. That’s why you’ll have to provide a lot of data and research to back up your claims.

Your Guide: Structuring a Dissertation

Dissertation length.

The length of a dissertation varies between study level and country. At an undergraduate level, this is more likely referred to as a research paper, which is 10,000 to 12,000 words on average. At a master’s level, the word count may be 15,000 to 25,000, and it will likely be in the form of a thesis. For those completing their PhD, then the dissertation could be 50,000 words or more.

Photo by  Louis Reed  on  Unsplash

Format of the dissertation.

Here are the items you must include in a dissertation. While the format may slightly vary, here’s a look at one way to format your dissertation:

1. Title page:

This is the first page which includes: title, your name, department, degree program, institution, and submission date. Your program may specify exactly how and what they want you to include on the title page.

2. Acknowledgements:

This is optional, but it is where you can express your gratitude to those who have helped you complete your dissertation (professors, research partners, etc.).

3. Abstract:

The abstract is about 150-300 words and summarizes what your research is about. You state the main topic, the methods used, the main results, and your conclusion.

4. Table of Contents

Here, you list the chapter titles and pages to serve as a wayfinding tool for your readers.

5. List of Figures and Tables:

This is like the table of contents, but for graphs and figures.

6. List of Abbreviations:

If you’ve constantly abbreviated words in your content, define them in a list at the beginning.

7. Glossary:

In highly specialized work, it’s likely that you’ve used words that most people may not understand, so a glossary is where you define these terms.

8. Introduction:

Your introduction sets up the topic, purpose, and relevance. It’s where readers will understand what they expect to gain from your dissertation.

9. Literature Review / Theoretical Framework:

Based on the research you performed to create your own dissertation, you’ll want to summarize and address the gaps in what you researched.

10. Methodology

This is where you define how you conducted your research. It offers credibility for you as a source of information. You should give all the details as to how you’ve conducted your research, including: where and when research took place, how it was conducted, any obstacles you faced, and how you justified your findings.

11. Results:

This is where you share the results that have helped contribute to your findings.

12. Discussion:

In the discussion section, you explain what these findings mean to your research question. Were they in line with your expectations or did something jump out as surprising? You may also want to recommend ways to move forward in researching and addressing the subject matter.

13. Conclusion:

A conclusion ties it all together and summarizes the answer to the research question and leaves your reader clearly understanding your main argument.

14. Reference List:

This is the equivalent to a works cited or bibliography page, which documents all the sources you used to create your dissertation.

15. Appendices:

If you have any information that was ancillary to creating the dissertation, but doesn’t directly fit into its chapters, then you can add it in the appendix.

Drafting and Rewriting

As with any paper, especially one of this size and importance, the writing requires a process. It may begin with outlines and drafts, and even a few rewrites. It’s important to proofread your dissertation for both grammatical mistakes, but also to ensure it can be clearly understood.

It’s always useful to read your writing out loud to catch mistakes. Also, if you have people who you trust to read it over — like a peer, family member, mentor, or professor — it’s very helpful to get a second eye on your work.

How is it Different from an Essay?

There are a few main differences between a dissertation and an essay. For starters, an essay is relatively short in comparison to a dissertation, which includes your own body of research and work. Not only is an essay shorter, but you are also likely given the topic matter of an essay. When it comes to a dissertation, you have the freedom to construct your own argument, conduct your own research, and then prove your findings.

Types of Dissertations

You can choose what type of dissertation you complete. Often, this depends on the subject and doctoral degree, but the two main types are:

This relies on conducting your own research.

Non-empirical:

This relies on studying existing research to support your argument.

Photo by  freddie marriage  on  Unsplash

More things you should know.

A dissertation is certainly no easy feat. Here’s a few more things to remember before you get started writing your own:

1. Independent by Nature:

The process of completing a dissertation is self-directed, and therefore can feel overwhelming. However, if you approach it like the new experience that it is with an open-mind and willingness to learn, you will make it through!

2. Seek Support:

There are countless people around to offer support. From professors to peers, you can always ask for help throughout the process.

3. Writing Skills:

The process of writing a dissertation will further hone your writing skills which will follow you throughout your life. These skills are highly transferable on the job, from having the ability to communicate to also developing analytical and critical thinking skills.

4. Time Management:

You can work backwards from the culmination of your program to break down this gargantuan task into smaller pieces. That way, you can manage your time to chip away at the task throughout the length of the program.

5. Topic Flexibility:

It’s okay to change subject matters and rethink the point of your dissertation. Just try as much as possible to do this early in the process so you don’t waste too much time and energy.

The Wrap Up

A dissertation marks the completion of your doctoral program and moves you from being a student to being a scholar. While the process is long and requires a lot of effort and energy, you have the power to lend an entirely new research and findings into your field of expertise.

As always, when in the thick of things, remember why you started. Completing both your dissertation and PhD is a commendable accomplishment.

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Dissertation Structure & Layout 101: How to structure your dissertation, thesis or research project.

By: Derek Jansen (MBA) Reviewed By: David Phair (PhD) | July 2019

So, you’ve got a decent understanding of what a dissertation is , you’ve chosen your topic and hopefully you’ve received approval for your research proposal . Awesome! Now its time to start the actual dissertation or thesis writing journey.

To craft a high-quality document, the very first thing you need to understand is dissertation structure . In this post, we’ll walk you through the generic dissertation structure and layout, step by step. We’ll start with the big picture, and then zoom into each chapter to briefly discuss the core contents. If you’re just starting out on your research journey, you should start with this post, which covers the big-picture process of how to write a dissertation or thesis .

Dissertation structure and layout - the basics

*The Caveat *

In this post, we’ll be discussing a traditional dissertation/thesis structure and layout, which is generally used for social science research across universities, whether in the US, UK, Europe or Australia. However, some universities may have small variations on this structure (extra chapters, merged chapters, slightly different ordering, etc).

So, always check with your university if they have a prescribed structure or layout that they expect you to work with. If not, it’s safe to assume the structure we’ll discuss here is suitable. And even if they do have a prescribed structure, you’ll still get value from this post as we’ll explain the core contents of each section.  

Overview: S tructuring a dissertation or thesis

  • Acknowledgements page
  • Abstract (or executive summary)
  • Table of contents , list of figures and tables
  • Chapter 1: Introduction
  • Chapter 2: Literature review
  • Chapter 3: Methodology
  • Chapter 4: Results
  • Chapter 5: Discussion
  • Chapter 6: Conclusion
  • Reference list

As I mentioned, some universities will have slight variations on this structure. For example, they want an additional “personal reflection chapter”, or they might prefer the results and discussion chapter to be merged into one. Regardless, the overarching flow will always be the same, as this flow reflects the research process , which we discussed here – i.e.:

  • The introduction chapter presents the core research question and aims .
  • The literature review chapter assesses what the current research says about this question.
  • The methodology, results and discussion chapters go about undertaking new research about this question.
  • The conclusion chapter (attempts to) answer the core research question .

In other words, the dissertation structure and layout reflect the research process of asking a well-defined question(s), investigating, and then answering the question – see below.

A dissertation's structure reflect the research process

To restate that – the structure and layout of a dissertation reflect the flow of the overall research process . This is essential to understand, as each chapter will make a lot more sense if you “get” this concept. If you’re not familiar with the research process, read this post before going further.

Right. Now that we’ve covered the big picture, let’s dive a little deeper into the details of each section and chapter. Oh and by the way, you can also grab our free dissertation/thesis template here to help speed things up.

The title page of your dissertation is the very first impression the marker will get of your work, so it pays to invest some time thinking about your title. But what makes for a good title? A strong title needs to be 3 things:

  • Succinct (not overly lengthy or verbose)
  • Specific (not vague or ambiguous)
  • Representative of the research you’re undertaking (clearly linked to your research questions)

Typically, a good title includes mention of the following:

  • The broader area of the research (i.e. the overarching topic)
  • The specific focus of your research (i.e. your specific context)
  • Indication of research design (e.g. quantitative , qualitative , or  mixed methods ).

For example:

A quantitative investigation [research design] into the antecedents of organisational trust [broader area] in the UK retail forex trading market [specific context/area of focus].

Again, some universities may have specific requirements regarding the format and structure of the title, so it’s worth double-checking expectations with your institution (if there’s no mention in the brief or study material).

Dissertations stacked up

Acknowledgements

This page provides you with an opportunity to say thank you to those who helped you along your research journey. Generally, it’s optional (and won’t count towards your marks), but it is academic best practice to include this.

So, who do you say thanks to? Well, there’s no prescribed requirements, but it’s common to mention the following people:

  • Your dissertation supervisor or committee.
  • Any professors, lecturers or academics that helped you understand the topic or methodologies.
  • Any tutors, mentors or advisors.
  • Your family and friends, especially spouse (for adult learners studying part-time).

There’s no need for lengthy rambling. Just state who you’re thankful to and for what (e.g. thank you to my supervisor, John Doe, for his endless patience and attentiveness) – be sincere. In terms of length, you should keep this to a page or less.

Abstract or executive summary

The dissertation abstract (or executive summary for some degrees) serves to provide the first-time reader (and marker or moderator) with a big-picture view of your research project. It should give them an understanding of the key insights and findings from the research, without them needing to read the rest of the report – in other words, it should be able to stand alone .

For it to stand alone, your abstract should cover the following key points (at a minimum):

  • Your research questions and aims – what key question(s) did your research aim to answer?
  • Your methodology – how did you go about investigating the topic and finding answers to your research question(s)?
  • Your findings – following your own research, what did do you discover?
  • Your conclusions – based on your findings, what conclusions did you draw? What answers did you find to your research question(s)?

So, in much the same way the dissertation structure mimics the research process, your abstract or executive summary should reflect the research process, from the initial stage of asking the original question to the final stage of answering that question.

In practical terms, it’s a good idea to write this section up last , once all your core chapters are complete. Otherwise, you’ll end up writing and rewriting this section multiple times (just wasting time). For a step by step guide on how to write a strong executive summary, check out this post .

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Table of contents

This section is straightforward. You’ll typically present your table of contents (TOC) first, followed by the two lists – figures and tables. I recommend that you use Microsoft Word’s automatic table of contents generator to generate your TOC. If you’re not familiar with this functionality, the video below explains it simply:

If you find that your table of contents is overly lengthy, consider removing one level of depth. Oftentimes, this can be done without detracting from the usefulness of the TOC.

Right, now that the “admin” sections are out of the way, its time to move on to your core chapters. These chapters are the heart of your dissertation and are where you’ll earn the marks. The first chapter is the introduction chapter – as you would expect, this is the time to introduce your research…

It’s important to understand that even though you’ve provided an overview of your research in your abstract, your introduction needs to be written as if the reader has not read that (remember, the abstract is essentially a standalone document). So, your introduction chapter needs to start from the very beginning, and should address the following questions:

  • What will you be investigating (in plain-language, big picture-level)?
  • Why is that worth investigating? How is it important to academia or business? How is it sufficiently original?
  • What are your research aims and research question(s)? Note that the research questions can sometimes be presented at the end of the literature review (next chapter).
  • What is the scope of your study? In other words, what will and won’t you cover ?
  • How will you approach your research? In other words, what methodology will you adopt?
  • How will you structure your dissertation? What are the core chapters and what will you do in each of them?

These are just the bare basic requirements for your intro chapter. Some universities will want additional bells and whistles in the intro chapter, so be sure to carefully read your brief or consult your research supervisor.

If done right, your introduction chapter will set a clear direction for the rest of your dissertation. Specifically, it will make it clear to the reader (and marker) exactly what you’ll be investigating, why that’s important, and how you’ll be going about the investigation. Conversely, if your introduction chapter leaves a first-time reader wondering what exactly you’ll be researching, you’ve still got some work to do.

Now that you’ve set a clear direction with your introduction chapter, the next step is the literature review . In this section, you will analyse the existing research (typically academic journal articles and high-quality industry publications), with a view to understanding the following questions:

  • What does the literature currently say about the topic you’re investigating?
  • Is the literature lacking or well established? Is it divided or in disagreement?
  • How does your research fit into the bigger picture?
  • How does your research contribute something original?
  • How does the methodology of previous studies help you develop your own?

Depending on the nature of your study, you may also present a conceptual framework towards the end of your literature review, which you will then test in your actual research.

Again, some universities will want you to focus on some of these areas more than others, some will have additional or fewer requirements, and so on. Therefore, as always, its important to review your brief and/or discuss with your supervisor, so that you know exactly what’s expected of your literature review chapter.

Dissertation writing

Now that you’ve investigated the current state of knowledge in your literature review chapter and are familiar with the existing key theories, models and frameworks, its time to design your own research. Enter the methodology chapter – the most “science-ey” of the chapters…

In this chapter, you need to address two critical questions:

  • Exactly HOW will you carry out your research (i.e. what is your intended research design)?
  • Exactly WHY have you chosen to do things this way (i.e. how do you justify your design)?

Remember, the dissertation part of your degree is first and foremost about developing and demonstrating research skills . Therefore, the markers want to see that you know which methods to use, can clearly articulate why you’ve chosen then, and know how to deploy them effectively.

Importantly, this chapter requires detail – don’t hold back on the specifics. State exactly what you’ll be doing, with who, when, for how long, etc. Moreover, for every design choice you make, make sure you justify it.

In practice, you will likely end up coming back to this chapter once you’ve undertaken all your data collection and analysis, and revise it based on changes you made during the analysis phase. This is perfectly fine. Its natural for you to add an additional analysis technique, scrap an old one, etc based on where your data lead you. Of course, I’m talking about small changes here – not a fundamental switch from qualitative to quantitative, which will likely send your supervisor in a spin!

You’ve now collected your data and undertaken your analysis, whether qualitative, quantitative or mixed methods. In this chapter, you’ll present the raw results of your analysis . For example, in the case of a quant study, you’ll present the demographic data, descriptive statistics, inferential statistics , etc.

Typically, Chapter 4 is simply a presentation and description of the data, not a discussion of the meaning of the data. In other words, it’s descriptive, rather than analytical – the meaning is discussed in Chapter 5. However, some universities will want you to combine chapters 4 and 5, so that you both present and interpret the meaning of the data at the same time. Check with your institution what their preference is.

Now that you’ve presented the data analysis results, its time to interpret and analyse them. In other words, its time to discuss what they mean, especially in relation to your research question(s).

What you discuss here will depend largely on your chosen methodology. For example, if you’ve gone the quantitative route, you might discuss the relationships between variables . If you’ve gone the qualitative route, you might discuss key themes and the meanings thereof. It all depends on what your research design choices were.

Most importantly, you need to discuss your results in relation to your research questions and aims, as well as the existing literature. What do the results tell you about your research questions? Are they aligned with the existing research or at odds? If so, why might this be? Dig deep into your findings and explain what the findings suggest, in plain English.

The final chapter – you’ve made it! Now that you’ve discussed your interpretation of the results, its time to bring it back to the beginning with the conclusion chapter . In other words, its time to (attempt to) answer your original research question s (from way back in chapter 1). Clearly state what your conclusions are in terms of your research questions. This might feel a bit repetitive, as you would have touched on this in the previous chapter, but its important to bring the discussion full circle and explicitly state your answer(s) to the research question(s).

Dissertation and thesis prep

Next, you’ll typically discuss the implications of your findings? In other words, you’ve answered your research questions – but what does this mean for the real world (or even for academia)? What should now be done differently, given the new insight you’ve generated?

Lastly, you should discuss the limitations of your research, as well as what this means for future research in the area. No study is perfect, especially not a Masters-level. Discuss the shortcomings of your research. Perhaps your methodology was limited, perhaps your sample size was small or not representative, etc, etc. Don’t be afraid to critique your work – the markers want to see that you can identify the limitations of your work. This is a strength, not a weakness. Be brutal!

This marks the end of your core chapters – woohoo! From here on out, it’s pretty smooth sailing.

The reference list is straightforward. It should contain a list of all resources cited in your dissertation, in the required format, e.g. APA , Harvard, etc.

It’s essential that you use reference management software for your dissertation. Do NOT try handle your referencing manually – its far too error prone. On a reference list of multiple pages, you’re going to make mistake. To this end, I suggest considering either Mendeley or Zotero. Both are free and provide a very straightforward interface to ensure that your referencing is 100% on point. I’ve included a simple how-to video for the Mendeley software (my personal favourite) below:

Some universities may ask you to include a bibliography, as opposed to a reference list. These two things are not the same . A bibliography is similar to a reference list, except that it also includes resources which informed your thinking but were not directly cited in your dissertation. So, double-check your brief and make sure you use the right one.

The very last piece of the puzzle is the appendix or set of appendices. This is where you’ll include any supporting data and evidence. Importantly, supporting is the keyword here.

Your appendices should provide additional “nice to know”, depth-adding information, which is not critical to the core analysis. Appendices should not be used as a way to cut down word count (see this post which covers how to reduce word count ). In other words, don’t place content that is critical to the core analysis here, just to save word count. You will not earn marks on any content in the appendices, so don’t try to play the system!

Time to recap…

And there you have it – the traditional dissertation structure and layout, from A-Z. To recap, the core structure for a dissertation or thesis is (typically) as follows:

  • Acknowledgments page

Most importantly, the core chapters should reflect the research process (asking, investigating and answering your research question). Moreover, the research question(s) should form the golden thread throughout your dissertation structure. Everything should revolve around the research questions, and as you’ve seen, they should form both the start point (i.e. introduction chapter) and the endpoint (i.e. conclusion chapter).

I hope this post has provided you with clarity about the traditional dissertation/thesis structure and layout. If you have any questions or comments, please leave a comment below, or feel free to get in touch with us. Also, be sure to check out the rest of the  Grad Coach Blog .

dissertation academic or professional

Psst… there’s more (for free)

This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project. 

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36 Comments

ARUN kumar SHARMA

many thanks i found it very useful

Derek Jansen

Glad to hear that, Arun. Good luck writing your dissertation.

Sue

Such clear practical logical advice. I very much needed to read this to keep me focused in stead of fretting.. Perfect now ready to start my research!

hayder

what about scientific fields like computer or engineering thesis what is the difference in the structure? thank you very much

Tim

Thanks so much this helped me a lot!

Ade Adeniyi

Very helpful and accessible. What I like most is how practical the advice is along with helpful tools/ links.

Thanks Ade!

Aswathi

Thank you so much sir.. It was really helpful..

You’re welcome!

Jp Raimundo

Hi! How many words maximum should contain the abstract?

Karmelia Renatee

Thank you so much 😊 Find this at the right moment

You’re most welcome. Good luck with your dissertation.

moha

best ever benefit i got on right time thank you

Krishnan iyer

Many times Clarity and vision of destination of dissertation is what makes the difference between good ,average and great researchers the same way a great automobile driver is fast with clarity of address and Clear weather conditions .

I guess Great researcher = great ideas + knowledge + great and fast data collection and modeling + great writing + high clarity on all these

You have given immense clarity from start to end.

Alwyn Malan

Morning. Where will I write the definitions of what I’m referring to in my report?

Rose

Thank you so much Derek, I was almost lost! Thanks a tonnnn! Have a great day!

yemi Amos

Thanks ! so concise and valuable

Kgomotso Siwelane

This was very helpful. Clear and concise. I know exactly what to do now.

dauda sesay

Thank you for allowing me to go through briefly. I hope to find time to continue.

Patrick Mwathi

Really useful to me. Thanks a thousand times

Adao Bundi

Very interesting! It will definitely set me and many more for success. highly recommended.

SAIKUMAR NALUMASU

Thank you soo much sir, for the opportunity to express my skills

mwepu Ilunga

Usefull, thanks a lot. Really clear

Rami

Very nice and easy to understand. Thank you .

Chrisogonas Odhiambo

That was incredibly useful. Thanks Grad Coach Crew!

Luke

My stress level just dropped at least 15 points after watching this. Just starting my thesis for my grad program and I feel a lot more capable now! Thanks for such a clear and helpful video, Emma and the GradCoach team!

Judy

Do we need to mention the number of words the dissertation contains in the main document?

It depends on your university’s requirements, so it would be best to check with them 🙂

Christine

Such a helpful post to help me get started with structuring my masters dissertation, thank you!

Simon Le

Great video; I appreciate that helpful information

Brhane Kidane

It is so necessary or avital course

johnson

This blog is very informative for my research. Thank you

avc

Doctoral students are required to fill out the National Research Council’s Survey of Earned Doctorates

Emmanuel Manjolo

wow this is an amazing gain in my life

Paul I Thoronka

This is so good

Tesfay haftu

How can i arrange my specific objectives in my dissertation?

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Thesis vs. Dissertation: What’s the difference?

Thesis and dissertation are extensive research papers that differ in terms of their requirements, length, and purpose, with the former being associated with a master's degree and the latter with a doctoral degree, but are often used interchangeably.

Updated on September 15, 2023

a researcher working on her thesis

A thesis and a dissertation are both extensive research papers, and both require literature searches and novel findings, but the two differ in various ways. Their definitions also differ across regions. Typically, in North America, a thesis is required for the completion of a master’s degree, while a dissertation is required for the completion of a doctoral degree. The former is long, while the latter is longer and more intensive.

Despite these differences, the two terms are often used interchangeably, especially among those who haven’t completed one or the other. Here, we’ll compare the components, length, and purpose of these two academic documents to clearly understand the differences between these important papers in the life of a graduate student.

What’s a thesis?

The term “thesis” explained here is generally consistent with how the word is used in North America to describe this substantive research paper.

A thesis is an extended argument (PDF). It is a research-based document that displays the student’s/author’s knowledge and understanding of a specific subject within their field of study. It generally presents findings on a particular topic. 

See this and this (PDFs) for examples. These superb master’s theses from Canada will give you an idea of the size and format of these papers.

Who would write a thesis?

You generally write a thesis if you’re undertaking a research-oriented master's degree program (as opposed to a practical program, which may require a capstone, internship, exam, etc.). 

The thesis is the essential part of a program’s research component, demonstrating the student's ability to critically analyze the literature and complete independent research. The process of writing a thesis involves exploring a specific research question, conducting a comprehensive literature review, collecting and analyzing data, and presenting findings in a structured and cohesive way.

A thesis' specific requirements and expectations differ depending on the academic institution, department, and program.

Components of a thesis

A thesis is typically presented in chapters. How many chapters will vary, but a common structure is:

  • Introduction: Presents the research topic, purpose, and objectives, setting the context for the work.
  • Literature review: Comprehensive survey of existing scholarly material related to the research topic, highlighting key theories and findings.
  • Methodology: Describes the methods, procedures, and tools used in doing the research.
  • Research: The actual performing of the study, collecting, and analyzing data relevant to the research question.
  • Findings and conclusions: Gives the results obtained and explains their significance in relation to the research question.
  • Limitations and future research: Outlines the study’s shortcomings and suggests potential areas for future investigation.

Within that structure, and in addition to those parts, a thesis may also include: 

  • Cover page: Contains the thesis title, author's name, institution, department, date, and other relevant information
  • Abstract : A brief summary of the thesis, highlighting the research objectives, methods, key findings, and conclusions.
  • Certificates of own work
  • Certificate of readiness to be included in the library
  • Certificate that the research has not been presented to another university
  • Acknowledgments
  • Table of contents: List of the main sections, subsections, and corresponding page numbers.
  • Index of figures and tables
  • References: A comprehensive list of all the sources cited in the thesis, following a specific citation style (e.g., APA, MLA).
  • Appendices (optional): Additional materials include:
  • Abbreviations and/or acronyms used
  • Questionnaire or interview schedule/s (if used)
  • Data acquired in the form of transcripts or numeric tables
  • Research protocol
  • Ethics protocol

What’s a dissertation?

This is also viewed from a North American perspective, where a dissertation is usually the main research work toward completing a research-based doctoral program.

A dissertation is a comprehensive and in-depth research project completed as part of the requirements for a doctoral degree. It’s a substantial piece of original work that contributes new knowledge to a specific field of study.  Naturally, when it’s completed as the major requirement for earning a PhD, it’s longer, more detailed, and the expectations are higher.

Dissertations themselves can add to the literature in the field. For this reason, some students choose to publish them and have them indexed. The research and the data acquired while working on a dissertation can potentially lead to more publications and help define the researcher’s growing area of expertise.

See this and this (PDFs)  top-ranking dissertation on ProQuest for good examples.

Who would write a dissertation?

Completion and defense of a dissertation is a standard requirement for doctoral students to earn a PhD or another doctorate such as an EdD or DM. But some specialized degrees, such as a PsyD (Doctor of Psychology), JD (Juris Doctor) or DPT (Doctor of Physical Therapy) may have practice-based requirements in place of a research project, as these courses of study are geared more toward practical application.

Components of a dissertation

A dissertation’s components are generally the same as those of a thesis. You can look at the list above for a thesis to see what typically goes into a dissertation. But, if compared with a master’s thesis, most aspects are longer and more rigorous.

The word count requirements for theses can vary significantly, but doctoral dissertations often range 40,000–80,000 words or, per Harvard , 100–300 pages.

Differences between a thesis and a dissertation

As already touched on, the key differences are in where the two documents are used, length, and rigor. There are also regional differences.

A thesis typically demonstrates a master’s degree program student's grasp and presentation of a specific subject in their field of study. It normally involves a literature review, data analysis, and original research, but it is usually shorter and less comprehensive than a dissertation. The standards for rigor and novelty may also be lower.

A dissertation requires more extensive research, original contributions to the field, and a deeper exploration of the research topic. A dissertation is typically the output associated with a doctoral degree program.

The main differences in structure between a thesis and a dissertation are in the scope and complexity.

The word count requirement for theses and dissertations can vary depending on the institution and program.

A thesis is usually 20,000–40,000 words. However, there have been cases of mathematics dissertations that were only a few pages long!

Doctoral dissertations may range 60,000 to upward of 100,000 words, and exceed 100 pages. Many universities, however, seek around 80,000 words.

Oversight and process

A thesis may simply be submitted to the student's instructor, though rigorous thesis programs require a committee and defense. A dissertation will nearly always require the student to choose a chair, a committee, and then go through a more rigorous defense and revision (if necessary).

  • Committee: Master's thesis committees usually have fewer members (typically 2–3) than doctoral dissertation committees (often 4–5, or even more).
  • Guidance: Master's students often receive more detailed direction from advisers than doctoral students, who are expected to work more independently.
  • Review: Dissertation reviews are typically more rigorous, often involving external reviewers, while thesis reviews are usually internal.
  • Defense: A dissertation defense is generally more intense and formal, as it often involves a presentation to the wider academic community, while a thesis defense might be more confined and informal.
  • Revision: The revision process for a doctoral dissertation is typically more extensive, given the larger scope of the project and higher stakes involved, compared with those for a master's thesis.

Regional differences

The terms' use varies among (and even within) countries. Here are some general regional differences:

In the United Kingdom, a thesis is commonly associated with both master's and doctoral degree programs. For example, the University College London  refers to a thesis for EngD, MPhil, MD(Res), and PhD degrees. At the University of Nottingham , a dissertation is written for a research master’s degree.

In Australia and New Zealand , “thesis” is generally used to refer to a substantial research project completed for a higher degree, though not limited to a master’s (you’ll find ample references to a “PhD thesis”).

In Latin American countries,  the thesis is commonly used to refer to both master's and doctoral research projects.

Closing thoughts

Both theses and dissertations are necessary documents for students in graduate programs. Despite the differences in expectations, and even in definitions of these papers, the student-author must do a diligent and rigorous job to earn their degree.

Here are a few helpful resources if you want to get into greater detail:

  • Writing the Winning Thesis or Dissertation: A Step-By-Step Guide
  • 100 PhD rules of the game to successfully complete a doctoral dissertation (PDF)
  • Theses and Dissertations: A Guide to Writing in Social and Physical Sciences

Perfect the English on your thesis or dissertation

Whether you’re submitting a thesis or a dissertation, if it’s in English, it should:

  • Have no grammatical or spelling mistakes
  • Use field-appropriate language
  • Concisely and clearly communicate your research.

That’s what AJE expert editors will do for you. Within days, you can receive an expert English edit of your work. The editor will be familiar with your field of study and will comprehensively improve both the language quality and the delivery of your message. Look into AJE English Editing .

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Choose between our expert academic editing services to prepare your thesis or dissertation.

Frequently asked questions

What is the difference between a dissertation and a thesis.

The words ‘ dissertation ’ and ‘thesis’ both refer to a large written research project undertaken to complete a degree, but they are used differently depending on the country:

  • In the UK, you write a dissertation at the end of a bachelor’s or master’s degree, and you write a thesis to complete a PhD.
  • In the US, it’s the other way around: you may write a thesis at the end of a bachelor’s or master’s degree, and you write a dissertation to complete a PhD.

Frequently asked questions: Knowledge Base

Methodology refers to the overarching strategy and rationale of your research. Developing your methodology involves studying the research methods used in your field and the theories or principles that underpin them, in order to choose the approach that best matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. interviews, experiments , surveys , statistical tests ).

In a dissertation or scientific paper, the methodology chapter or methods section comes after the introduction and before the results , discussion and conclusion .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

Reliability and validity are both about how well a method measures something:

  • Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
  • Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research , you also have to consider the internal and external validity of your experiment.

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

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

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

There are several reasons to conduct a literature review at the beginning of a research project:

  • To familiarise yourself with the current state of knowledge on your topic
  • To ensure that you’re not just repeating what others have already done
  • To identify gaps in knowledge and unresolved problems that your research can address
  • To develop your theoretical framework and methodology
  • To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a dissertation , thesis, research paper , or proposal .

The literature review usually comes near the beginning of your  dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

Harvard referencing uses an author–date system. Sources are cited by the author’s last name and the publication year in brackets. Each Harvard in-text citation corresponds to an entry in the alphabetised reference list at the end of the paper.

Vancouver referencing uses a numerical system. Sources are cited by a number in parentheses or superscript. Each number corresponds to a full reference at the end of the paper.

A Harvard in-text citation should appear in brackets every time you quote, paraphrase, or refer to information from a source.

The citation can appear immediately after the quotation or paraphrase, or at the end of the sentence. If you’re quoting, place the citation outside of the quotation marks but before any other punctuation like a comma or full stop.

In Harvard referencing, up to three author names are included in an in-text citation or reference list entry. When there are four or more authors, include only the first, followed by ‘ et al. ’

A bibliography should always contain every source you cited in your text. Sometimes a bibliography also contains other sources that you used in your research, but did not cite in the text.

MHRA doesn’t specify a rule about this, so check with your supervisor to find out exactly what should be included in your bibliography.

Footnote numbers should appear in superscript (e.g. 11 ). You can use the ‘Insert footnote’ button in Word to do this automatically; it’s in the ‘References’ tab at the top.

Footnotes always appear after the quote or paraphrase they relate to. MHRA generally recommends placing footnote numbers at the end of the sentence, immediately after any closing punctuation, like this. 12

In situations where this might be awkward or misleading, such as a long sentence containing multiple quotations, footnotes can also be placed at the end of a clause mid-sentence, like this; 13 note that they still come after any punctuation.

When a source has two or three authors, name all of them in your MHRA references . When there are four or more, use only the first name, followed by ‘and others’:

Note that in the bibliography, only the author listed first has their name inverted. The names of additional authors and those of translators or editors are written normally.

A citation should appear wherever you use information or ideas from a source, whether by quoting or paraphrasing its content.

In Vancouver style , you have some flexibility about where the citation number appears in the sentence – usually directly after mentioning the author’s name is best, but simply placing it at the end of the sentence is an acceptable alternative, as long as it’s clear what it relates to.

In Vancouver style , when you refer to a source with multiple authors in your text, you should only name the first author followed by ‘et al.’. This applies even when there are only two authors.

In your reference list, include up to six authors. For sources with seven or more authors, list the first six followed by ‘et al.’.

The main difference is in terms of scale – a dissertation is usually much longer than the other essays you complete during your degree.

Another key difference is that you are given much more independence when working on a dissertation. You choose your own dissertation topic , and you have to conduct the research and write the dissertation yourself (with some assistance from your supervisor).

Dissertation word counts vary widely across different fields, institutions, and levels of education:

  • An undergraduate dissertation is typically 8,000–15,000 words
  • A master’s dissertation is typically 12,000–50,000 words
  • A PhD thesis is typically book-length: 70,000–100,000 words

However, none of these are strict guidelines – your word count may be lower or higher than the numbers stated here. Always check the guidelines provided by your university to determine how long your own dissertation should be.

At the bachelor’s and master’s levels, the dissertation is usually the main focus of your final year. You might work on it (alongside other classes) for the entirety of the final year, or for the last six months. This includes formulating an idea, doing the research, and writing up.

A PhD thesis takes a longer time, as the thesis is the main focus of the degree. A PhD thesis might be being formulated and worked on for the whole four years of the degree program. The writing process alone can take around 18 months.

References should be included in your text whenever you use words, ideas, or information from a source. A source can be anything from a book or journal article to a website or YouTube video.

If you don’t acknowledge your sources, you can get in trouble for plagiarism .

Your university should tell you which referencing style to follow. If you’re unsure, check with a supervisor. Commonly used styles include:

  • Harvard referencing , the most commonly used style in UK universities.
  • MHRA , used in humanities subjects.
  • APA , used in the social sciences.
  • Vancouver , used in biomedicine.
  • OSCOLA , used in law.

Your university may have its own referencing style guide.

If you are allowed to choose which style to follow, we recommend Harvard referencing, as it is a straightforward and widely used style.

To avoid plagiarism , always include a reference when you use words, ideas or information from a source. This shows that you are not trying to pass the work of others off as your own.

You must also properly quote or paraphrase the source. If you’re not sure whether you’ve done this correctly, you can use the Scribbr Plagiarism Checker to find and correct any mistakes.

In Harvard style , when you quote directly from a source that includes page numbers, your in-text citation must include a page number. For example: (Smith, 2014, p. 33).

You can also include page numbers to point the reader towards a passage that you paraphrased . If you refer to the general ideas or findings of the source as a whole, you don’t need to include a page number.

When you want to use a quote but can’t access the original source, you can cite it indirectly. In the in-text citation , first mention the source you want to refer to, and then the source in which you found it. For example:

It’s advisable to avoid indirect citations wherever possible, because they suggest you don’t have full knowledge of the sources you’re citing. Only use an indirect citation if you can’t reasonably gain access to the original source.

In Harvard style referencing , to distinguish between two sources by the same author that were published in the same year, you add a different letter after the year for each source:

  • (Smith, 2019a)
  • (Smith, 2019b)

Add ‘a’ to the first one you cite, ‘b’ to the second, and so on. Do the same in your bibliography or reference list .

To create a hanging indent for your bibliography or reference list :

  • Highlight all the entries
  • Click on the arrow in the bottom-right corner of the ‘Paragraph’ tab in the top menu.
  • In the pop-up window, under ‘Special’ in the ‘Indentation’ section, use the drop-down menu to select ‘Hanging’.
  • Then close the window with ‘OK’.

Though the terms are sometimes used interchangeably, there is a difference in meaning:

  • A reference list only includes sources cited in the text – every entry corresponds to an in-text citation .
  • A bibliography also includes other sources which were consulted during the research but not cited.

It’s important to assess the reliability of information found online. Look for sources from established publications and institutions with expertise (e.g. peer-reviewed journals and government agencies).

The CRAAP test (currency, relevance, authority, accuracy, purpose) can aid you in assessing sources, as can our list of credible sources . You should generally avoid citing websites like Wikipedia that can be edited by anyone – instead, look for the original source of the information in the “References” section.

You can generally omit page numbers in your in-text citations of online sources which don’t have them. But when you quote or paraphrase a specific passage from a particularly long online source, it’s useful to find an alternate location marker.

For text-based sources, you can use paragraph numbers (e.g. ‘para. 4’) or headings (e.g. ‘under “Methodology”’). With video or audio sources, use a timestamp (e.g. ‘10:15’).

In the acknowledgements of your thesis or dissertation, you should first thank those who helped you academically or professionally, such as your supervisor, funders, and other academics.

Then you can include personal thanks to friends, family members, or anyone else who supported you during the process.

Yes, it’s important to thank your supervisor(s) in the acknowledgements section of your thesis or dissertation .

Even if you feel your supervisor did not contribute greatly to the final product, you still should acknowledge them, if only for a very brief thank you. If you do not include your supervisor, it may be seen as a snub.

The acknowledgements are generally included at the very beginning of your thesis or dissertation, directly after the title page and before the abstract .

In a thesis or dissertation, the acknowledgements should usually be no longer than one page. There is no minimum length.

You may acknowledge God in your thesis or dissertation acknowledgements , but be sure to follow academic convention by also thanking the relevant members of academia, as well as family, colleagues, and friends who helped you.

All level 1 and 2 headings should be included in your table of contents . That means the titles of your chapters and the main sections within them.

The contents should also include all appendices and the lists of tables and figures, if applicable, as well as your reference list .

Do not include the acknowledgements or abstract   in the table of contents.

To automatically insert a table of contents in Microsoft Word, follow these steps:

  • Apply heading styles throughout the document.
  • In the references section in the ribbon, locate the Table of Contents group.
  • Click the arrow next to the Table of Contents icon and select Custom Table of Contents.
  • Select which levels of headings you would like to include in the table of contents.

Make sure to update your table of contents if you move text or change headings. To update, simply right click and select Update Field.

The table of contents in a thesis or dissertation always goes between your abstract and your introduction.

An abbreviation is a shortened version of an existing word, such as Dr for Doctor. In contrast, an acronym uses the first letter of each word to create a wholly new word, such as UNESCO (an acronym for the United Nations Educational, Scientific and Cultural Organization).

Your dissertation sometimes contains a list of abbreviations .

As a rule of thumb, write the explanation in full the first time you use an acronym or abbreviation. You can then proceed with the shortened version. However, if the abbreviation is very common (like UK or PC), then you can just use the abbreviated version straight away.

Be sure to add each abbreviation in your list of abbreviations !

If you only used a few abbreviations in your thesis or dissertation, you don’t necessarily need to include a list of abbreviations .

If your abbreviations are numerous, or if you think they won’t be known to your audience, it’s never a bad idea to add one. They can also improve readability, minimising confusion about abbreviations unfamiliar to your reader.

A list of abbreviations is a list of all the abbreviations you used in your thesis or dissertation. It should appear at the beginning of your document, immediately after your table of contents . It should always be in alphabetical order.

Fishbone diagrams have a few different names that are used interchangeably, including herringbone diagram, cause-and-effect diagram, and Ishikawa diagram.

These are all ways to refer to the same thing– a problem-solving approach that uses a fish-shaped diagram to model possible root causes of problems and troubleshoot solutions.

Fishbone diagrams (also called herringbone diagrams, cause-and-effect diagrams, and Ishikawa diagrams) are most popular in fields of quality management. They are also commonly used in nursing and healthcare, or as a brainstorming technique for students.

Some synonyms and near synonyms of among include:

  • In the company of
  • In the middle of
  • Surrounded by

Some synonyms and near synonyms of between  include:

  • In the space separating
  • In the time separating

In spite of   is a preposition used to mean ‘ regardless of ‘, ‘notwithstanding’, or ‘even though’.

It’s always used in a subordinate clause to contrast with the information given in the main clause of a sentence (e.g., ‘Amy continued to watch TV, in spite of the time’).

Despite   is a preposition used to mean ‘ regardless of ‘, ‘notwithstanding’, or ‘even though’.

It’s used in a subordinate clause to contrast with information given in the main clause of a sentence (e.g., ‘Despite the stress, Joe loves his job’).

‘Log in’ is a phrasal verb meaning ‘connect to an electronic device, system, or app’. The preposition ‘to’ is often used directly after the verb; ‘in’ and ‘to’ should be written as two separate words (e.g., ‘ log in to the app to update privacy settings’).

‘Log into’ is sometimes used instead of ‘log in to’, but this is generally considered incorrect (as is ‘login to’).

Some synonyms and near synonyms of ensure include:

  • Make certain

Some synonyms and near synonyms of assure  include:

Rest assured is an expression meaning ‘you can be certain’ (e.g., ‘Rest assured, I will find your cat’). ‘Assured’ is the adjectival form of the verb assure , meaning ‘convince’ or ‘persuade’.

Some synonyms and near synonyms for council include:

There are numerous synonyms and near synonyms for the two meanings of counsel :

AI writing tools can be used to perform a variety of tasks.

Generative AI writing tools (like ChatGPT ) generate text based on human inputs and can be used for interactive learning, to provide feedback, or to generate research questions or outlines.

These tools can also be used to paraphrase or summarise text or to identify grammar and punctuation mistakes. Y ou can also use Scribbr’s free paraphrasing tool , summarising tool , and grammar checker , which are designed specifically for these purposes.

Using AI writing tools (like ChatGPT ) to write your essay is usually considered plagiarism and may result in penalisation, unless it is allowed by your university. Text generated by AI tools is based on existing texts and therefore cannot provide unique insights. Furthermore, these outputs sometimes contain factual inaccuracies or grammar mistakes.

However, AI writing tools can be used effectively as a source of feedback and inspiration for your writing (e.g., to generate research questions ). Other AI tools, like grammar checkers, can help identify and eliminate grammar and punctuation mistakes to enhance your writing.

The Scribbr Knowledge Base is a collection of free resources to help you succeed in academic research, writing, and citation. Every week, we publish helpful step-by-step guides, clear examples, simple templates, engaging videos, and more.

The Knowledge Base is for students at all levels. Whether you’re writing your first essay, working on your bachelor’s or master’s dissertation, or getting to grips with your PhD research, we’ve got you covered.

As well as the Knowledge Base, Scribbr provides many other tools and services to support you in academic writing and citation:

  • Create your citations and manage your reference list with our free Reference Generators in APA and MLA style.
  • Scan your paper for in-text citation errors and inconsistencies with our innovative APA Citation Checker .
  • Avoid accidental plagiarism with our reliable Plagiarism Checker .
  • Polish your writing and get feedback on structure and clarity with our Proofreading & Editing services .

Yes! We’re happy for educators to use our content, and we’ve even adapted some of our articles into ready-made lecture slides .

You are free to display, distribute, and adapt Scribbr materials in your classes or upload them in private learning environments like Blackboard. We only ask that you credit Scribbr for any content you use.

We’re always striving to improve the Knowledge Base. If you have an idea for a topic we should cover, or you notice a mistake in any of our articles, let us know by emailing [email protected] .

The consequences of plagiarism vary depending on the type of plagiarism and the context in which it occurs. For example, submitting a whole paper by someone else will have the most severe consequences, while accidental citation errors are considered less serious.

If you’re a student, then you might fail the course, be suspended or expelled, or be obligated to attend a workshop on plagiarism. It depends on whether it’s your first offence or you’ve done it before.

As an academic or professional, plagiarising seriously damages your reputation. You might also lose your research funding or your job, and you could even face legal consequences for copyright infringement.

Paraphrasing without crediting the original author is a form of plagiarism , because you’re presenting someone else’s ideas as if they were your own.

However, paraphrasing is not plagiarism if you correctly reference the source . This means including an in-text referencing and a full reference , formatted according to your required citation style (e.g., Harvard , Vancouver ).

As well as referencing your source, make sure that any paraphrased text is completely rewritten in your own words.

Accidental plagiarism is one of the most common examples of plagiarism . Perhaps you forgot to cite a source, or paraphrased something a bit too closely. Maybe you can’t remember where you got an idea from, and aren’t totally sure if it’s original or not.

These all count as plagiarism, even though you didn’t do it on purpose. When in doubt, make sure you’re citing your sources . Also consider running your work through a plagiarism checker tool prior to submission, which work by using advanced database software to scan for matches between your text and existing texts.

Scribbr’s Plagiarism Checker takes less than 10 minutes and can help you turn in your paper with confidence.

The accuracy depends on the plagiarism checker you use. Per our in-depth research , Scribbr is the most accurate plagiarism checker. Many free plagiarism checkers fail to detect all plagiarism or falsely flag text as plagiarism.

Plagiarism checkers work by using advanced database software to scan for matches between your text and existing texts. Their accuracy is determined by two factors: the algorithm (which recognises the plagiarism) and the size of the database (with which your document is compared).

To avoid plagiarism when summarising an article or other source, follow these two rules:

  • Write the summary entirely in your own words by   paraphrasing the author’s ideas.
  • Reference the source with an in-text citation and a full reference so your reader can easily find the original text.

Plagiarism can be detected by your professor or readers if the tone, formatting, or style of your text is different in different parts of your paper, or if they’re familiar with the plagiarised source.

Many universities also use   plagiarism detection software like Turnitin’s, which compares your text to a large database of other sources, flagging any similarities that come up.

It can be easier than you think to commit plagiarism by accident. Consider using a   plagiarism checker prior to submitting your essay to ensure you haven’t missed any citations.

Some examples of plagiarism include:

  • Copying and pasting a Wikipedia article into the body of an assignment
  • Quoting a source without including a citation
  • Not paraphrasing a source properly (e.g. maintaining wording too close to the original)
  • Forgetting to cite the source of an idea

The most surefire way to   avoid plagiarism is to always cite your sources . When in doubt, cite!

Global plagiarism means taking an entire work written by someone else and passing it off as your own. This can include getting someone else to write an essay or assignment for you, or submitting a text you found online as your own work.

Global plagiarism is one of the most serious types of plagiarism because it involves deliberately and directly lying about the authorship of a work. It can have severe consequences for students and professionals alike.

Verbatim plagiarism means copying text from a source and pasting it directly into your own document without giving proper credit.

If the structure and the majority of the words are the same as in the original source, then you are committing verbatim plagiarism. This is the case even if you delete a few words or replace them with synonyms.

If you want to use an author’s exact words, you need to quote the original source by putting the copied text in quotation marks and including an   in-text citation .

Patchwork plagiarism , also called mosaic plagiarism, means copying phrases, passages, or ideas from various existing sources and combining them to create a new text. This includes slightly rephrasing some of the content, while keeping many of the same words and the same structure as the original.

While this type of plagiarism is more insidious than simply copying and pasting directly from a source, plagiarism checkers like Turnitin’s can still easily detect it.

To avoid plagiarism in any form, remember to reference your sources .

Yes, reusing your own work without citation is considered self-plagiarism . This can range from resubmitting an entire assignment to reusing passages or data from something you’ve handed in previously.

Self-plagiarism often has the same consequences as other types of plagiarism . If you want to reuse content you wrote in the past, make sure to check your university’s policy or consult your professor.

If you are reusing content or data you used in a previous assignment, make sure to cite yourself. You can cite yourself the same way you would cite any other source: simply follow the directions for the citation style you are using.

Keep in mind that reusing prior content can be considered self-plagiarism , so make sure you ask your instructor or consult your university’s handbook prior to doing so.

Most institutions have an internal database of previously submitted student assignments. Turnitin can check for self-plagiarism by comparing your paper against this database. If you’ve reused parts of an assignment you already submitted, it will flag any similarities as potential plagiarism.

Online plagiarism checkers don’t have access to your institution’s database, so they can’t detect self-plagiarism of unpublished work. If you’re worried about accidentally self-plagiarising, you can use Scribbr’s Self-Plagiarism Checker to upload your unpublished documents and check them for similarities.

Plagiarism has serious consequences and can be illegal in certain scenarios.

While most of the time plagiarism in an undergraduate setting is not illegal, plagiarism or self-plagiarism in a professional academic setting can lead to legal action, including copyright infringement and fraud. Many scholarly journals do not allow you to submit the same work to more than one journal, and if you do not credit a coauthor, you could be legally defrauding them.

Even if you aren’t breaking the law, plagiarism can seriously impact your academic career. While the exact consequences of plagiarism vary by institution and severity, common consequences include a lower grade, automatically failing a course, academic suspension or probation, and even expulsion.

Self-plagiarism means recycling work that you’ve previously published or submitted as an assignment. It’s considered academic dishonesty to present something as brand new when you’ve already gotten credit and perhaps feedback for it in the past.

If you want to refer to ideas or data from previous work, be sure to cite yourself.

Academic integrity means being honest, ethical, and thorough in your academic work. To maintain academic integrity, you should avoid misleading your readers about any part of your research and refrain from offences like plagiarism and contract cheating, which are examples of academic misconduct.

Academic dishonesty refers to deceitful or misleading behavior in an academic setting. Academic dishonesty can occur intentionally or unintentionally, and it varies in severity.

It can encompass paying for a pre-written essay, cheating on an exam, or committing plagiarism . It can also include helping others cheat, copying a friend’s homework answers, or even pretending to be sick to miss an exam.

Academic dishonesty doesn’t just occur in a classroom setting, but also in research and other academic-adjacent fields.

Consequences of academic dishonesty depend on the severity of the offence and your institution’s policy. They can range from a warning for a first offence to a failing grade in a course to expulsion from your university.

For those in certain fields, such as nursing, engineering, or lab sciences, not learning fundamentals properly can directly impact the health and safety of others. For those working in academia or research, academic dishonesty impacts your professional reputation, leading others to doubt your future work.

Academic dishonesty can be intentional or unintentional, ranging from something as simple as claiming to have read something you didn’t to copying your neighbour’s answers on an exam.

You can commit academic dishonesty with the best of intentions, such as helping a friend cheat on a paper. Severe academic dishonesty can include buying a pre-written essay or the answers to a multiple-choice test, or falsifying a medical emergency to avoid taking a final exam.

Plagiarism means presenting someone else’s work as your own without giving proper credit to the original author. In academic writing, plagiarism involves using words, ideas, or information from a source without including a citation .

Plagiarism can have serious consequences , even when it’s done accidentally. To avoid plagiarism, it’s important to keep track of your sources and cite them correctly.

Common knowledge does not need to be cited. However, you should be extra careful when deciding what counts as common knowledge.

Common knowledge encompasses information that the average educated reader would accept as true without needing the extra validation of a source or citation.

Common knowledge should be widely known, undisputed, and easily verified. When in doubt, always cite your sources.

Most online plagiarism checkers only have access to public databases, whose software doesn’t allow you to compare two documents for plagiarism.

However, in addition to our Plagiarism Checker , Scribbr also offers an Self-Plagiarism Checker . This is an add-on tool that lets you compare your paper with unpublished or private documents. This way you can rest assured that you haven’t unintentionally plagiarised or self-plagiarised .

Compare two sources for plagiarism

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

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

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

  • Prepare and organise your data.
  • Review and explore your data.
  • Develop a data coding system.
  • Assign codes to the data.
  • Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

There are five common approaches to qualitative research :

  • Grounded theory involves collecting data in order to develop new theories.
  • Ethnography involves immersing yourself in a group or organisation to understand its culture.
  • Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
  • Phenomenological research involves investigating phenomena through people’s lived experiences.
  • Action research links theory and practice in several cycles to drive innovative changes.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

Operationalisation means turning abstract conceptual ideas into measurable observations.

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

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

Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.

Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . Mixed methods research always uses triangulation.

These are four of the most common mixed methods designs :

  • Convergent parallel: Quantitative and qualitative data are collected at the same time and analysed separately. After both analyses are complete, compare your results to draw overall conclusions. 
  • Embedded: Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.
  • Explanatory sequential: Quantitative data is collected and analysed first, followed by qualitative data. You can use this design if you think your qualitative data will explain and contextualise your quantitative findings.
  • Exploratory sequential: Qualitative data is collected and analysed first, followed by quantitative data. You can use this design if you think the quantitative data will confirm or validate your qualitative findings.

An observational study could be a good fit for your research if your research question is based on things you observe. If you have ethical, logistical, or practical concerns that make an experimental design challenging, consider an observational study. Remember that in an observational study, it is critical that there be no interference or manipulation of the research subjects. Since it’s not an experiment, there are no control or treatment groups either.

The key difference between observational studies and experiments is that, done correctly, an observational study will never influence the responses or behaviours of participants. Experimental designs will have a treatment condition applied to at least a portion of participants.

Exploratory research explores the main aspects of a new or barely researched question.

Explanatory research explains the causes and effects of an already widely researched question.

Experimental designs are a set of procedures that you plan in order to examine the relationship between variables that interest you.

To design a successful experiment, first identify:

  • A testable hypothesis
  • One or more independent variables that you will manipulate
  • One or more dependent variables that you will measure

When designing the experiment, first decide:

  • How your variable(s) will be manipulated
  • How you will control for any potential confounding or lurking variables
  • How many subjects you will include
  • How you will assign treatments to your subjects

There are four main types of triangulation :

  • Data triangulation : Using data from different times, spaces, and people
  • Investigator triangulation : Involving multiple researchers in collecting or analysing data
  • Theory triangulation : Using varying theoretical perspectives in your research
  • Methodological triangulation : Using different methodologies to approach the same topic

Triangulation can help:

  • Reduce bias that comes from using a single method, theory, or investigator
  • Enhance validity by approaching the same topic with different tools
  • Establish credibility by giving you a complete picture of the research problem

But triangulation can also pose problems:

  • It’s time-consuming and labour-intensive, often involving an interdisciplinary team.
  • Your results may be inconsistent or even contradictory.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word ‘between’ means that you’re comparing different conditions between groups, while the word ‘within’ means you’re comparing different conditions within the same group.

A quasi-experiment is a type of research design that attempts to establish a cause-and-effect relationship. The main difference between this and a true experiment is that the groups are not randomly assigned.

In experimental research, random assignment is a way of placing participants from your sample into different groups using randomisation. With this method, every member of the sample has a known or equal chance of being placed in a control group or an experimental group.

Quasi-experimental design is most useful in situations where it would be unethical or impractical to run a true experiment .

Quasi-experiments have lower internal validity than true experiments, but they often have higher external validity  as they can use real-world interventions instead of artificial laboratory settings.

Within-subjects designs have many potential threats to internal validity , but they are also very statistically powerful .

Advantages:

  • Only requires small samples
  • Statistically powerful
  • Removes the effects of individual differences on the outcomes

Disadvantages:

  • Internal validity threats reduce the likelihood of establishing a direct relationship between variables
  • Time-related effects, such as growth, can influence the outcomes
  • Carryover effects mean that the specific order of different treatments affect the outcomes

Yes. Between-subjects and within-subjects designs can be combined in a single study when you have two or more independent variables (a factorial design). In a mixed factorial design, one variable is altered between subjects and another is altered within subjects.

In a factorial design, multiple independent variables are tested.

If you test two variables, each level of one independent variable is combined with each level of the other independent variable to create different conditions.

While a between-subjects design has fewer threats to internal validity , it also requires more participants for high statistical power than a within-subjects design .

  • Prevents carryover effects of learning and fatigue.
  • Shorter study duration.
  • Needs larger samples for high power.
  • Uses more resources to recruit participants, administer sessions, cover costs, etc.
  • Individual differences may be an alternative explanation for results.

Samples are used to make inferences about populations . Samples are easier to collect data from because they are practical, cost-effective, convenient, and manageable.

Probability sampling means that every member of the target population has a known chance of being included in the sample.

Probability sampling methods include simple random sampling , systematic sampling , stratified sampling , and cluster sampling .

In non-probability sampling , the sample is selected based on non-random criteria, and not every member of the population has a chance of being included.

Common non-probability sampling methods include convenience sampling , voluntary response sampling, purposive sampling , snowball sampling , and quota sampling .

In multistage sampling , or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage.

This method is often used to collect data from a large, geographically spread group of people in national surveys, for example. You take advantage of hierarchical groupings (e.g., from county to city to neighbourhood) to create a sample that’s less expensive and time-consuming to collect data from.

Sampling bias occurs when some members of a population are systematically more likely to be selected in a sample than others.

Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population . Each member of the population has an equal chance of being selected. Data are then collected from as large a percentage as possible of this random subset.

The American Community Survey  is an example of simple random sampling . In order to collect detailed data on the population of the US, the Census Bureau officials randomly select 3.5 million households per year and use a variety of methods to convince them to fill out the survey.

If properly implemented, simple random sampling is usually the best sampling method for ensuring both internal and external validity . However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied,

If you have a list of every member of the population and the ability to reach whichever members are selected, you can use simple random sampling.

Cluster sampling is more time- and cost-efficient than other probability sampling methods , particularly when it comes to large samples spread across a wide geographical area.

However, it provides less statistical certainty than other methods, such as simple random sampling , because it is difficult to ensure that your clusters properly represent the population as a whole.

There are three types of cluster sampling : single-stage, double-stage and multi-stage clustering. In all three types, you first divide the population into clusters, then randomly select clusters for use in your sample.

  • In single-stage sampling , you collect data from every unit within the selected clusters.
  • In double-stage sampling , you select a random sample of units from within the clusters.
  • In multi-stage sampling , you repeat the procedure of randomly sampling elements from within the clusters until you have reached a manageable sample.

Cluster sampling is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample.

The clusters should ideally each be mini-representations of the population as a whole.

In multistage sampling , you can use probability or non-probability sampling methods.

For a probability sample, you have to probability sampling at every stage. You can mix it up by using simple random sampling , systematic sampling , or stratified sampling to select units at different stages, depending on what is applicable and relevant to your study.

Multistage sampling can simplify data collection when you have large, geographically spread samples, and you can obtain a probability sample without a complete sampling frame.

But multistage sampling may not lead to a representative sample, and larger samples are needed for multistage samples to achieve the statistical properties of simple random samples .

In stratified sampling , researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment).

Once divided, each subgroup is randomly sampled using another probability sampling method .

You should use stratified sampling when your sample can be divided into mutually exclusive and exhaustive subgroups that you believe will take on different mean values for the variable that you’re studying.

Using stratified sampling will allow you to obtain more precise (with lower variance ) statistical estimates of whatever you are trying to measure.

For example, say you want to investigate how income differs based on educational attainment, but you know that this relationship can vary based on race. Using stratified sampling, you can ensure you obtain a large enough sample from each racial group, allowing you to draw more precise conclusions.

Yes, you can create a stratified sample using multiple characteristics, but you must ensure that every participant in your study belongs to one and only one subgroup. In this case, you multiply the numbers of subgroups for each characteristic to get the total number of groups.

For example, if you were stratifying by location with three subgroups (urban, rural, or suburban) and marital status with five subgroups (single, divorced, widowed, married, or partnered), you would have 3 × 5 = 15 subgroups.

There are three key steps in systematic sampling :

  • Define and list your population , ensuring that it is not ordered in a cyclical or periodic order.
  • Decide on your sample size and calculate your interval, k , by dividing your population by your target sample size.
  • Choose every k th member of the population as your sample.

Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval – for example, by selecting every 15th person on a list of the population. If the population is in a random order, this can imitate the benefits of simple random sampling .

Populations are used when a research question requires data from every member of the population. This is usually only feasible when the population is small and easily accessible.

A statistic refers to measures about the sample , while a parameter refers to measures about the population .

A sampling error is the difference between a population parameter and a sample statistic .

There are eight threats to internal validity : history, maturation, instrumentation, testing, selection bias , regression to the mean, social interaction, and attrition .

Internal validity is the extent to which you can be confident that a cause-and-effect relationship established in a study cannot be explained by other factors.

Attrition bias is a threat to internal validity . In experiments, differential rates of attrition between treatment and control groups can skew results.

This bias can affect the relationship between your independent and dependent variables . It can make variables appear to be correlated when they are not, or vice versa.

The external validity of a study is the extent to which you can generalise your findings to different groups of people, situations, and measures.

The two types of external validity are population validity (whether you can generalise to other groups of people) and ecological validity (whether you can generalise to other situations and settings).

There are seven threats to external validity : selection bias , history, experimenter effect, Hawthorne effect , testing effect, aptitude-treatment, and situation effect.

Attrition bias can skew your sample so that your final sample differs significantly from your original sample. Your sample is biased because some groups from your population are underrepresented.

With a biased final sample, you may not be able to generalise your findings to the original population that you sampled from, so your external validity is compromised.

Construct validity is about how well a test measures the concept it was designed to evaluate. It’s one of four types of measurement validity , which includes construct validity, face validity , and criterion validity.

There are two subtypes of construct validity.

  • Convergent validity : The extent to which your measure corresponds to measures of related constructs
  • Discriminant validity: The extent to which your measure is unrelated or negatively related to measures of distinct constructs

When designing or evaluating a measure, construct validity helps you ensure you’re actually measuring the construct you’re interested in. If you don’t have construct validity, you may inadvertently measure unrelated or distinct constructs and lose precision in your research.

Construct validity is often considered the overarching type of measurement validity ,  because it covers all of the other types. You need to have face validity , content validity, and criterion validity to achieve construct validity.

Statistical analyses are often applied to test validity with data from your measures. You test convergent validity and discriminant validity with correlations to see if results from your test are positively or negatively related to those of other established tests.

You can also use regression analyses to assess whether your measure is actually predictive of outcomes that you expect it to predict theoretically. A regression analysis that supports your expectations strengthens your claim of construct validity .

Face validity is about whether a test appears to measure what it’s supposed to measure. This type of validity is concerned with whether a measure seems relevant and appropriate for what it’s assessing only on the surface.

Face validity is important because it’s a simple first step to measuring the overall validity of a test or technique. It’s a relatively intuitive, quick, and easy way to start checking whether a new measure seems useful at first glance.

Good face validity means that anyone who reviews your measure says that it seems to be measuring what it’s supposed to. With poor face validity, someone reviewing your measure may be left confused about what you’re measuring and why you’re using this method.

It’s often best to ask a variety of people to review your measurements. You can ask experts, such as other researchers, or laypeople, such as potential participants, to judge the face validity of tests.

While experts have a deep understanding of research methods , the people you’re studying can provide you with valuable insights you may have missed otherwise.

There are many different types of inductive reasoning that people use formally or informally.

Here are a few common types:

  • Inductive generalisation : You use observations about a sample to come to a conclusion about the population it came from.
  • Statistical generalisation: You use specific numbers about samples to make statements about populations.
  • Causal reasoning: You make cause-and-effect links between different things.
  • Sign reasoning: You make a conclusion about a correlational relationship between different things.
  • Analogical reasoning: You make a conclusion about something based on its similarities to something else.

Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.

Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.

In inductive research , you start by making observations or gathering data. Then, you take a broad scan of your data and search for patterns. Finally, you make general conclusions that you might incorporate into theories.

Inductive reasoning is a method of drawing conclusions by going from the specific to the general. It’s usually contrasted with deductive reasoning, where you proceed from general information to specific conclusions.

Inductive reasoning is also called inductive logic or bottom-up reasoning.

Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning , where you start with specific observations and form general conclusions.

Deductive reasoning is also called deductive logic.

Deductive reasoning is commonly used in scientific research, and it’s especially associated with quantitative research .

In research, you might have come across something called the hypothetico-deductive method . It’s the scientific method of testing hypotheses to check whether your predictions are substantiated by real-world data.

A dependent variable is what changes as a result of the independent variable manipulation in experiments . It’s what you’re interested in measuring, and it ‘depends’ on your independent variable.

In statistics, dependent variables are also called:

  • Response variables (they respond to a change in another variable)
  • Outcome variables (they represent the outcome you want to measure)
  • Left-hand-side variables (they appear on the left-hand side of a regression equation)

An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called ‘independent’ because it’s not influenced by any other variables in the study.

Independent variables are also called:

  • Explanatory variables (they explain an event or outcome)
  • Predictor variables (they can be used to predict the value of a dependent variable)
  • Right-hand-side variables (they appear on the right-hand side of a regression equation)

A correlation is usually tested for two variables at a time, but you can test correlations between three or more variables.

On graphs, the explanatory variable is conventionally placed on the x -axis, while the response variable is placed on the y -axis.

  • If you have quantitative variables , use a scatterplot or a line graph.
  • If your response variable is categorical, use a scatterplot or a line graph.
  • If your explanatory variable is categorical, use a bar graph.

The term ‘ explanatory variable ‘ is sometimes preferred over ‘ independent variable ‘ because, in real-world contexts, independent variables are often influenced by other variables. This means they aren’t totally independent.

Multiple independent variables may also be correlated with each other, so ‘explanatory variables’ is a more appropriate term.

The difference between explanatory and response variables is simple:

  • An explanatory variable is the expected cause, and it explains the results.
  • A response variable is the expected effect, and it responds to other variables.

There are 4 main types of extraneous variables :

  • Demand characteristics : Environmental cues that encourage participants to conform to researchers’ expectations
  • Experimenter effects : Unintentional actions by researchers that influence study outcomes
  • Situational variables : Eenvironmental variables that alter participants’ behaviours
  • Participant variables : Any characteristic or aspect of a participant’s background that could affect study results

An extraneous variable is any variable that you’re not investigating that can potentially affect the dependent variable of your research study.

A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable.

‘Controlling for a variable’ means measuring extraneous variables and accounting for them statistically to remove their effects on other variables.

Researchers often model control variable data along with independent and dependent variable data in regression analyses and ANCOVAs . That way, you can isolate the control variable’s effects from the relationship between the variables of interest.

Control variables help you establish a correlational or causal relationship between variables by enhancing internal validity .

If you don’t control relevant extraneous variables , they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable .

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

In statistics, ordinal and nominal variables are both considered categorical variables .

Even though ordinal data can sometimes be numerical, not all mathematical operations can be performed on them.

In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports).

The process of turning abstract concepts into measurable variables and indicators is called operationalisation .

There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control, and randomisation.

In restriction , you restrict your sample by only including certain subjects that have the same values of potential confounding variables.

In matching , you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable .

In statistical control , you include potential confounders as variables in your regression .

In randomisation , you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

To ensure the internal validity of your research, you must consider the impact of confounding variables. If you fail to account for them, you might over- or underestimate the causal relationship between your independent and dependent variables , or even find a causal relationship where none exists.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both.

You want to find out how blood sugar levels are affected by drinking diet cola and regular cola, so you conduct an experiment .

  • The type of cola – diet or regular – is the independent variable .
  • The level of blood sugar that you measure is the dependent variable – it changes depending on the type of cola.

Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.

Quantitative variables are any variables where the data represent amounts (e.g. height, weight, or age).

Categorical variables are any variables where the data represent groups. This includes rankings (e.g. finishing places in a race), classifications (e.g. brands of cereal), and binary outcomes (e.g. coin flips).

You need to know what type of variables you are working with to choose the right statistical test for your data and interpret your results .

Discrete and continuous variables are two types of quantitative variables :

  • Discrete variables represent counts (e.g., the number of objects in a collection).
  • Continuous variables represent measurable amounts (e.g., water volume or weight).

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause , while a dependent variable is the effect .

In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:

  • The  independent variable  is the amount of nutrients added to the crop field.
  • The  dependent variable is the biomass of the crops at harvest time.

Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design .

Including mediators and moderators in your research helps you go beyond studying a simple relationship between two variables for a fuller picture of the real world. They are important to consider when studying complex correlational or causal relationships.

Mediators are part of the causal pathway of an effect, and they tell you how or why an effect takes place. Moderators usually help you judge the external validity of your study by identifying the limitations of when the relationship between variables holds.

If something is a mediating variable :

  • It’s caused by the independent variable
  • It influences the dependent variable
  • When it’s taken into account, the statistical correlation between the independent and dependent variables is higher than when it isn’t considered

A confounder is a third variable that affects variables of interest and makes them seem related when they are not. In contrast, a mediator is the mechanism of a relationship between two variables: it explains the process by which they are related.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

When conducting research, collecting original data has significant advantages:

  • You can tailor data collection to your specific research aims (e.g., understanding the needs of your consumers or user testing your website).
  • You can control and standardise the process for high reliability and validity (e.g., choosing appropriate measurements and sampling methods ).

However, there are also some drawbacks: data collection can be time-consuming, labour-intensive, and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

A structured interview is a data collection method that relies on asking questions in a set order to collect data on a topic. They are often quantitative in nature. Structured interviews are best used when:

  • You already have a very clear understanding of your topic. Perhaps significant research has already been conducted, or you have done some prior research yourself, but you already possess a baseline for designing strong structured questions.
  • You are constrained in terms of time or resources and need to analyse your data quickly and efficiently
  • Your research question depends on strong parity between participants, with environmental conditions held constant

More flexible interview options include semi-structured interviews , unstructured interviews , and focus groups .

The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) influences the responses given by the interviewee.

There is a risk of an interviewer effect in all types of interviews , but it can be mitigated by writing really high-quality interview questions.

A semi-structured interview is a blend of structured and unstructured types of interviews. Semi-structured interviews are best used when:

  • You have prior interview experience. Spontaneous questions are deceptively challenging, and it’s easy to accidentally ask a leading question or make a participant uncomfortable.
  • Your research question is exploratory in nature. Participant answers can guide future research questions and help you develop a more robust knowledge base for future research.

An unstructured interview is the most flexible type of interview, but it is not always the best fit for your research topic.

Unstructured interviews are best used when:

  • You are an experienced interviewer and have a very strong background in your research topic, since it is challenging to ask spontaneous, colloquial questions
  • Your research question is exploratory in nature. While you may have developed hypotheses, you are open to discovering new or shifting viewpoints through the interview process.
  • You are seeking descriptive data, and are ready to ask questions that will deepen and contextualise your initial thoughts and hypotheses
  • Your research depends on forming connections with your participants and making them feel comfortable revealing deeper emotions, lived experiences, or thoughts

The four most common types of interviews are:

  • Structured interviews : The questions are predetermined in both topic and order.
  • Semi-structured interviews : A few questions are predetermined, but other questions aren’t planned.
  • Unstructured interviews : None of the questions are predetermined.
  • Focus group interviews : The questions are presented to a group instead of one individual.

A focus group is a research method that brings together a small group of people to answer questions in a moderated setting. The group is chosen due to predefined demographic traits, and the questions are designed to shed light on a topic of interest. It is one of four types of interviews .

Social desirability bias is the tendency for interview participants to give responses that will be viewed favourably by the interviewer or other participants. It occurs in all types of interviews and surveys , but is most common in semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias can be mitigated by ensuring participants feel at ease and comfortable sharing their views. Make sure to pay attention to your own body language and any physical or verbal cues, such as nodding or widening your eyes.

This type of bias in research can also occur in observations if the participants know they’re being observed. They might alter their behaviour accordingly.

As a rule of thumb, questions related to thoughts, beliefs, and feelings work well in focus groups . Take your time formulating strong questions, paying special attention to phrasing. Be careful to avoid leading questions , which can bias your responses.

Overall, your focus group questions should be:

  • Open-ended and flexible
  • Impossible to answer with ‘yes’ or ‘no’ (questions that start with ‘why’ or ‘how’ are often best)
  • Unambiguous, getting straight to the point while still stimulating discussion
  • Unbiased and neutral

The third variable and directionality problems are two main reasons why correlation isn’t causation .

The third variable problem means that a confounding variable affects both variables to make them seem causally related when they are not.

The directionality problem is when two variables correlate and might actually have a causal relationship, but it’s impossible to conclude which variable causes changes in the other.

Controlled experiments establish causality, whereas correlational studies only show associations between variables.

  • In an experimental design , you manipulate an independent variable and measure its effect on a dependent variable. Other variables are controlled so they can’t impact the results.
  • In a correlational design , you measure variables without manipulating any of them. You can test whether your variables change together, but you can’t be sure that one variable caused a change in another.

In general, correlational research is high in external validity while experimental research is high in internal validity .

A correlation coefficient is a single number that describes the strength and direction of the relationship between your variables.

Different types of correlation coefficients might be appropriate for your data based on their levels of measurement and distributions . The Pearson product-moment correlation coefficient (Pearson’s r ) is commonly used to assess a linear relationship between two quantitative variables.

A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. It’s a non-experimental type of quantitative research .

A correlation reflects the strength and/or direction of the association between two or more variables.

  • A positive correlation means that both variables change in the same direction.
  • A negative correlation means that the variables change in opposite directions.
  • A zero correlation means there’s no relationship between the variables.

Longitudinal studies can last anywhere from weeks to decades, although they tend to be at least a year long.

The 1970 British Cohort Study , which has collected data on the lives of 17,000 Brits since their births in 1970, is one well-known example of a longitudinal study .

Longitudinal studies are better to establish the correct sequence of events, identify changes over time, and provide insight into cause-and-effect relationships, but they also tend to be more expensive and time-consuming than other types of studies.

Longitudinal studies and cross-sectional studies are two different types of research design . In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time.

Cross-sectional studies cannot establish a cause-and-effect relationship or analyse behaviour over a period of time. To investigate cause and effect, you need to do a longitudinal study or an experimental study .

Cross-sectional studies are less expensive and time-consuming than many other types of study. They can provide useful insights into a population’s characteristics and identify correlations for further research.

Sometimes only cross-sectional data are available for analysis; other times your research question may only require a cross-sectional study to answer it.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess. It should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (‘ x affects y because …’).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyse your data.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviours. It is made up of four or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with five or seven possible responses, to capture their degree of agreement.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

A true experiment (aka a controlled experiment) always includes at least one control group that doesn’t receive the experimental treatment.

However, some experiments use a within-subjects design to test treatments without a control group. In these designs, you usually compare one group’s outcomes before and after a treatment (instead of comparing outcomes between different groups).

For strong internal validity , it’s usually best to include a control group if possible. Without a control group, it’s harder to be certain that the outcome was caused by the experimental treatment and not by other variables.

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

In a controlled experiment , all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:

  • A control group that receives a standard treatment, a fake treatment, or no treatment
  • Random assignment of participants to ensure the groups are equivalent

Depending on your study topic, there are various other methods of controlling variables .

Questionnaires can be self-administered or researcher-administered.

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or by post. All questions are standardised so that all respondents receive the same questions with identical wording.

Researcher-administered questionnaires are interviews that take place by phone, in person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

You can organise the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomisation can minimise the bias from order effects.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

Naturalistic observation is a qualitative research method where you record the behaviours of your research subjects in real-world settings. You avoid interfering or influencing anything in a naturalistic observation.

You can think of naturalistic observation as ‘people watching’ with a purpose.

Naturalistic observation is a valuable tool because of its flexibility, external validity , and suitability for topics that can’t be studied in a lab setting.

The downsides of naturalistic observation include its lack of scientific control , ethical considerations , and potential for bias from observers and subjects.

You can use several tactics to minimise observer bias .

  • Use masking (blinding) to hide the purpose of your study from all observers.
  • Triangulate your data with different data collection methods or sources.
  • Use multiple observers and ensure inter-rater reliability.
  • Train your observers to make sure data is consistently recorded between them.
  • Standardise your observation procedures to make sure they are structured and clear.

The observer-expectancy effect occurs when researchers influence the results of their own study through interactions with participants.

Researchers’ own beliefs and expectations about the study results may unintentionally influence participants through demand characteristics .

Observer bias occurs when a researcher’s expectations, opinions, or prejudices influence what they perceive or record in a study. It usually affects studies when observers are aware of the research aims or hypotheses. This type of research bias is also called detection bias or ascertainment bias .

Data cleaning is necessary for valid and appropriate analyses. Dirty data contain inconsistencies or errors , but cleaning your data helps you minimise or resolve these.

Without data cleaning, you could end up with a Type I or II error in your conclusion. These types of erroneous conclusions can be practically significant with important consequences, because they lead to misplaced investments or missed opportunities.

Data cleaning involves spotting and resolving potential data inconsistencies or errors to improve your data quality. An error is any value (e.g., recorded weight) that doesn’t reflect the true value (e.g., actual weight) of something that’s being measured.

In this process, you review, analyse, detect, modify, or remove ‘dirty’ data to make your dataset ‘clean’. Data cleaning is also called data cleansing or data scrubbing.

Data cleaning takes place between data collection and data analyses. But you can use some methods even before collecting data.

For clean data, you should start by designing measures that collect valid data. Data validation at the time of data entry or collection helps you minimize the amount of data cleaning you’ll need to do.

After data collection, you can use data standardisation and data transformation to clean your data. You’ll also deal with any missing values, outliers, and duplicate values.

Clean data are valid, accurate, complete, consistent, unique, and uniform. Dirty data include inconsistencies and errors.

Dirty data can come from any part of the research process, including poor research design , inappropriate measurement materials, or flawed data entry.

Random assignment is used in experiments with a between-groups or independent measures design. In this research design, there’s usually a control group and one or more experimental groups. Random assignment helps ensure that the groups are comparable.

In general, you should always use random assignment in this type of experimental design when it is ethically possible and makes sense for your study topic.

Random selection, or random sampling , is a way of selecting members of a population for your study’s sample.

In contrast, random assignment is a way of sorting the sample into control and experimental groups.

Random sampling enhances the external validity or generalisability of your results, while random assignment improves the internal validity of your study.

To implement random assignment , assign a unique number to every member of your study’s sample .

Then, you can use a random number generator or a lottery method to randomly assign each number to a control or experimental group. You can also do so manually, by flipping a coin or rolling a die to randomly assign participants to groups.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

Explanatory research is used to investigate how or why a phenomenon occurs. Therefore, this type of research is often one of the first stages in the research process , serving as a jumping-off point for future research.

Explanatory research is a research method used to investigate how or why something occurs when only a small amount of information is available pertaining to that topic. It can help you increase your understanding of a given topic.

Blinding means hiding who is assigned to the treatment group and who is assigned to the control group in an experiment .

Blinding is important to reduce bias (e.g., observer bias , demand characteristics ) and ensure a study’s internal validity .

If participants know whether they are in a control or treatment group , they may adjust their behaviour in ways that affect the outcome that researchers are trying to measure. If the people administering the treatment are aware of group assignment, they may treat participants differently and thus directly or indirectly influence the final results.

  • In a single-blind study , only the participants are blinded.
  • In a double-blind study , both participants and experimenters are blinded.
  • In a triple-blind study , the assignment is hidden not only from participants and experimenters, but also from the researchers analysing the data.

Many academic fields use peer review , largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the published manuscript.

However, peer review is also common in non-academic settings. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. It is also widely used in medical and health-related fields as a teaching or quality-of-care measure.

Peer assessment is often used in the classroom as a pedagogical tool. Both receiving feedback and providing it are thought to enhance the learning process, helping students think critically and collaboratively.

Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. It also represents an excellent opportunity to get feedback from renowned experts in your field.

It acts as a first defence, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process.

Peer-reviewed articles are considered a highly credible source due to this stringent process they go through before publication.

In general, the peer review process follows the following steps:

  • First, the author submits the manuscript to the editor.
  • Reject the manuscript and send it back to author, or
  • Send it onward to the selected peer reviewer(s)
  • Next, the peer review process occurs. The reviewer provides feedback, addressing any major or minor issues with the manuscript, and gives their advice regarding what edits should be made.
  • Lastly, the edited manuscript is sent back to the author. They input the edits, and resubmit it to the editor for publication.

Peer review is a process of evaluating submissions to an academic journal. Utilising rigorous criteria, a panel of reviewers in the same subject area decide whether to accept each submission for publication.

For this reason, academic journals are often considered among the most credible sources you can use in a research project – provided that the journal itself is trustworthy and well regarded.

Anonymity means you don’t know who the participants are, while confidentiality means you know who they are but remove identifying information from your research report. Both are important ethical considerations .

You can only guarantee anonymity by not collecting any personally identifying information – for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.

You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals.

Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. It’s a form of academic fraud.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe.

Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.

Scientists and researchers must always adhere to a certain code of conduct when collecting data from others .

These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity.

A systematic review is secondary research because it uses existing research. You don’t collect new data yourself.

The two main types of social desirability bias are:

  • Self-deceptive enhancement (self-deception): The tendency to see oneself in a favorable light without realizing it.
  • Impression managemen t (other-deception): The tendency to inflate one’s abilities or achievement in order to make a good impression on other people.

Demand characteristics are aspects of experiments that may give away the research objective to participants. Social desirability bias occurs when participants automatically try to respond in ways that make them seem likeable in a study, even if it means misrepresenting how they truly feel.

Participants may use demand characteristics to infer social norms or experimenter expectancies and act in socially desirable ways, so you should try to control for demand characteristics wherever possible.

Response bias refers to conditions or factors that take place during the process of responding to surveys, affecting the responses. One type of response bias is social desirability bias .

When your population is large in size, geographically dispersed, or difficult to contact, it’s necessary to use a sampling method .

This allows you to gather information from a smaller part of the population, i.e. the sample, and make accurate statements by using statistical analysis. A few sampling methods include simple random sampling , convenience sampling , and snowball sampling .

Stratified and cluster sampling may look similar, but bear in mind that groups created in cluster sampling are heterogeneous , so the individual characteristics in the cluster vary. In contrast, groups created in stratified sampling are homogeneous , as units share characteristics.

Relatedly, in cluster sampling you randomly select entire groups and include all units of each group in your sample. However, in stratified sampling, you select some units of all groups and include them in your sample. In this way, both methods can ensure that your sample is representative of the target population .

A sampling frame is a list of every member in the entire population . It is important that the sampling frame is as complete as possible, so that your sample accurately reflects your population.

Convenience sampling and quota sampling are both non-probability sampling methods. They both use non-random criteria like availability, geographical proximity, or expert knowledge to recruit study participants.

However, in convenience sampling, you continue to sample units or cases until you reach the required sample size.

In quota sampling, you first need to divide your population of interest into subgroups (strata) and estimate their proportions (quota) in the population. Then you can start your data collection , using convenience sampling to recruit participants, until the proportions in each subgroup coincide with the estimated proportions in the population.

Random sampling or probability sampling is based on random selection. This means that each unit has an equal chance (i.e., equal probability) of being included in the sample.

On the other hand, convenience sampling involves stopping people at random, which means that not everyone has an equal chance of being selected depending on the place, time, or day you are collecting your data.

Stratified sampling and quota sampling both involve dividing the population into subgroups and selecting units from each subgroup. The purpose in both cases is to select a representative sample and/or to allow comparisons between subgroups.

The main difference is that in stratified sampling, you draw a random sample from each subgroup ( probability sampling ). In quota sampling you select a predetermined number or proportion of units, in a non-random manner ( non-probability sampling ).

Snowball sampling is best used in the following cases:

  • If there is no sampling frame available (e.g., people with a rare disease)
  • If the population of interest is hard to access or locate (e.g., people experiencing homelessness)
  • If the research focuses on a sensitive topic (e.g., extra-marital affairs)

Snowball sampling relies on the use of referrals. Here, the researcher recruits one or more initial participants, who then recruit the next ones. 

Participants share similar characteristics and/or know each other. Because of this, not every member of the population has an equal chance of being included in the sample, giving rise to sampling bias .

Snowball sampling is a non-probability sampling method , where there is not an equal chance for every member of the population to be included in the sample .

This means that you cannot use inferential statistics and make generalisations – often the goal of quantitative research . As such, a snowball sample is not representative of the target population, and is usually a better fit for qualitative research .

Snowball sampling is a non-probability sampling method . Unlike probability sampling (which involves some form of random selection ), the initial individuals selected to be studied are the ones who recruit new participants.

Because not every member of the target population has an equal chance of being recruited into the sample, selection in snowball sampling is non-random.

Reproducibility and replicability are related terms.

  • Reproducing research entails reanalysing the existing data in the same manner.
  • Replicating (or repeating ) the research entails reconducting the entire analysis, including the collection of new data . 
  • A successful reproduction shows that the data analyses were conducted in a fair and honest manner.
  • A successful replication shows that the reliability of the results is high.

The reproducibility and replicability of a study can be ensured by writing a transparent, detailed method section and using clear, unambiguous language.

Convergent validity and discriminant validity are both subtypes of construct validity . Together, they help you evaluate whether a test measures the concept it was designed to measure.

  • Convergent validity indicates whether a test that is designed to measure a particular construct correlates with other tests that assess the same or similar construct.
  • Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related

You need to assess both in order to demonstrate construct validity. Neither one alone is sufficient for establishing construct validity.

Construct validity has convergent and discriminant subtypes. They assist determine if a test measures the intended notion.

Content validity shows you how accurately a test or other measurement method taps  into the various aspects of the specific construct you are researching.

In other words, it helps you answer the question: “does the test measure all aspects of the construct I want to measure?” If it does, then the test has high content validity.

The higher the content validity, the more accurate the measurement of the construct.

If the test fails to include parts of the construct, or irrelevant parts are included, the validity of the instrument is threatened, which brings your results into question.

Construct validity refers to how well a test measures the concept (or construct) it was designed to measure. Assessing construct validity is especially important when you’re researching concepts that can’t be quantified and/or are intangible, like introversion. To ensure construct validity your test should be based on known indicators of introversion ( operationalisation ).

On the other hand, content validity assesses how well the test represents all aspects of the construct. If some aspects are missing or irrelevant parts are included, the test has low content validity.

Face validity and content validity are similar in that they both evaluate how suitable the content of a test is. The difference is that face validity is subjective, and assesses content at surface level.

When a test has strong face validity, anyone would agree that the test’s questions appear to measure what they are intended to measure.

For example, looking at a 4th grade math test consisting of problems in which students have to add and multiply, most people would agree that it has strong face validity (i.e., it looks like a math test).

On the other hand, content validity evaluates how well a test represents all the aspects of a topic. Assessing content validity is more systematic and relies on expert evaluation. of each question, analysing whether each one covers the aspects that the test was designed to cover.

A 4th grade math test would have high content validity if it covered all the skills taught in that grade. Experts(in this case, math teachers), would have to evaluate the content validity by comparing the test to the learning objectives.

  • Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related. This type of validity is also called divergent validity .

Criterion validity and construct validity are both types of measurement validity . In other words, they both show you how accurately a method measures something.

While construct validity is the degree to which a test or other measurement method measures what it claims to measure, criterion validity is the degree to which a test can predictively (in the future) or concurrently (in the present) measure something.

Construct validity is often considered the overarching type of measurement validity . You need to have face validity , content validity , and criterion validity in order to achieve construct validity.

Attrition refers to participants leaving a study. It always happens to some extent – for example, in randomised control trials for medical research.

Differential attrition occurs when attrition or dropout rates differ systematically between the intervention and the control group . As a result, the characteristics of the participants who drop out differ from the characteristics of those who stay in the study. Because of this, study results may be biased .

Criterion validity evaluates how well a test measures the outcome it was designed to measure. An outcome can be, for example, the onset of a disease.

Criterion validity consists of two subtypes depending on the time at which the two measures (the criterion and your test) are obtained:

  • Concurrent validity is a validation strategy where the the scores of a test and the criterion are obtained at the same time
  • Predictive validity is a validation strategy where the criterion variables are measured after the scores of the test

Validity tells you how accurately a method measures what it was designed to measure. There are 4 main types of validity :

  • Construct validity : Does the test measure the construct it was designed to measure?
  • Face validity : Does the test appear to be suitable for its objectives ?
  • Content validity : Does the test cover all relevant parts of the construct it aims to measure.
  • Criterion validity : Do the results accurately measure the concrete outcome they are designed to measure?

Convergent validity shows how much a measure of one construct aligns with other measures of the same or related constructs .

On the other hand, concurrent validity is about how a measure matches up to some known criterion or gold standard, which can be another measure.

Although both types of validity are established by calculating the association or correlation between a test score and another variable , they represent distinct validation methods.

The purpose of theory-testing mode is to find evidence in order to disprove, refine, or support a theory. As such, generalisability is not the aim of theory-testing mode.

Due to this, the priority of researchers in theory-testing mode is to eliminate alternative causes for relationships between variables . In other words, they prioritise internal validity over external validity , including ecological validity .

Inclusion and exclusion criteria are typically presented and discussed in the methodology section of your thesis or dissertation .

Inclusion and exclusion criteria are predominantly used in non-probability sampling . In purposive sampling and snowball sampling , restrictions apply as to who can be included in the sample .

Scope of research is determined at the beginning of your research process , prior to the data collection stage. Sometimes called “scope of study,” your scope delineates what will and will not be covered in your project. It helps you focus your work and your time, ensuring that you’ll be able to achieve your goals and outcomes.

Defining a scope can be very useful in any research project, from a research proposal to a thesis or dissertation . A scope is needed for all types of research: quantitative , qualitative , and mixed methods .

To define your scope of research, consider the following:

  • Budget constraints or any specifics of grant funding
  • Your proposed timeline and duration
  • Specifics about your population of study, your proposed sample size , and the research methodology you’ll pursue
  • Any inclusion and exclusion criteria
  • Any anticipated control , extraneous , or confounding variables that could bias your research if not accounted for properly.

To make quantitative observations , you need to use instruments that are capable of measuring the quantity you want to observe. For example, you might use a ruler to measure the length of an object or a thermometer to measure its temperature.

Quantitative observations involve measuring or counting something and expressing the result in numerical form, while qualitative observations involve describing something in non-numerical terms, such as its appearance, texture, or color.

The Scribbr Reference Generator is developed using the open-source Citation Style Language (CSL) project and Frank Bennett’s citeproc-js . It’s the same technology used by dozens of other popular citation tools, including Mendeley and Zotero.

You can find all the citation styles and locales used in the Scribbr Reference Generator in our publicly accessible repository on Github .

To paraphrase effectively, don’t just take the original sentence and swap out some of the words for synonyms. Instead, try:

  • Reformulating the sentence (e.g., change active to passive , or start from a different point)
  • Combining information from multiple sentences into one
  • Leaving out information from the original that isn’t relevant to your point
  • Using synonyms where they don’t distort the meaning

The main point is to ensure you don’t just copy the structure of the original text, but instead reformulate the idea in your own words.

Plagiarism means using someone else’s words or ideas and passing them off as your own. Paraphrasing means putting someone else’s ideas into your own words.

So when does paraphrasing count as plagiarism?

  • Paraphrasing is plagiarism if you don’t properly credit the original author.
  • Paraphrasing is plagiarism if your text is too close to the original wording (even if you cite the source). If you directly copy a sentence or phrase, you should quote it instead.
  • Paraphrasing  is not plagiarism if you put the author’s ideas completely into your own words and properly reference the source .

To present information from other sources in academic writing , it’s best to paraphrase in most cases. This shows that you’ve understood the ideas you’re discussing and incorporates them into your text smoothly.

It’s appropriate to quote when:

  • Changing the phrasing would distort the meaning of the original text
  • You want to discuss the author’s language choices (e.g., in literary analysis )
  • You’re presenting a precise definition
  • You’re looking in depth at a specific claim

A quote is an exact copy of someone else’s words, usually enclosed in quotation marks and credited to the original author or speaker.

Every time you quote a source , you must include a correctly formatted in-text citation . This looks slightly different depending on the citation style .

For example, a direct quote in APA is cited like this: ‘This is a quote’ (Streefkerk, 2020, p. 5).

Every in-text citation should also correspond to a full reference at the end of your paper.

In scientific subjects, the information itself is more important than how it was expressed, so quoting should generally be kept to a minimum. In the arts and humanities, however, well-chosen quotes are often essential to a good paper.

In social sciences, it varies. If your research is mainly quantitative , you won’t include many quotes, but if it’s more qualitative , you may need to quote from the data you collected .

As a general guideline, quotes should take up no more than 5–10% of your paper. If in doubt, check with your instructor or supervisor how much quoting is appropriate in your field.

If you’re quoting from a text that paraphrases or summarises other sources and cites them in parentheses , APA  recommends retaining the citations as part of the quote:

  • Smith states that ‘the literature on this topic (Jones, 2015; Sill, 2019; Paulson, 2020) shows no clear consensus’ (Smith, 2019, p. 4).

Footnote or endnote numbers that appear within quoted text should be omitted.

If you want to cite an indirect source (one you’ve only seen quoted in another source), either locate the original source or use the phrase ‘as cited in’ in your citation.

A block quote is a long quote formatted as a separate ‘block’ of text. Instead of using quotation marks , you place the quote on a new line, and indent the entire quote to mark it apart from your own words.

APA uses block quotes for quotes that are 40 words or longer.

A credible source should pass the CRAAP test  and follow these guidelines:

  • The information should be up to date and current.
  • The author and publication should be a trusted authority on the subject you are researching.
  • The sources the author cited should be easy to find, clear, and unbiased.
  • For a web source, the URL and layout should signify that it is trustworthy.

Common examples of primary sources include interview transcripts , photographs, novels, paintings, films, historical documents, and official statistics.

Anything you directly analyze or use as first-hand evidence can be a primary source, including qualitative or quantitative data that you collected yourself.

Common examples of secondary sources include academic books, journal articles , reviews, essays , and textbooks.

Anything that summarizes, evaluates or interprets primary sources can be a secondary source. If a source gives you an overview of background information or presents another researcher’s ideas on your topic, it is probably a secondary source.

To determine if a source is primary or secondary, ask yourself:

  • Was the source created by someone directly involved in the events you’re studying (primary), or by another researcher (secondary)?
  • Does the source provide original information (primary), or does it summarize information from other sources (secondary)?
  • Are you directly analyzing the source itself (primary), or only using it for background information (secondary)?

Some types of sources are nearly always primary: works of art and literature, raw statistical data, official documents and records, and personal communications (e.g. letters, interviews ). If you use one of these in your research, it is probably a primary source.

Primary sources are often considered the most credible in terms of providing evidence for your argument, as they give you direct evidence of what you are researching. However, it’s up to you to ensure the information they provide is reliable and accurate.

Always make sure to properly cite your sources to avoid plagiarism .

A fictional movie is usually a primary source. A documentary can be either primary or secondary depending on the context.

If you are directly analysing some aspect of the movie itself – for example, the cinematography, narrative techniques, or social context – the movie is a primary source.

If you use the movie for background information or analysis about your topic – for example, to learn about a historical event or a scientific discovery – the movie is a secondary source.

Whether it’s primary or secondary, always properly cite the movie in the citation style you are using. Learn how to create an MLA movie citation or an APA movie citation .

Articles in newspapers and magazines can be primary or secondary depending on the focus of your research.

In historical studies, old articles are used as primary sources that give direct evidence about the time period. In social and communication studies, articles are used as primary sources to analyse language and social relations (for example, by conducting content analysis or discourse analysis ).

If you are not analysing the article itself, but only using it for background information or facts about your topic, then the article is a secondary source.

In academic writing , there are three main situations where quoting is the best choice:

  • To analyse the author’s language (e.g., in a literary analysis essay )
  • To give evidence from primary sources
  • To accurately present a precise definition or argument

Don’t overuse quotes; your own voice should be dominant. If you just want to provide information from a source, it’s usually better to paraphrase or summarise .

Your list of tables and figures should go directly after your table of contents in your thesis or dissertation.

Lists of figures and tables are often not required, and they aren’t particularly common. They specifically aren’t required for APA Style, though you should be careful to follow their other guidelines for figures and tables .

If you have many figures and tables in your thesis or dissertation, include one may help you stay organised. Your educational institution may require them, so be sure to check their guidelines.

Copyright information can usually be found wherever the table or figure was published. For example, for a diagram in a journal article , look on the journal’s website or the database where you found the article. Images found on sites like Flickr are listed with clear copyright information.

If you find that permission is required to reproduce the material, be sure to contact the author or publisher and ask for it.

A list of figures and tables compiles all of the figures and tables that you used in your thesis or dissertation and displays them with the page number where they can be found.

APA doesn’t require you to include a list of tables or a list of figures . However, it is advisable to do so if your text is long enough to feature a table of contents and it includes a lot of tables and/or figures .

A list of tables and list of figures appear (in that order) after your table of contents, and are presented in a similar way.

A glossary is a collection of words pertaining to a specific topic. In your thesis or dissertation, it’s a list of all terms you used that may not immediately be obvious to your reader. Your glossary only needs to include terms that your reader may not be familiar with, and is intended to enhance their understanding of your work.

Definitional terms often fall into the category of common knowledge , meaning that they don’t necessarily have to be cited. This guidance can apply to your thesis or dissertation glossary as well.

However, if you’d prefer to cite your sources , you can follow guidance for citing dictionary entries in MLA or APA style for your glossary.

A glossary is a collection of words pertaining to a specific topic. In your thesis or dissertation, it’s a list of all terms you used that may not immediately be obvious to your reader. In contrast, an index is a list of the contents of your work organised by page number.

Glossaries are not mandatory, but if you use a lot of technical or field-specific terms, it may improve readability to add one to your thesis or dissertation. Your educational institution may also require them, so be sure to check their specific guidelines.

A glossary is a collection of words pertaining to a specific topic. In your thesis or dissertation, it’s a list of all terms you used that may not immediately be obvious to your reader. In contrast, dictionaries are more general collections of words.

The title page of your thesis or dissertation should include your name, department, institution, degree program, and submission date.

The title page of your thesis or dissertation goes first, before all other content or lists that you may choose to include.

Usually, no title page is needed in an MLA paper . A header is generally included at the top of the first page instead. The exceptions are when:

  • Your instructor requires one, or
  • Your paper is a group project

In those cases, you should use a title page instead of a header, listing the same information but on a separate page.

When you mention different chapters within your text, it’s considered best to use Roman numerals for most citation styles. However, the most important thing here is to remain consistent whenever using numbers in your dissertation .

A thesis or dissertation outline is one of the most critical first steps in your writing process. It helps you to lay out and organise your ideas and can provide you with a roadmap for deciding what kind of research you’d like to undertake.

Generally, an outline contains information on the different sections included in your thesis or dissertation, such as:

  • Your anticipated title
  • Your abstract
  • Your chapters (sometimes subdivided into further topics like literature review, research methods, avenues for future research, etc.)

While a theoretical framework describes the theoretical underpinnings of your work based on existing research, a conceptual framework allows you to draw your own conclusions, mapping out the variables you may use in your study and the interplay between them.

A literature review and a theoretical framework are not the same thing and cannot be used interchangeably. While a theoretical framework describes the theoretical underpinnings of your work, a literature review critically evaluates existing research relating to your topic. You’ll likely need both in your dissertation .

A theoretical framework can sometimes be integrated into a  literature review chapter , but it can also be included as its own chapter or section in your dissertation . As a rule of thumb, if your research involves dealing with a lot of complex theories, it’s a good idea to include a separate theoretical framework chapter.

An abstract is a concise summary of an academic text (such as a journal article or dissertation ). It serves two main purposes:

  • To help potential readers determine the relevance of your paper for their own research.
  • To communicate your key findings to those who don’t have time to read the whole paper.

Abstracts are often indexed along with keywords on academic databases, so they make your work more easily findable. Since the abstract is the first thing any reader sees, it’s important that it clearly and accurately summarises the contents of your paper.

The abstract is the very last thing you write. You should only write it after your research is complete, so that you can accurately summarize the entirety of your thesis or paper.

Avoid citing sources in your abstract . There are two reasons for this:

  • The abstract should focus on your original research, not on the work of others.
  • The abstract should be self-contained and fully understandable without reference to other sources.

There are some circumstances where you might need to mention other sources in an abstract: for example, if your research responds directly to another study or focuses on the work of a single theorist. In general, though, don’t include citations unless absolutely necessary.

The abstract appears on its own page, after the title page and acknowledgements but before the table of contents .

Results are usually written in the past tense , because they are describing the outcome of completed actions.

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

Formulating a main research question can be a difficult task. Overall, your question should contribute to solving the problem that you have defined in your problem statement .

However, it should also fulfill criteria in three main areas:

  • Researchability
  • Feasibility and specificity
  • Relevance and originality

The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.

A noun is a word that represents a person, thing, concept, or place (e.g., ‘John’, ‘house’, ‘affinity’, ‘river’). Most sentences contain at least one noun or pronoun .

Nouns are often, but not always, preceded by an article (‘the’, ‘a’, or ‘an’) and/or another determiner such as an adjective.

There are many ways to categorize nouns into various types, and the same noun can fall into multiple categories or even change types depending on context.

Some of the main types of nouns are:

  • Common nouns and proper nouns
  • Countable and uncountable nouns
  • Concrete and abstract nouns
  • Collective nouns
  • Possessive nouns
  • Attributive nouns
  • Appositive nouns
  • Generic nouns

Pronouns are words like ‘I’, ‘she’, and ‘they’ that are used in a similar way to nouns . They stand in for a noun that has already been mentioned or refer to yourself and other people.

Pronouns can function just like nouns as the head of a noun phrase and as the subject or object of a verb. However, pronouns change their forms (e.g., from ‘I’ to ‘me’) depending on the grammatical context they’re used in, whereas nouns usually don’t.

Common nouns are words for types of things, people, and places, such as ‘dog’, ‘professor’, and ‘city’. They are not capitalised and are typically used in combination with articles and other determiners.

Proper nouns are words for specific things, people, and places, such as ‘Max’, ‘Dr Prakash’, and ‘London’. They are always capitalised and usually aren’t combined with articles and other determiners.

A proper adjective is an adjective that was derived from a proper noun and is therefore capitalised .

Proper adjectives include words for nationalities, languages, and ethnicities (e.g., ‘Japanese’, ‘Inuit’, ‘French’) and words derived from people’s names (e.g., ‘Bayesian’, ‘Orwellian’).

The names of seasons (e.g., ‘spring’) are treated as common nouns in English and therefore not capitalised . People often assume they are proper nouns, but this is an error.

The names of days and months, however, are capitalised since they’re treated as proper nouns in English (e.g., ‘Wednesday’, ‘January’).

No, as a general rule, academic concepts, disciplines, theories, models, etc. are treated as common nouns , not proper nouns , and therefore not capitalised . For example, ‘five-factor model of personality’ or ‘analytic philosophy’.

However, proper nouns that appear within the name of an academic concept (such as the name of the inventor) are capitalised as usual. For example, ‘Darwin’s theory of evolution’ or ‘ Student’s t table ‘.

Collective nouns are most commonly treated as singular (e.g., ‘the herd is grazing’), but usage differs between US and UK English :

  • In US English, it’s standard to treat all collective nouns as singular, even when they are plural in appearance (e.g., ‘The Rolling Stones is …’). Using the plural form is usually seen as incorrect.
  • In UK English, collective nouns can be treated as singular or plural depending on context. It’s quite common to use the plural form, especially when the noun looks plural (e.g., ‘The Rolling Stones are …’).

The plural of “crisis” is “crises”. It’s a loanword from Latin and retains its original Latin plural noun form (similar to “analyses” and “bases”). It’s wrong to write “crisises”.

For example, you might write “Several crises destabilized the regime.”

Normally, the plural of “fish” is the same as the singular: “fish”. It’s one of a group of irregular plural nouns in English that are identical to the corresponding singular nouns (e.g., “moose”, “sheep”). For example, you might write “The fish scatter as the shark approaches.”

If you’re referring to several species of fish, though, the regular plural “fishes” is often used instead. For example, “The aquarium contains many different fishes , including trout and carp.”

The correct plural of “octopus” is “octopuses”.

People often write “octopi” instead because they assume that the plural noun is formed in the same way as Latin loanwords such as “fungus/fungi”. But “octopus” actually comes from Greek, where its original plural is “octopodes”. In English, it instead has the regular plural form “octopuses”.

For example, you might write “There are four octopuses in the aquarium.”

The plural of “moose” is the same as the singular: “moose”. It’s one of a group of plural nouns in English that are identical to the corresponding singular nouns. So it’s wrong to write “mooses”.

For example, you might write “There are several moose in the forest.”

Bias in research affects the validity and reliability of your findings, leading to false conclusions and a misinterpretation of the truth. This can have serious implications in areas like medical research where, for example, a new form of treatment may be evaluated.

Observer bias occurs when the researcher’s assumptions, views, or preconceptions influence what they see and record in a study, while actor–observer bias refers to situations where respondents attribute internal factors (e.g., bad character) to justify other’s behaviour and external factors (difficult circumstances) to justify the same behaviour in themselves.

Response bias is a general term used to describe a number of different conditions or factors that cue respondents to provide inaccurate or false answers during surveys or interviews . These factors range from the interviewer’s perceived social position or appearance to the the phrasing of questions in surveys.

Nonresponse bias occurs when the people who complete a survey are different from those who did not, in ways that are relevant to the research topic. Nonresponse can happen either because people are not willing or not able to participate.

In research, demand characteristics are cues that might indicate the aim of a study to participants. These cues can lead to participants changing their behaviors or responses based on what they think the research is about.

Demand characteristics are common problems in psychology experiments and other social science studies because they can bias your research findings.

Demand characteristics are a type of extraneous variable that can affect the outcomes of the study. They can invalidate studies by providing an alternative explanation for the results.

These cues may nudge participants to consciously or unconsciously change their responses, and they pose a threat to both internal and external validity . You can’t be sure that your independent variable manipulation worked, or that your findings can be applied to other people or settings.

You can control demand characteristics by taking a few precautions in your research design and materials.

Use these measures:

  • Deception: Hide the purpose of the study from participants
  • Between-groups design : Give each participant only one independent variable treatment
  • Double-blind design : Conceal the assignment of groups from participants and yourself
  • Implicit measures: Use indirect or hidden measurements for your variables

Some attrition is normal and to be expected in research. However, the type of attrition is important because systematic research bias can distort your findings. Attrition bias can lead to inaccurate results because it affects internal and/or external validity .

To avoid attrition bias , applying some of these measures can help you reduce participant dropout (attrition) by making it easy and appealing for participants to stay.

  • Provide compensation (e.g., cash or gift cards) for attending every session
  • Minimise the number of follow-ups as much as possible
  • Make all follow-ups brief, flexible, and convenient for participants
  • Send participants routine reminders to schedule follow-ups
  • Recruit more participants than you need for your sample (oversample)
  • Maintain detailed contact information so you can get in touch with participants even if they move

If you have a small amount of attrition bias , you can use a few statistical methods to try to make up for this research bias .

Multiple imputation involves using simulations to replace the missing data with likely values. Alternatively, you can use sample weighting to make up for the uneven balance of participants in your sample.

Placebos are used in medical research for new medication or therapies, called clinical trials. In these trials some people are given a placebo, while others are given the new medication being tested.

The purpose is to determine how effective the new medication is: if it benefits people beyond a predefined threshold as compared to the placebo, it’s considered effective.

Although there is no definite answer to what causes the placebo effect , researchers propose a number of explanations such as the power of suggestion, doctor-patient interaction, classical conditioning, etc.

Belief bias and confirmation bias are both types of cognitive bias that impact our judgment and decision-making.

Confirmation bias relates to how we perceive and judge evidence. We tend to seek out and prefer information that supports our preexisting beliefs, ignoring any information that contradicts those beliefs.

Belief bias describes the tendency to judge an argument based on how plausible the conclusion seems to us, rather than how much evidence is provided to support it during the course of the argument.

Positivity bias is phenomenon that occurs when a person judges individual members of a group positively, even when they have negative impressions or judgments of the group as a whole. Positivity bias is closely related to optimism bias , or the e xpectation that things will work out well, even if rationality suggests that problems are inevitable in life.

Perception bias is a problem because it prevents us from seeing situations or people objectively. Rather, our expectations, beliefs, or emotions interfere with how we interpret reality. This, in turn, can cause us to misjudge ourselves or others. For example, our prejudices can interfere with whether we perceive people’s faces as friendly or unfriendly.

There are many ways to categorize adjectives into various types. An adjective can fall into one or more of these categories depending on how it is used.

Some of the main types of adjectives are:

  • Attributive adjectives
  • Predicative adjectives
  • Comparative adjectives
  • Superlative adjectives
  • Coordinate adjectives
  • Appositive adjectives
  • Compound adjectives
  • Participial adjectives
  • Proper adjectives
  • Denominal adjectives
  • Nominal adjectives

Cardinal numbers (e.g., one, two, three) can be placed before a noun to indicate quantity (e.g., one apple). While these are sometimes referred to as ‘numeral adjectives ‘, they are more accurately categorised as determiners or quantifiers.

Proper adjectives are adjectives formed from a proper noun (i.e., the name of a specific person, place, or thing) that are used to indicate origin. Like proper nouns, proper adjectives are always capitalised (e.g., Newtonian, Marxian, African).

The cost of proofreading depends on the type and length of text, the turnaround time, and the level of services required. Most proofreading companies charge per word or page, while freelancers sometimes charge an hourly rate.

For proofreading alone, which involves only basic corrections of typos and formatting mistakes, you might pay as little as £0.01 per word, but in many cases, your text will also require some level of editing , which costs slightly more.

It’s often possible to purchase combined proofreading and editing services and calculate the price in advance based on your requirements.

Then and than are two commonly confused words . In the context of ‘better than’, you use ‘than’ with an ‘a’.

  • Julie is better than Jesse.
  • I’d rather spend my time with you than with him.
  • I understand Eoghan’s point of view better than Claudia’s.

Use to and used to are commonly confused words . In the case of ‘used to do’, the latter (with ‘d’) is correct, since you’re describing an action or state in the past.

  • I used to do laundry once a week.
  • They used to do each other’s hair.
  • We used to do the dishes every day .

There are numerous synonyms and near synonyms for the various meanings of “ favour ”:

There are numerous synonyms and near synonyms for the two meanings of “ favoured ”:

No one (two words) is an indefinite pronoun meaning ‘nobody’. People sometimes mistakenly write ‘noone’, but this is incorrect and should be avoided. ‘No-one’, with a hyphen, is also acceptable in UK English .

Nobody and no one are both indefinite pronouns meaning ‘no person’. They can be used interchangeably (e.g., ‘nobody is home’ means the same as ‘no one is home’).

Some synonyms and near synonyms of  every time include:

  • Without exception

‘Everytime’ is sometimes used to mean ‘each time’ or ‘whenever’. However, this is incorrect and should be avoided. The correct phrase is every time   (two words).

Yes, the conjunction because is a compound word , but one with a long history. It originates in Middle English from the preposition “bi” (“by”) and the noun “cause”. Over time, the open compound “bi cause” became the closed compound “because”, which we use today.

Though it’s spelled this way now, the verb “be” is not one of the words that makes up “because”.

Yes, today is a compound word , but a very old one. It wasn’t originally formed from the preposition “to” and the noun “day”; rather, it originates from their Old English equivalents, “tō” and “dæġe”.

In the past, it was sometimes written as a hyphenated compound: “to-day”. But the hyphen is no longer included; it’s always “today” now (“to day” is also wrong).

IEEE citation format is defined by the Institute of Electrical and Electronics Engineers and used in their publications.

It’s also a widely used citation style for students in technical fields like electrical and electronic engineering, computer science, telecommunications, and computer engineering.

An IEEE in-text citation consists of a number in brackets at the relevant point in the text, which points the reader to the right entry in the numbered reference list at the end of the paper. For example, ‘Smith [1] states that …’

A location marker such as a page number is also included within the brackets when needed: ‘Smith [1, p. 13] argues …’

The IEEE reference page consists of a list of references numbered in the order they were cited in the text. The title ‘References’ appears in bold at the top, either left-aligned or centered.

The numbers appear in square brackets on the left-hand side of the page. The reference entries are indented consistently to separate them from the numbers. Entries are single-spaced, with a normal paragraph break between them.

If you cite the same source more than once in your writing, use the same number for all of the IEEE in-text citations for that source, and only include it on the IEEE reference page once. The source is numbered based on the first time you cite it.

For example, the fourth source you cite in your paper is numbered [4]. If you cite it again later, you still cite it as [4]. You can cite different parts of the source each time by adding page numbers [4, p. 15].

A verb is a word that indicates a physical action (e.g., ‘drive’), a mental action (e.g., ‘think’) or a state of being (e.g., ‘exist’). Every sentence contains a verb.

Verbs are almost always used along with a noun or pronoun to describe what the noun or pronoun is doing.

There are many ways to categorize verbs into various types. A verb can fall into one or more of these categories depending on how it is used.

Some of the main types of verbs are:

  • Regular verbs
  • Irregular verbs
  • Transitive verbs
  • Intransitive verbs
  • Dynamic verbs
  • Stative verbs
  • Linking verbs
  • Auxiliary verbs
  • Modal verbs
  • Phrasal verbs

Regular verbs are verbs whose simple past and past participle are formed by adding the suffix ‘-ed’ (e.g., ‘walked’).

Irregular verbs are verbs that form their simple past and past participles in some way other than by adding the suffix ‘-ed’ (e.g., ‘sat’).

The indefinite articles a and an are used to refer to a general or unspecified version of a noun (e.g., a house). Which indefinite article you use depends on the pronunciation of the word that follows it.

  • A is used for words that begin with a consonant sound (e.g., a bear).
  • An is used for words that begin with a vowel sound (e.g., an eagle).

Indefinite articles can only be used with singular countable nouns . Like definite articles, they are a type of determiner .

Editing and proofreading are different steps in the process of revising a text.

Editing comes first, and can involve major changes to content, structure and language. The first stages of editing are often done by authors themselves, while a professional editor makes the final improvements to grammar and style (for example, by improving sentence structure and word choice ).

Proofreading is the final stage of checking a text before it is published or shared. It focuses on correcting minor errors and inconsistencies (for example, in punctuation and capitalization ). Proofreaders often also check for formatting issues, especially in print publishing.

Whether you’re publishing a blog, submitting a research paper , or even just writing an important email, there are a few techniques you can use to make sure it’s error-free:

  • Take a break : Set your work aside for at least a few hours so that you can look at it with fresh eyes.
  • Proofread a printout : Staring at a screen for too long can cause fatigue – sit down with a pen and paper to check the final version.
  • Use digital shortcuts : Take note of any recurring mistakes (for example, misspelling a particular word, switching between US and UK English , or inconsistently capitalizing a term), and use Find and Replace to fix it throughout the document.

If you want to be confident that an important text is error-free, it might be worth choosing a professional proofreading service instead.

There are many different routes to becoming a professional proofreader or editor. The necessary qualifications depend on the field – to be an academic or scientific proofreader, for example, you will need at least a university degree in a relevant subject.

For most proofreading jobs, experience and demonstrated skills are more important than specific qualifications. Often your skills will be tested as part of the application process.

To learn practical proofreading skills, you can choose to take a course with a professional organisation such as the Society for Editors and Proofreaders . Alternatively, you can apply to companies that offer specialised on-the-job training programmes, such as the Scribbr Academy .

Though they’re pronounced the same, there’s a big difference in meaning between its and it’s .

  • ‘The cat ate its food’.
  • ‘It’s almost Christmas’.

Its and it’s are often confused, but its (without apostrophe) is the possessive form of ‘it’ (e.g., its tail, its argument, its wing). You use ‘its’ instead of ‘his’ and ‘her’ for neuter, inanimate nouns.

Then and than are two commonly confused words with different meanings and grammatical roles.

  • Then (pronounced with a short ‘e’ sound) refers to time. It’s often an adverb , but it can also be used as a noun meaning ‘that time’ and as an adjective referring to a previous status.
  • Than (pronounced with a short ‘a’ sound) is used for comparisons. Grammatically, it usually functions as a conjunction , but sometimes it’s a preposition .

Use to and used to are commonly confused words . In the case of ‘used to be’, the latter (with ‘d’) is correct, since you’re describing an action or state in the past.

  • I used to be the new coworker.
  • There used to be 4 cookies left.
  • We used to walk to school every day .

A grammar checker is a tool designed to automatically check your text for spelling errors, grammatical issues, punctuation mistakes , and problems with sentence structure . You can check out our analysis of the best free grammar checkers to learn more.

A paraphrasing tool edits your text more actively, changing things whether they were grammatically incorrect or not. It can paraphrase your sentences to make them more concise and readable or for other purposes. You can check out our analysis of the best free paraphrasing tools to learn more.

Some tools available online combine both functions. Others, such as QuillBot , have separate grammar checker and paraphrasing tools. Be aware of what exactly the tool you’re using does to avoid introducing unwanted changes.

Good grammar is the key to expressing yourself clearly and fluently, especially in professional communication and academic writing . Word processors, browsers, and email programs typically have built-in grammar checkers, but they’re quite limited in the kinds of problems they can fix.

If you want to go beyond detecting basic spelling errors, there are many online grammar checkers with more advanced functionality. They can often detect issues with punctuation , word choice, and sentence structure that more basic tools would miss.

Not all of these tools are reliable, though. You can check out our research into the best free grammar checkers to explore the options.

Our research indicates that the best free grammar checker available online is the QuillBot grammar checker .

We tested 10 of the most popular checkers with the same sample text (containing 20 grammatical errors) and found that QuillBot easily outperformed the competition, scoring 18 out of 20, a drastic improvement over the second-place score of 13 out of 20.

It even appeared to outperform the premium versions of other grammar checkers, despite being entirely free.

A teacher’s aide is a person who assists in teaching classes but is not a qualified teacher. Aide is a noun meaning ‘assistant’, so it will always refer to a person.

‘Teacher’s aid’ is incorrect.

A visual aid is an instructional device (e.g., a photo, a chart) that appeals to vision to help you understand written or spoken information. Aid is often placed after an attributive noun or adjective (like ‘visual’) that describes the type of help provided.

‘Visual aide’ is incorrect.

A job aid is an instructional tool (e.g., a checklist, a cheat sheet) that helps you work efficiently. Aid is a noun meaning ‘assistance’. It’s often placed after an adjective or attributive noun (like ‘job’) that describes the specific type of help provided.

‘Job aide’ is incorrect.

There are numerous synonyms for the various meanings of truly :

Yours truly is a phrase used at the end of a formal letter or email. It can also be used (typically in a humorous way) as a pronoun to refer to oneself (e.g., ‘The dinner was cooked by yours truly ‘). The latter usage should be avoided in formal writing.

It’s formed by combining the second-person possessive pronoun ‘yours’ with the adverb ‘ truly ‘.

A pathetic fallacy can be a short phrase or a whole sentence and is often used in novels and poetry. Pathetic fallacies serve multiple purposes, such as:

  • Conveying the emotional state of the characters or the narrator
  • Creating an atmosphere or set the mood of a scene
  • Foreshadowing events to come
  • Giving texture and vividness to a piece of writing
  • Communicating emotion to the reader in a subtle way, by describing the external world.
  • Bringing inanimate objects to life so that they seem more relatable.

AMA citation format is a citation style designed by the American Medical Association. It’s frequently used in the field of medicine.

You may be told to use AMA style for your student papers. You will also have to follow this style if you’re submitting a paper to a journal published by the AMA.

An AMA in-text citation consists of the number of the relevant reference on your AMA reference page , written in superscript 1 at the point in the text where the source is used.

It may also include the page number or range of the relevant material in the source (e.g., the part you quoted 2(p46) ). Multiple sources can be cited at one point, presented as a range or list (with no spaces 3,5–9 ).

An AMA reference usually includes the author’s last name and initials, the title of the source, information about the publisher or the publication it’s contained in, and the publication date. The specific details included, and the formatting, depend on the source type.

References in AMA style are presented in numerical order (numbered by the order in which they were first cited in the text) on your reference page. A source that’s cited repeatedly in the text still only appears once on the reference page.

An AMA in-text citation just consists of the number of the relevant entry on your AMA reference page , written in superscript at the point in the text where the source is referred to.

You don’t need to mention the author of the source in your sentence, but you can do so if you want. It’s not an official part of the citation, but it can be useful as part of a signal phrase introducing the source.

On your AMA reference page , author names are written with the last name first, followed by the initial(s) of their first name and middle name if mentioned.

There’s a space between the last name and the initials, but no space or punctuation between the initials themselves. The names of multiple authors are separated by commas , and the whole list ends in a period, e.g., ‘Andreessen F, Smith PW, Gonzalez E’.

The names of up to six authors should be listed for each source on your AMA reference page , separated by commas . For a source with seven or more authors, you should list the first three followed by ‘ et al’ : ‘Isidore, Gilbert, Gunvor, et al’.

In the text, mentioning author names is optional (as they aren’t an official part of AMA in-text citations ). If you do mention them, though, you should use the first author’s name followed by ‘et al’ when there are three or more : ‘Isidore et al argue that …’

Note that according to AMA’s rather minimalistic punctuation guidelines, there’s no period after ‘et al’ unless it appears at the end of a sentence. This is different from most other styles, where there is normally a period.

Yes, you should normally include an access date in an AMA website citation (or when citing any source with a URL). This is because webpages can change their content over time, so it’s useful for the reader to know when you accessed the page.

When a publication or update date is provided on the page, you should include it in addition to the access date. The access date appears second in this case, e.g., ‘Published June 19, 2021. Accessed August 29, 2022.’

Don’t include an access date when citing a source with a DOI (such as in an AMA journal article citation ).

Some variables have fixed levels. For example, gender and ethnicity are always nominal level data because they cannot be ranked.

However, for other variables, you can choose the level of measurement . For example, income is a variable that can be recorded on an ordinal or a ratio scale:

  • At an ordinal level , you could create 5 income groupings and code the incomes that fall within them from 1–5.
  • At a ratio level , you would record exact numbers for income.

If you have a choice, the ratio level is always preferable because you can analyse data in more ways. The higher the level of measurement, the more precise your data is.

The level at which you measure a variable determines how you can analyse your data.

Depending on the level of measurement , you can perform different descriptive statistics to get an overall summary of your data and inferential statistics to see if your results support or refute your hypothesis .

Levels of measurement tell you how precisely variables are recorded. There are 4 levels of measurement, which can be ranked from low to high:

  • Nominal : the data can only be categorised.
  • Ordinal : the data can be categorised and ranked.
  • Interval : the data can be categorised and ranked, and evenly spaced.
  • Ratio : the data can be categorised, ranked, evenly spaced and has a natural zero.

Statistical analysis is the main method for analyzing quantitative research data . It uses probabilities and models to test predictions about a population from sample data.

The null hypothesis is often abbreviated as H 0 . When the null hypothesis is written using mathematical symbols, it always includes an equality symbol (usually =, but sometimes ≥ or ≤).

The alternative hypothesis is often abbreviated as H a or H 1 . When the alternative hypothesis is written using mathematical symbols, it always includes an inequality symbol (usually ≠, but sometimes < or >).

As the degrees of freedom increase, Student’s t distribution becomes less leptokurtic , meaning that the probability of extreme values decreases. The distribution becomes more and more similar to a standard normal distribution .

When there are only one or two degrees of freedom , the chi-square distribution is shaped like a backwards ‘J’. When there are three or more degrees of freedom, the distribution is shaped like a right-skewed hump. As the degrees of freedom increase, the hump becomes less right-skewed and the peak of the hump moves to the right. The distribution becomes more and more similar to a normal distribution .

‘Looking forward in hearing from you’ is an incorrect version of the phrase looking forward to hearing from you . The phrasal verb ‘looking forward to’ always needs the preposition ‘to’, not ‘in’.

  • I am looking forward in hearing from you.
  • I am looking forward to hearing from you.

Some synonyms and near synonyms for the expression looking forward to hearing from you include:

  • Eagerly awaiting your response
  • Hoping to hear from you soon
  • It would be great to hear back from you
  • Thanks in advance for your reply

People sometimes mistakenly write ‘looking forward to hear from you’, but this is incorrect. The correct phrase is looking forward to hearing from you .

The phrasal verb ‘look forward to’ is always followed by a direct object, the thing you’re looking forward to. As the direct object has to be a noun phrase , it should be the gerund ‘hearing’, not the verb ‘hear’.

  • I’m looking forward to hear from you soon.
  • I’m looking forward to hearing from you soon.

Traditionally, the sign-off Yours sincerely is used in an email message or letter when you are writing to someone you have interacted with before, not a complete stranger.

Yours faithfully is used instead when you are writing to someone you have had no previous correspondence with, especially if you greeted them as ‘ Dear Sir or Madam ’.

Just checking in   is a standard phrase used to start an email (or other message) that’s intended to ask someone for a response or follow-up action in a friendly, informal way. However, it’s a cliché opening that can come across as passive-aggressive, so we recommend avoiding it in favor of a more direct opening like “We previously discussed …”

In a more personal context, you might encounter “just checking in” as part of a longer phrase such as “I’m just checking in to see how you’re doing”. In this case, it’s not asking the other person to do anything but rather asking about their well-being (emotional or physical) in a friendly way.

“Earliest convenience” is part of the phrase at your earliest convenience , meaning “as soon as you can”. 

It’s typically used to end an email in a formal context by asking the recipient to do something when it’s convenient for them to do so.

ASAP is an abbreviation of the phrase “as soon as possible”. 

It’s typically used to indicate a sense of urgency in highly informal contexts (e.g., “Let me know ASAP if you need me to drive you to the airport”).

“ASAP” should be avoided in more formal correspondence. Instead, use an alternative like at your earliest convenience .

Some synonyms and near synonyms of the verb   compose   (meaning “to make up”) are:

People increasingly use “comprise” as a synonym of “compose.” However, this is normally still seen as a mistake, and we recommend avoiding it in your academic writing . “Comprise” traditionally means “to be made up of,” not “to make up.”

Some synonyms and near synonyms of the verb comprise are:

  • Be composed of
  • Be made up of

People increasingly use “comprise” interchangeably with “compose,” meaning that they consider words like “compose,” “constitute,” and “form” to be synonymous with “comprise.” However, this is still normally regarded as an error, and we advise against using these words interchangeably in academic writing .

A fallacy is a mistaken belief, particularly one based on unsound arguments or one that lacks the evidence to support it. Common types of fallacy that may compromise the quality of your research are:

  • Correlation/causation fallacy: Claiming that two events that occur together have a cause-and-effect relationship even though this can’t be proven
  • Ecological fallacy : Making inferences about the nature of individuals based on aggregate data for the group
  • The sunk cost fallacy : Following through on a project or decision because we have already invested time, effort, or money into it, even if the current costs outweigh the benefits
  • The base-rate fallacy : Ignoring base-rate or statistically significant information, such as sample size or the relative frequency of an event, in favor of  less relevant information e.g., pertaining to a single case, or a small number of cases
  • The planning fallacy : Underestimating the time needed to complete a future task, even when we know that similar tasks in the past have taken longer than planned

The planning fallacy refers to people’s tendency to underestimate the resources needed to complete a future task, despite knowing that previous tasks have also taken longer than planned.

For example, people generally tend to underestimate the cost and time needed for construction projects. The planning fallacy occurs due to people’s tendency to overestimate the chances that positive events, such as a shortened timeline, will happen to them. This phenomenon is called optimism bias or positivity bias.

Although both red herring fallacy and straw man fallacy are logical fallacies or reasoning errors, they denote different attempts to “win” an argument. More specifically:

  • A red herring fallacy refers to an attempt to change the subject and divert attention from the original issue. In other words, a seemingly solid but ultimately irrelevant argument is introduced into the discussion, either on purpose or by mistake.
  • A straw man argument involves the deliberate distortion of another person’s argument. By oversimplifying or exaggerating it, the other party creates an easy-to-refute argument and then attacks it.

The red herring fallacy is a problem because it is flawed reasoning. It is a distraction device that causes people to become sidetracked from the main issue and draw wrong conclusions.

Although a red herring may have some kernel of truth, it is used as a distraction to keep our eyes on a different matter. As a result, it can cause us to accept and spread misleading information.

The sunk cost fallacy and escalation of commitment (or commitment bias ) are two closely related terms. However, there is a slight difference between them:

  • Escalation of commitment (aka commitment bias ) is the tendency to be consistent with what we have already done or said we will do in the past, especially if we did so in public. In other words, it is an attempt to save face and appear consistent.
  • Sunk cost fallacy is the tendency to stick with a decision or a plan even when it’s failing. Because we have already invested valuable time, money, or energy, quitting feels like these resources were wasted.

In other words, escalating commitment is a manifestation of the sunk cost fallacy: an irrational escalation of commitment frequently occurs when people refuse to accept that the resources they’ve already invested cannot be recovered. Instead, they insist on more spending to justify the initial investment (and the incurred losses).

When you are faced with a straw man argument , the best way to respond is to draw attention to the fallacy and ask your discussion partner to show how your original statement and their distorted version are the same. Since these are different, your partner will either have to admit that their argument is invalid or try to justify it by using more flawed reasoning, which you can then attack.

The straw man argument is a problem because it occurs when we fail to take an opposing point of view seriously. Instead, we intentionally misrepresent our opponent’s ideas and avoid genuinely engaging with them. Due to this, resorting to straw man fallacy lowers the standard of constructive debate.

A straw man argument is a distorted (and weaker) version of another person’s argument that can easily be refuted (e.g., when a teacher proposes that the class spend more time on math exercises, a parent complains that the teacher doesn’t care about reading and writing).

This is a straw man argument because it misrepresents the teacher’s position, which didn’t mention anything about cutting down on reading and writing. The straw man argument is also known as the straw man fallacy .

A slippery slope argument is not always a fallacy.

  • When someone claims adopting a certain policy or taking a certain action will automatically lead to a series of other policies or actions also being taken, this is a slippery slope argument.
  • If they don’t show a causal connection between the advocated policy and the consequent policies, then they commit a slippery slope fallacy .

There are a number of ways you can deal with slippery slope arguments especially when you suspect these are fallacious:

  • Slippery slope arguments take advantage of the gray area between an initial action or decision and the possible next steps that might lead to the undesirable outcome. You can point out these missing steps and ask your partner to indicate what evidence exists to support the claimed relationship between two or more events.
  • Ask yourself if each link in the chain of events or action is valid. Every proposition has to be true for the overall argument to work, so even if one link is irrational or not supported by evidence, then the argument collapses.
  • Sometimes people commit a slippery slope fallacy unintentionally. In these instances, use an example that demonstrates the problem with slippery slope arguments in general (e.g., by using statements to reach a conclusion that is not necessarily relevant to the initial statement). By attacking the concept of slippery slope arguments you can show that they are often fallacious.

People sometimes confuse cognitive bias and logical fallacies because they both relate to flawed thinking. However, they are not the same:

  • Cognitive bias is the tendency to make decisions or take action in an illogical way because of our values, memory, socialization, and other personal attributes. In other words, it refers to a fixed pattern of thinking rooted in the way our brain works.
  • Logical fallacies relate to how we make claims and construct our arguments in the moment. They are statements that sound convincing at first but can be disproven through logical reasoning.

In other words, cognitive bias refers to an ongoing predisposition, while logical fallacy refers to mistakes of reasoning that occur in the moment.

An appeal to ignorance (ignorance here meaning lack of evidence) is a type of informal logical fallacy .

It asserts that something must be true because it hasn’t been proven false—or that something must be false because it has not yet been proven true.

For example, “unicorns exist because there is no evidence that they don’t.” The appeal to ignorance is also called the burden of proof fallacy .

An ad hominem (Latin for “to the person”) is a type of informal logical fallacy . Instead of arguing against a person’s position, an ad hominem argument attacks the person’s character or actions in an effort to discredit them.

This rhetorical strategy is fallacious because a person’s character, motive, education, or other personal trait is logically irrelevant to whether their argument is true or false.

Name-calling is common in ad hominem fallacy (e.g., “environmental activists are ineffective because they’re all lazy tree-huggers”).

Ad hominem is a persuasive technique where someone tries to undermine the opponent’s argument by personally attacking them.

In this way, one can redirect the discussion away from the main topic and to the opponent’s personality without engaging with their viewpoint. When the opponent’s personality is irrelevant to the discussion, we call it an ad hominem fallacy .

Ad hominem tu quoque (‘you too”) is an attempt to rebut a claim by attacking its proponent on the grounds that they uphold a double standard or that they don’t practice what they preach. For example, someone is telling you that you should drive slowly otherwise you’ll get a speeding ticket one of these days, and you reply “but you used to get them all the time!”

Argumentum ad hominem means “argument to the person” in Latin and it is commonly referred to as ad hominem argument or personal attack. Ad hominem arguments are used in debates to refute an argument by attacking the character of the person making it, instead of the logic or premise of the argument itself.

The opposite of the hasty generalization fallacy is called slothful induction fallacy or appeal to coincidence .

It is the tendency to deny a conclusion even though there is sufficient evidence that supports it. Slothful induction occurs due to our natural tendency to dismiss events or facts that do not align with our personal biases and expectations. For example, a researcher may try to explain away unexpected results by claiming it is just a coincidence.

To avoid a hasty generalization fallacy we need to ensure that the conclusions drawn are well-supported by the appropriate evidence. More specifically:

  • In statistics , if we want to draw inferences about an entire population, we need to make sure that the sample is random and representative of the population . We can achieve that by using a probability sampling method , like simple random sampling or stratified sampling .
  • In academic writing , use precise language and measured phases. Try to avoid making absolute claims, cite specific instances and examples without applying the findings to a larger group.
  • As readers, we need to ask ourselves “does the writer demonstrate sufficient knowledge of the situation or phenomenon that would allow them to make a generalization?”

The hasty generalization fallacy and the anecdotal evidence fallacy are similar in that they both result in conclusions drawn from insufficient evidence. However, there is a difference between the two:

  • The hasty generalization fallacy involves genuinely considering an example or case (i.e., the evidence comes first and then an incorrect conclusion is drawn from this).
  • The anecdotal evidence fallacy (also known as “cherry-picking” ) is knowing in advance what conclusion we want to support, and then selecting the story (or a few stories) that support it. By overemphasizing anecdotal evidence that fits well with the point we are trying to make, we overlook evidence that would undermine our argument.

Although many sources use circular reasoning fallacy and begging the question interchangeably, others point out that there is a subtle difference between the two:

  • Begging the question fallacy occurs when you assume that an argument is true in order to justify a conclusion. If something begs the question, what you are actually asking is, “Is the premise of that argument actually true?” For example, the statement “Snakes make great pets. That’s why we should get a snake” begs the question “are snakes really great pets?”
  • Circular reasoning fallacy on the other hand, occurs when the evidence used to support a claim is just a repetition of the claim itself.  For example, “People have free will because they can choose what to do.”

In other words, we could say begging the question is a form of circular reasoning.

Circular reasoning fallacy uses circular reasoning to support an argument. More specifically, the evidence used to support a claim is just a repetition of the claim itself. For example: “The President of the United States is a good leader (claim), because they are the leader of this country (supporting evidence)”.

An example of a non sequitur is the following statement:

“Giving up nuclear weapons weakened the United States’ military. Giving up nuclear weapons also weakened China. For this reason, it is wrong to try to outlaw firearms in the United States today.”

Clearly there is a step missing in this line of reasoning and the conclusion does not follow from the premise, resulting in a non sequitur fallacy .

The difference between the post hoc fallacy and the non sequitur fallacy is that post hoc fallacy infers a causal connection between two events where none exists, whereas the non sequitur fallacy infers a conclusion that lacks a logical connection to the premise.

In other words, a post hoc fallacy occurs when there is a lack of a cause-and-effect relationship, while a non sequitur fallacy occurs when there is a lack of logical connection.

An example of post hoc fallacy is the following line of reasoning:

“Yesterday I had ice cream, and today I have a terrible stomachache. I’m sure the ice cream caused this.”

Although it is possible that the ice cream had something to do with the stomachache, there is no proof to justify the conclusion other than the order of events. Therefore, this line of reasoning is fallacious.

Post hoc fallacy and hasty generalisation fallacy are similar in that they both involve jumping to conclusions. However, there is a difference between the two:

  • Post hoc fallacy is assuming a cause and effect relationship between two events, simply because one happened after the other.
  • Hasty generalisation fallacy is drawing a general conclusion from a small sample or little evidence.

In other words, post hoc fallacy involves a leap to a causal claim; hasty generalisation fallacy involves a leap to a general proposition.

The fallacy of composition is similar to and can be confused with the hasty generalization fallacy . However, there is a difference between the two:

  • The fallacy of composition involves drawing an inference about the characteristics of a whole or group based on the characteristics of its individual members.
  • The hasty generalization fallacy involves drawing an inference about a population or class of things on the basis of few atypical instances or a small sample of that population or thing.

In other words, the fallacy of composition is using an unwarranted assumption that we can infer something about a whole based on the characteristics of its parts, while the hasty generalization fallacy is using insufficient evidence to draw a conclusion.

The opposite of the fallacy of composition is the fallacy of division . In the fallacy of division, the assumption is that a characteristic which applies to a whole or a group must necessarily apply to the parts or individual members. For example, “Australians travel a lot. Gary is Australian, so he must travel a lot.”

Base rate fallacy can be avoided by following these steps:

  • Avoid making an important decision in haste. When we are under pressure, we are more likely to resort to cognitive shortcuts like the availability heuristic and the representativeness heuristic . Due to this, we are more likely to factor in only current and vivid information, and ignore the actual probability of something happening (i.e., base rate).
  • Take a long-term view on the decision or question at hand. Look for relevant statistical data, which can reveal long-term trends and give you the full picture.
  • Talk to experts like professionals. They are more aware of probabilities related to specific decisions.

Suppose there is a population consisting of 90% psychologists and 10% engineers. Given that you know someone enjoyed physics at school, you may conclude that they are an engineer rather than a psychologist, even though you know that this person comes from a population consisting of far more psychologists than engineers.

When we ignore the rate of occurrence of some trait in a population (the base-rate information) we commit base rate fallacy .

Cost-benefit fallacy is a common error that occurs when allocating sources in project management. It is the fallacy of assuming that cost-benefit estimates are more or less accurate, when in fact they are highly inaccurate and biased. This means that cost-benefit analyses can be useful, but only after the cost-benefit fallacy has been acknowledged and corrected for. Cost-benefit fallacy is a type of base rate fallacy .

In advertising, the fallacy of equivocation is often used to create a pun. For example, a billboard company might advertise their billboards using a line like: “Looking for a sign? This is it!” The word sign has a literal meaning as billboard and a figurative one as a sign from God, the universe, etc.

Equivocation is a fallacy because it is a form of argumentation that is both misleading and logically unsound. When the meaning of a word or phrase shifts in the course of an argument, it causes confusion and also implies that the conclusion (which may be true) does not follow from the premise.

The fallacy of equivocation is an informal logical fallacy, meaning that the error lies in the content of the argument instead of the structure.

Fallacies of relevance are a group of fallacies that occur in arguments when the premises are logically irrelevant to the conclusion. Although at first there seems to be a connection between the premise and the conclusion, in reality fallacies of relevance use unrelated forms of appeal.

For example, the genetic fallacy makes an appeal to the source or origin of the claim in an attempt to assert or refute something.

The ad hominem fallacy and the genetic fallacy are closely related in that they are both fallacies of relevance. In other words, they both involve arguments that use evidence or examples that are not logically related to the argument at hand. However, there is a difference between the two:

  • In the ad hominem fallacy , the goal is to discredit the argument by discrediting the person currently making the argument.
  • In the genetic fallacy , the goal is to discredit the argument by discrediting the history or origin (i.e., genesis) of an argument.

False dilemma fallacy is also known as false dichotomy, false binary, and “either-or” fallacy. It is the fallacy of presenting only two choices, outcomes, or sides to an argument as the only possibilities, when more are available.

The false dilemma fallacy works in two ways:

  • By presenting only two options as if these were the only ones available
  • By presenting two options as mutually exclusive (i.e., only one option can be selected or can be true at a time)

In both cases, by using the false dilemma fallacy, one conceals alternative choices and doesn’t allow others to consider the full range of options. This is usually achieved through an“either-or” construction and polarised, divisive language (“you are either a friend or an enemy”).

The best way to avoid a false dilemma fallacy is to pause and reflect on two points:

  • Are the options presented truly the only ones available ? It could be that another option has been deliberately omitted.
  • Are the options mentioned mutually exclusive ? Perhaps all of the available options can be selected (or be true) at the same time, which shows that they aren’t mutually exclusive. Proving this is called “escaping between the horns of the dilemma.”

Begging the question fallacy is an argument in which you assume what you are trying to prove. In other words, your position and the justification of that position are the same, only slightly rephrased.

For example: “All freshmen should attend college orientation, because all college students should go to such an orientation.”

The complex question fallacy and begging the question fallacy are similar in that they are both based on assumptions. However, there is a difference between them:

  • A complex question fallacy occurs when someone asks a question that presupposes the answer to another question that has not been established or accepted by the other person. For example, asking someone “Have you stopped cheating on tests?”, unless it has previously been established that the person is indeed cheating on tests, is a fallacy.
  • Begging the question fallacy occurs when we assume the very thing as a premise that we’re trying to prove in our conclusion. In other words, the conclusion is used to support the premises, and the premises prove the validity of the conclusion. For example: “God exists because the Bible says so, and the Bible is true because it is the word of God.”

In other words, begging the question is about drawing a conclusion based on an assumption, while a complex question involves asking a question that presupposes the answer to a prior question.

“ No true Scotsman ” arguments aren’t always fallacious. When there is a generally accepted definition of who or what constitutes a group, it’s reasonable to use statements in the form of “no true Scotsman”.

For example, the statement that “no true pacifist would volunteer for military service” is not fallacious, since a pacifist is, by definition, someone who opposes war or violence as a means of settling disputes.

No true Scotsman arguments are fallacious because instead of logically refuting the counterexample, they simply assert that it doesn’t count. In other words, the counterexample is rejected for psychological, but not logical, reasons.

The appeal to purity or no true Scotsman fallacy is an attempt to defend a generalisation about a group from a counterexample by shifting the definition of the group in the middle of the argument. In this way, one can exclude the counterexample as not being “true”, “genuine”, or “pure” enough to be considered as part of the group in question.

To identify an appeal to authority fallacy , you can ask yourself the following questions:

  • Is the authority cited really a qualified expert in this particular area under discussion? For example, someone who has formal education or years of experience can be an expert.
  • Do experts disagree on this particular subject? If that is the case, then for almost any claim supported by one expert there will be a counterclaim that is supported by another expert. If there is no consensus, an appeal to authority is fallacious.
  • Is the authority in question biased? If you suspect that an expert’s prejudice and bias could have influenced their views, then the expert is not reliable and an argument citing this expert will be fallacious.To identify an appeal to authority fallacy, you ask yourself whether the authority cited is a qualified expert in the particular area under discussion.

Appeal to authority is a fallacy when those who use it do not provide any justification to support their argument. Instead they cite someone famous who agrees with their viewpoint, but is not qualified to make reliable claims on the subject.

Appeal to authority fallacy is often convincing because of the effect authority figures have on us. When someone cites a famous person, a well-known scientist, a politician, etc. people tend to be distracted and often fail to critically examine whether the authority figure is indeed an expert in the area under discussion.

The ad populum fallacy is common in politics. One example is the following viewpoint: “The majority of our countrymen think we should have military operations overseas; therefore, it’s the right thing to do.”

This line of reasoning is fallacious, because popular acceptance of a belief or position does not amount to a justification of that belief. In other words, following the prevailing opinion without examining the underlying reasons is irrational.

The ad populum fallacy plays on our innate desire to fit in (known as “bandwagon effect”). If many people believe something, our common sense tells us that it must be true and we tend to accept it. However, in logic, the popularity of a proposition cannot serve as evidence of its truthfulness.

Ad populum (or appeal to popularity) fallacy and appeal to authority fallacy are similar in that they both conflate the validity of a belief with its popular acceptance among a specific group. However there is a key difference between the two:

  • An ad populum fallacy tries to persuade others by claiming that something is true or right because a lot of people think so.
  • An appeal to authority fallacy tries to persuade by claiming a group of experts believe something is true or right, therefore it must be so.

To identify a false cause fallacy , you need to carefully analyse the argument:

  • When someone claims that one event directly causes another, ask if there is sufficient evidence to establish a cause-and-effect relationship. 
  • Ask if the claim is based merely on the chronological order or co-occurrence of the two events. 
  • Consider alternative possible explanations (are there other factors at play that could influence the outcome?).

By carefully analysing the reasoning, considering alternative explanations, and examining the evidence provided, you can identify a false cause fallacy and discern whether a causal claim is valid or flawed.

False cause fallacy examples include: 

  • Believing that wearing your lucky jersey will help your team win 
  • Thinking that everytime you wash your car, it rains
  • Claiming that playing video games causes violent behavior 

In each of these examples, we falsely assume that one event causes another without any proof.

The planning fallacy and procrastination are not the same thing. Although they both relate to time and task management, they describe different challenges:

  • The planning fallacy describes our inability to correctly estimate how long a future task will take, mainly due to optimism bias and a strong focus on the best-case scenario.
  • Procrastination refers to postponing a task, usually by focusing on less urgent or more enjoyable activities. This is due to psychological reasons, like fear of failure.

In other words, the planning fallacy refers to inaccurate predictions about the time we need to finish a task, while procrastination is a deliberate delay due to psychological factors.

A real-life example of the planning fallacy is the construction of the Sydney Opera House in Australia. When construction began in the late 1950s, it was initially estimated that it would be completed in four years at a cost of around $7 million.

Because the government wanted the construction to start before political opposition would stop it and while public opinion was still favorable, a number of design issues had not been carefully studied in advance. Due to this, several problems appeared immediately after the project commenced.

The construction process eventually stretched over 14 years, with the Opera House being completed in 1973 at a cost of over $100 million, significantly exceeding the initial estimates.

An example of appeal to pity fallacy is the following appeal by a student to their professor:

“Professor, please consider raising my grade. I had a terrible semester: my car broke down, my laptop got stolen, and my cat got sick.”

While these circumstances may be unfortunate, they are not directly related to the student’s academic performance.

While both the appeal to pity fallacy and   red herring fallacy can serve as a distraction from the original discussion topic, they are distinct fallacies. More specifically:

  • Appeal to pity fallacy attempts to evoke feelings of sympathy, pity, or guilt in an audience, so that they accept the speaker’s conclusion as truthful.
  • Red herring fallacy attempts to introduce an irrelevant piece of information that diverts the audience’s attention to a different topic.

Both fallacies can be used as a tool of deception. However, they operate differently and serve distinct purposes in arguments.

Argumentum ad misericordiam (Latin for “argument from pity or misery”) is another name for appeal to pity fallacy . It occurs when someone evokes sympathy or guilt in an attempt to gain support for their claim, without providing any logical reasons to support the claim itself. Appeal to pity is a deceptive tactic of argumentation, playing on people’s emotions to sway their opinion.

Yes, it’s quite common to start a sentence with a preposition, and there’s no reason not to do so.

For example, the sentence “ To many, she was a hero” is perfectly grammatical. It could also be rephrased as “She was a hero to  many”, but there’s no particular reason to do so. Both versions are fine.

Some people argue that you shouldn’t end a sentence with a preposition , but that “rule” can also be ignored, since it’s not supported by serious language authorities.

Yes, it’s fine to end a sentence with a preposition . The “rule” against doing so is overwhelmingly rejected by modern style guides and language authorities and is based on the rules of Latin grammar, not English.

Trying to avoid ending a sentence with a preposition often results in very unnatural phrasings. For example, turning “He knows what he’s talking about ” into “He knows about what he’s talking” or “He knows that about which he’s talking” is definitely not an improvement.

No, ChatGPT is not a credible source of factual information and can’t be cited for this purpose in academic writing . While it tries to provide accurate answers, it often gets things wrong because its responses are based on patterns, not facts and data.

Specifically, the CRAAP test for evaluating sources includes five criteria: currency , relevance , authority , accuracy , and purpose . ChatGPT fails to meet at least three of them:

  • Currency: The dataset that ChatGPT was trained on only extends to 2021, making it slightly outdated.
  • Authority: It’s just a language model and is not considered a trustworthy source of factual information.
  • Accuracy: It bases its responses on patterns rather than evidence and is unable to cite its sources .

So you shouldn’t cite ChatGPT as a trustworthy source for a factual claim. You might still cite ChatGPT for other reasons – for example, if you’re writing a paper about AI language models, ChatGPT responses are a relevant primary source .

ChatGPT is an AI language model that was trained on a large body of text from a variety of sources (e.g., Wikipedia, books, news articles, scientific journals). The dataset only went up to 2021, meaning that it lacks information on more recent events.

It’s also important to understand that ChatGPT doesn’t access a database of facts to answer your questions. Instead, its responses are based on patterns that it saw in the training data.

So ChatGPT is not always trustworthy . It can usually answer general knowledge questions accurately, but it can easily give misleading answers on more specialist topics.

Another consequence of this way of generating responses is that ChatGPT usually can’t cite its sources accurately. It doesn’t really know what source it’s basing any specific claim on. It’s best to check any information you get from it against a credible source .

No, it is not possible to cite your sources with ChatGPT . You can ask it to create citations, but it isn’t designed for this task and tends to make up sources that don’t exist or present information in the wrong format. ChatGPT also cannot add citations to direct quotes in your text.

Instead, use a tool designed for this purpose, like the Scribbr Citation Generator .

But you can use ChatGPT for assignments in other ways, to provide inspiration, feedback, and general writing advice.

GPT  stands for “generative pre-trained transformer”, which is a type of large language model: a neural network trained on a very large amount of text to produce convincing, human-like language outputs. The Chat part of the name just means “chat”: ChatGPT is a chatbot that you interact with by typing in text.

The technology behind ChatGPT is GPT-3.5 (in the free version) or GPT-4 (in the premium version). These are the names for the specific versions of the GPT model. GPT-4 is currently the most advanced model that OpenAI has created. It’s also the model used in Bing’s chatbot feature.

ChatGPT was created by OpenAI, an AI research company. It started as a nonprofit company in 2015 but became for-profit in 2019. Its CEO is Sam Altman, who also co-founded the company. OpenAI released ChatGPT as a free “research preview” in November 2022. Currently, it’s still available for free, although a more advanced premium version is available if you pay for it.

OpenAI is also known for developing DALL-E, an AI image generator that runs on similar technology to ChatGPT.

ChatGPT is owned by OpenAI, the company that developed and released it. OpenAI is a company dedicated to AI research. It started as a nonprofit company in 2015 but transitioned to for-profit in 2019. Its current CEO is Sam Altman, who also co-founded the company.

In terms of who owns the content generated by ChatGPT, OpenAI states that it will not claim copyright on this content , and the terms of use state that “you can use Content for any purpose, including commercial purposes such as sale or publication”. This means that you effectively own any content you generate with ChatGPT and can use it for your own purposes.

Be cautious about how you use ChatGPT content in an academic context. University policies on AI writing are still developing, so even if you “own” the content, you’re often not allowed to submit it as your own work according to your university or to publish it in a journal.

ChatGPT is a chatbot based on a large language model (LLM). These models are trained on huge datasets consisting of hundreds of billions of words of text, based on which the model learns to effectively predict natural responses to the prompts you enter.

ChatGPT was also refined through a process called reinforcement learning from human feedback (RLHF), which involves “rewarding” the model for providing useful answers and discouraging inappropriate answers – encouraging it to make fewer mistakes.

Essentially, ChatGPT’s answers are based on predicting the most likely responses to your inputs based on its training data, with a reward system on top of this to incentivise it to give you the most helpful answers possible. It’s a bit like an incredibly advanced version of predictive text. This is also one of ChatGPT’s limitations : because its answers are based on probabilities, they’re not always trustworthy .

OpenAI may store ChatGPT conversations for the purposes of future training. Additionally, these conversations may be monitored by human AI trainers.

Users can choose not to have their chat history saved. Unsaved chats are not used to train future models and are permanently deleted from ChatGPT’s system after 30 days.

The official ChatGPT app is currently only available on iOS devices. If you don’t have an iOS device, only use the official OpenAI website to access the tool. This helps to eliminate the potential risk of downloading fraudulent or malicious software.

ChatGPT conversations are generally used to train future models and to resolve issues/bugs. These chats may be monitored by human AI trainers.

However, users can opt out of having their conversations used for training. In these instances, chats are monitored only for potential abuse.

Yes, using ChatGPT as a conversation partner is a great way to practice a language in an interactive way.

Try using a prompt like this one:

“Please be my Spanish conversation partner. Only speak to me in Spanish. Keep your answers short (maximum 50 words). Ask me questions. Let’s start the conversation with the following topic: [conversation topic].”

Yes, there are a variety of ways to use ChatGPT for language learning , including treating it as a conversation partner, asking it for translations, and using it to generate a curriculum or practice exercises.

AI detectors aim to identify the presence of AI-generated text (e.g., from ChatGPT ) in a piece of writing, but they can’t do so with complete accuracy. In our comparison of the best AI detectors , we found that the 10 tools we tested had an average accuracy of 60%. The best free tool had 68% accuracy, the best premium tool 84%.

Because of how AI detectors work , they can never guarantee 100% accuracy, and there is always at least a small risk of false positives (human text being marked as AI-generated). Therefore, these tools should not be relied upon to provide absolute proof that a text is or isn’t AI-generated. Rather, they can provide a good indication in combination with other evidence.

Tools called AI detectors are designed to label text as AI-generated or human. AI detectors work by looking for specific characteristics in the text, such as a low level of randomness in word choice and sentence length. These characteristics are typical of AI writing, allowing the detector to make a good guess at when text is AI-generated.

But these tools can’t guarantee 100% accuracy. Check out our comparison of the best AI detectors to learn more.

You can also manually watch for clues that a text is AI-generated – for example, a very different style from the writer’s usual voice or a generic, overly polite tone.

Our research into the best summary generators (aka summarisers or summarising tools) found that the best summariser available in 2023 is the one offered by QuillBot.

While many summarisers just pick out some sentences from the text, QuillBot generates original summaries that are creative, clear, accurate, and concise. It can summarise texts of up to 1,200 words for free, or up to 6,000 with a premium subscription.

Try the QuillBot summarizer for free

Deep learning requires a large dataset (e.g., images or text) to learn from. The more diverse and representative the data, the better the model will learn to recognise objects or make predictions. Only when the training data is sufficiently varied can the model make accurate predictions or recognise objects from new data.

Deep learning models can be biased in their predictions if the training data consist of biased information. For example, if a deep learning model used for screening job applicants has been trained with a dataset consisting primarily of white male applicants, it will consistently favour this specific population over others.

A good ChatGPT prompt (i.e., one that will get you the kinds of responses you want):

  • Gives the tool a role to explain what type of answer you expect from it
  • Is precisely formulated and gives enough context
  • Is free from bias
  • Has been tested and improved by experimenting with the tool

ChatGPT prompts are the textual inputs (e.g., questions, instructions) that you enter into ChatGPT to get responses.

ChatGPT predicts an appropriate response to the prompt you entered. In general, a more specific and carefully worded prompt will get you better responses.

Yes, ChatGPT is currently available for free. You have to sign up for a free account to use the tool, and you should be aware that your data may be collected to train future versions of the model.

To sign up and use the tool for free, go to this page and click “Sign up”. You can do so with your email or with a Google account.

A premium version of the tool called ChatGPT Plus is available as a monthly subscription. It currently costs £16 and gets you access to features like GPT-4 (a more advanced version of the language model). But it’s optional: you can use the tool completely free if you’re not interested in the extra features.

You can access ChatGPT by signing up for a free account:

  • Follow this link to the ChatGPT website.
  • Click on “Sign up” and fill in the necessary details (or use your Google account). It’s free to sign up and use the tool.
  • Type a prompt into the chat box to get started!

A ChatGPT app is also available for iOS, and an Android app is planned for the future. The app works similarly to the website, and you log in with the same account for both.

According to OpenAI’s terms of use, users have the right to reproduce text generated by ChatGPT during conversations.

However, publishing ChatGPT outputs may have legal implications , such as copyright infringement.

Users should be aware of such issues and use ChatGPT outputs as a source of inspiration instead.

According to OpenAI’s terms of use, users have the right to use outputs from their own ChatGPT conversations for any purpose (including commercial publication).

However, users should be aware of the potential legal implications of publishing ChatGPT outputs. ChatGPT responses are not always unique: different users may receive the same response.

Furthermore, ChatGPT outputs may contain copyrighted material. Users may be liable if they reproduce such material.

ChatGPT can sometimes reproduce biases from its training data , since it draws on the text it has “seen” to create plausible responses to your prompts.

For example, users have shown that it sometimes makes sexist assumptions such as that a doctor mentioned in a prompt must be a man rather than a woman. Some have also pointed out political bias in terms of which political figures the tool is willing to write positively or negatively about and which requests it refuses.

The tool is unlikely to be consistently biased toward a particular perspective or against a particular group. Rather, its responses are based on its training data and on the way you phrase your ChatGPT prompts . It’s sensitive to phrasing, so asking it the same question in different ways will result in quite different answers.

Information extraction  refers to the process of starting from unstructured sources (e.g., text documents written in ordinary English) and automatically extracting structured information (i.e., data in a clearly defined format that’s easily understood by computers). It’s an important concept in natural language processing (NLP) .

For example, you might think of using news articles full of celebrity gossip to automatically create a database of the relationships between the celebrities mentioned (e.g., married, dating, divorced, feuding). You would end up with data in a structured format, something like MarriageBetween(celebrity 1 ,celebrity 2 ,date) .

The challenge involves developing systems that can “understand” the text well enough to extract this kind of data from it.

Knowledge representation and reasoning (KRR) is the study of how to represent information about the world in a form that can be used by a computer system to solve and reason about complex problems. It is an important field of artificial intelligence (AI) research.

An example of a KRR application is a semantic network, a way of grouping words or concepts by how closely related they are and formally defining the relationships between them so that a machine can “understand” language in something like the way people do.

A related concept is information extraction , concerned with how to get structured information from unstructured sources.

Yes, you can use ChatGPT to summarise text . This can help you understand complex information more easily, summarise the central argument of your own paper, or clarify your research question.

You can also use Scribbr’s free text summariser , which is designed specifically for this purpose.

Yes, you can use ChatGPT to paraphrase text to help you express your ideas more clearly, explore different ways of phrasing your arguments, and avoid repetition.

However, it’s not specifically designed for this purpose. We recommend using a specialised tool like Scribbr’s free paraphrasing tool , which will provide a smoother user experience.

Yes, you use ChatGPT to help write your college essay by having it generate feedback on certain aspects of your work (consistency of tone, clarity of structure, etc.).

However, ChatGPT is not able to adequately judge qualities like vulnerability and authenticity. For this reason, it’s important to also ask for feedback from people who have experience with college essays and who know you well. Alternatively, you can get advice using Scribbr’s essay editing service .

No, having ChatGPT write your college essay can negatively impact your application in numerous ways. ChatGPT outputs are unoriginal and lack personal insight.

Furthermore, Passing off AI-generated text as your own work is considered academically dishonest . AI detectors may be used to detect this offense, and it’s highly unlikely that any university will accept you if you are caught submitting an AI-generated admission essay.

However, you can use ChatGPT to help write your college essay during the preparation and revision stages (e.g., for brainstorming ideas and generating feedback).

ChatGPT and other AI writing tools can have unethical uses. These include:

  • Reproducing biases and false information
  • Using ChatGPT to cheat in academic contexts
  • Violating the privacy of others by inputting personal information

However, when used correctly, AI writing tools can be helpful resources for improving your academic writing and research skills. Some ways to use ChatGPT ethically include:

  • Following your institution’s guidelines
  • Critically evaluating outputs
  • Being transparent about how you used the tool

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  • February 8, 2024
  • Academic Advice , Education Advice

Dissertation vs Thesis: Understanding the Key Differences

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dissertation-vs-thesis

Embarking on an academic journey often involves deciphering the complexities of advanced research projects like dissertations and theses. While these terms might seem interchangeable, they possess distinctive changes in the world of higher education. A fundamental distinction between a thesis and a dissertation lies in their approach to research. A thesis typically involves synthesizing existing research and knowledge in your field, while a dissertation requires conducting original research, addressing research gaps, and making a substantive contribution to the academic domain. 

As you continue your higher education journey in academia, it’s critical to decipher the fundamental differences between dissertation and thesis that set them apart.

What Is a Thesis?

A thesis is a long-term academic research paper that presents an in-depth review of existing research on a specific subject. It requires extensive research, data collection, analysis, and critical interpretation of the findings. Although some undergraduate programs may mandate a thesis, it is more commonly expected in postgraduate studies, such as upon completing a master’s degree . 

What Is a Dissertation?

A dissertation is a longer and more comprehensive research project based on original research. It’s a substantial piece of academic writing required for the completion of a doctoral degree . The dissertation is the culmination of years of research, study, and expertise, contributing valuable insights in a particular field of study. 

dissertation-vs-thesis

Dissertation vs Thesis: Key Differences

Both theses and dissertations serve as culminating projects for program graduation, demanding a profound grasp of the research subject and analytical skills to substantiate findings. Despite these commonalities, significant differences set them apart. The key differences include: 

Academic and Research Requirements

The academic requirements for a doctoral dissertation are clearly defined hypotheses, a detailed methodology section, rigorous data analysis, and a critical discussion of the results in the context of existing literature.

In contrast, the requirements for a master’s thesis include a thorough literature review, methodology, data analysis, and a conclusion that summarizes the findings.

Research requirements are also more extensive for dissertations compared to theses, as they include conducting original experiments and studies.

Length and Complexity

The length of a dissertation or a thesis varies according to the topic and the method of analysis, or it can vary based on the departmental requirements. Usually, a master’s thesis is around 40-80 pages, sometimes up to 100 pages. A dissertation, however, is significantly longer, ranging from 100 to 300 pages and sometimes up to 400. 

Dissertations and theses also vary on the level of complexity. While the thesis requires a thorough literature review and analysis of existing research, it’s less complex than a dissertation. Moreover, the original research is limited, contrary to dissertations involving extensive original research (experiments and studies). 

Research Objectives

The research objectives are an essential component that can guide the research project and highlight the specific goals to achieve. Moreover, they outline the grounds for pursuing a particular topic.

However, they can vary depending on the academic level and the nature of the research. In a master’s thesis, the research objectives usually focus on addressing specific research questions related to the chosen topic, to deepen the understanding of existing theories within the field of study. Contrarily, in a doctoral dissertation, the research objectives are broader and are formulated to address complex research gaps, propose new theories, and contribute to the academic field. 

Timeframe and Milestones

The timeframe depends on internal factors like the student’s work pace and personal circumstances and external factors like the complexity of the subject, availability of resources, and academic level. While we can’t give a definitive answer, it usually takes a couple of semesters or 1-2 years to complete a master’s thesis. On the contrary, a doctoral dissertation is more time-consuming and can take 4-7 years to complete. 

Although there are many similarities between the milestones for completing a thesis and a dissertation, such as topic selection, literature review, and data collection, their differences lie in the higher complexity of doctoral dissertations, including original research, review by the advisory committee, and publication. 

Review and Approval Process

The review and approval process is vital to evaluate the quality of research, analysis, and presentation. Although the overall process is similar for both a master’s thesis and a doctoral dissertation, the scrutiny applied to dissertations is notably more rigorous. For a master’s thesis, a committee of professors or advisors within the university’s department evaluates the thesis for adherence to academic standards, clarity, and coherence. Following the review, approval is granted to the thesis if the evaluators are content with the student’s work. On the other hand, for a doctoral dissertation, the review process includes a committee of experts in the field, often external reviewers, to assess the dissertation’s quality, methodology, and contribution to the academic field. The approval process is more challenging as it may require defending the dissertation orally and answering questions from the committee members and to a broader audience than a master’s thesis presentation.

Potential for Publication

Lastly, one of the main differences between a dissertation and a thesis is the potential for publication. As the dissertation is more extensive and requires original research contributing to the academic field, theses are less likely to be published in a peer-reviewed journal. Although a master’s thesis is more narrowly focused, it can still be published as a single article. In contrast, a doctoral dissertation is generally equivalent to at least three articles. 

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The Scope of Dissertation vs Thesis

While both require extensive research and dedication, the thesis has a narrower scope on a specific topic within the field of study. It aims to illustrate the student’s mastery of the subject matter, ability to synthesize existing research, and ability to present coherent arguments. On the other hand, the dissertation has a broader scope , encompassing a comprehensive analysis of a complex research problem or exploring interconnected topics in the field. It aims to showcase the student’s expertise and ability to conduct original and independent research and contribute new knowledge in the field. 

As we draw the curtain in exploring the factors that differentiate a thesis and a dissertation, it becomes evident that both academic endeavors are crucial in unraveling discoveries. A master’s thesis showcases analytical finesse and a deep understanding of existing theories. And a doctoral dissertation displays new groundbreaking insights, original research, and innovative methodologies. Therefore, while they may have substantial differences, they remain a driving force in shaping the future of academia. 

Frequently Asked Questions (FAQs): What is the main difference between a dissertation and a thesis?

While many factors differentiate a dissertation and a thesis, the main difference is their academic level. A thesis is usually required at the end of a master’s degree program. In contrast, a dissertation is necessary to complete a doctoral degree.

How long does it take to complete a thesis or a dissertation?

The time it takes to complete a thesis or a dissertation depends on the complexity of the research, the availability of resources, and the student’s work pace. Usually, it takes a couple of semesters to complete a thesis at the end of a master’s program. In contrast, completing a doctoral dissertation can take four to seven years.

Is there a difference in the level of research expected in a dissertation vs a thesis?

Although a thesis requires a significant amount of research literature review and analysis of existing studies, a dissertation demands a higher level of original research through identifying research gaps, developing new hypotheses, conducting experiments, and collecting and analyzing data. 

Are there any specific publication or accessibility differences between dissertations and theses?

Yes, there are specific publication and accessibility differences between dissertations and theses. Doctoral dissertations are usually published and made public through university libraries or digital repositories. Whereas a master’s thesis is less frequently published in academic journals compared to doctoral dissertations. Theses are often made available within the university’s library or department.

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Thesis and Dissertation: Getting Started

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The resources in this section are designed to provide guidance for the first steps of the thesis or dissertation writing process. They offer tools to support the planning and managing of your project, including writing out your weekly schedule, outlining your goals, and organzing the various working elements of your project.

Weekly Goals Sheet (a.k.a. Life Map) [Word Doc]

This editable handout provides a place for you to fill in available time blocks on a weekly chart that will help you visualize the amount of time you have available to write. By using this chart, you will be able to work your writing goals into your schedule and put these goals into perspective with your day-to-day plans and responsibilities each week. This handout also contains a formula to help you determine the minimum number of pages you would need to write per day in order to complete your writing on time.

Setting a Production Schedule (Word Doc)

This editable handout can help you make sense of the various steps involved in the production of your thesis or dissertation and determine how long each step might take. A large part of this process involves (1) seeking out the most accurate and up-to-date information regarding specific document formatting requirements, (2) understanding research protocol limitations, (3) making note of deadlines, and (4) understanding your personal writing habits.

Creating a Roadmap (PDF)

Part of organizing your writing involves having a clear sense of how the different working parts relate to one another. Creating a roadmap for your dissertation early on can help you determine what the final document will include and how all the pieces are connected. This resource offers guidance on several approaches to creating a roadmap, including creating lists, maps, nut-shells, visuals, and different methods for outlining. It is important to remember that you can create more than one roadmap (or more than one type of roadmap) depending on how the different approaches discussed here meet your needs.

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Dissertation vs Thesis: Your 2024 Guide

Chriselle Sy

If you’ve been thinking about going to graduate school, you may be familiar with the application requirements, rigorous academic schedule, and thesis or dissertation you’ll be expected to complete. So, what exactly is the difference between a thesis and a dissertation? While there are similarities, there’s a clear difference between the two. In our guide, we compare dissertation vs thesis. Discover more about both – and what you can expect during your graduate program. Let’s get started!

  • Table of Contents

What Is a Thesis?

A thesis is an academic paper or project that’s completed towards the end of a master’s degree program . It is typically completed as the capstone project , meaning it’s the final project required for a student to graduate.

Students need to select a narrow, specific topic within – or relating to – their field of study. Once they’ve selected a topic, students must conduct an in-depth review of existing research on their chosen subjects. The next step is to formulate an academic argument, an assertion they’ll need to support or prove with said research.

Therefore, a thesis is akin to an in-depth research paper. It’s comprised of research that essentially proves what a student has learned during their program.

What Is a Typical Thesis Structure?

A thesis generally follows a rigid structure that’s decided by the program, department, or university. Here is an example of a thesis structure:

  • The Title Page
  • Summary of Thesis Abstract
  • Table of Maps and Figures
  • The Thesis Body (Sometimes divided into chapters)
  • The Results or Conclusion

Who Needs to Complete a Thesis?

Most master’s degree programs require students to complete a thesis. While some undergraduate programs may also require a thesis, these are generally shorter and narrower in scope.

Some programs will also require a master’s student to defend their thesis in front of a panel or committee.

What Is a Dissertation?

What is “the PhD paper” called? Some people refer to it as a PhD thesis, but it’s most commonly known as a dissertation in the US. Dissertations are the capstone project required at the tail end of a PhD program . It is almost always required, except for a select few one-year PhD programs .

Much like a thesis, dissertations are also academic papers that aim to prove a student’s expertise – while adding to the current body of knowledge – in their field. Thus, a student must look at existing research and conduct their own research .

dissertation academic or professional

Basically, it’s the magnum opus of a doctoral journey in the United States. A dissertation isn’t just a long research paper; it’s a beast of a project. It demands extensive research, originality, and the ability to make a meaningful contribution to your chosen field. Think of it as a research odyssey guided by a seasoned mentor. Once you’ve conquered this scholarly quest and defended your findings, you’ll proudly emerge with your hard-earned doctoral degree, a testament to your dedication and scholarly prowess.

A dissertation typically comes after a PhD student completes their required courses and passes their qualifying exams. In some programs, the dissertation process is embedded into the coursework. In such cases, students receive a jump start on their work, allowing them to potentially finish their program earlier.

What Does a Dissertation Do?

PhD candidates must present a new theory or hypothesis. Alternatively, they must present their research to question (or disprove) the existing accepted theory on their chosen subject. Students may choose to tackle their topic from a new angle or take their research in a different direction.

Most programs will require students to defend their dissertations. During the defense, candidates must be able to justify the methodology of their research and the results and interpretation of their findings. Defenses are typically oral presentations in front of a dissertation committee , where the students are asked questions or presented with challenges.

Although the defense may seem daunting, PhD students work closely with their advisors to prepare for their dissertations. Students receive feedback and advice to guide their dissertations in their chosen direction.

What Is the Typical Dissertation Structure? 

Dissertations follow a rigid structure typically set by the program, department, or university. Here is an example format:

  • The Acknowledgments Page
  • The Abstract
  • Introduction
  • The Literature Review & Theoretical Framework
  • The Methodology
  • Findings/Results
  • Discussions of the Findings, including analysis, interpretation, and applications
  • The Conclusion
  • List of References
  • Any Appendices

What Is a Doctoral Thesis?

A doctoral thesis is a substantial piece of scholarly work that marks the pinnacle of a doctoral degree program, such as a PhD. Think of it as the academic grand finale. Its primary mission? To showcase the candidate’s mastery in their chosen field and their knack for delving deep into research.

dissertation academic or professional

In a nutshell, a doctoral thesis is a mammoth project that calls for originality. You’ve got to dig, investigate, gather data, crunch numbers, and present real data-supported findings. All this hard work usually happens under the watchful eye of a knowledgeable mentor. Once you’ve conquered this scholarly mountain and defended your thesis successfully, you’ll be proudly awarded your well-deserved doctoral degree. It’s the hallmark of your expertise and contribution to your field.

And how does a doctoral thesis differ from a dissertation? That’s mainly a geographic explanation. While they’re largely similar in scope and purpose, when comparing a doctoral thesis vs. a dissertation:

  • A dissertation is the PhD capstone requirement in the US .
  • A doctoral thesis is the PhD capstone requirement in Europe .

Related Reading: The Easiest PhDs

Dissertation vs. Thesis: The Similarities

In the master’s thesis vs dissertation discussion, there are plenty of similarities. Both are lengthy academic papers that require intense research and original writing. They’re also capstone projects which are completed at the tail end of their respective programs.

Students must work closely with their respective committees (e.g., faculty members, advisors, professionals) who provide feedback and guidance on their research, writing, and academic arguments. Both thesis and dissertation committees have a committee chair with whom the students work closely.

In some ways, the requirements for theses and dissertations are quite similar. They require a skillful defense of a student’s academic arguments. What’s more, both papers require critical thinking and good analytical reasoning, as well as in-depth expertise in the chosen field of study.

Students must also invest a significant amount of time into both projects while also being able to accept and action feedback on their work.

Dissertation vs. Thesis: The Differences

What are the differences between a PhD dissertation vs. thesis? The first and most distinct difference is the degree program requiring a PhD dissertation or thesis. A dissertation is typically the capstone project for a doctorate, while a thesis is the capstone project for a master’s degree program (or undergraduate program).

Candidates will have to defend their dissertation during an oral presentation in front of their committee. Only some master’s theses require this.

During a thesis, students typically conduct research by reviewing existing literature and knowledge on their chosen subject. During a dissertation, students must do their own research and prove their theory, concept, or hypothesis. They should also expect to develop a unique concept and defend it based on the practical and theoretical results achieved from their rigorous research.

Theses are also typically shorter (around 40 to 80 pages). Dissertations, however, are much longer (between 100 and 300 pages). Of course, the actual length of the paper may depend on the topic, program, department, or university.

Related Reading : PhD Candidate vs Student: What’s the Difference? 

Dissertations and Theses: US vs. Europe

Whether you’re in the US or Europe, dissertations and theses are similar. However, European requirements and conventions differ slightly:

Doctoral Thesis

To ensure your PhD graduation, a dissertation is generally required. Doctoral theses in Europe are much like a PhD dissertation in the US : You must complete your own research and add to the existing body of knowledge in your field.

Master’s Dissertation

It may seem odd to require a dissertation for master’s degree programs, but in Europe, this is exactly what you’ll need. A master’s dissertation is a broader post-graduate program research project , though it’s most typically required for master’s programs.

Frequently Asked Questions

Here are a few of the most common questions we hear about the meaning of thesis vs. dissertation.

Is a Thesis and a Dissertation the Same?

Yes and no. In some ways, a dissertation and a thesis are the same. For example, both require original writing, critical skills, analytical thinking, plenty of research, and lots of academic effort. However, a thesis is more commonly reserved for master’s – and some undergraduate – programs. Dissertations are generally required by PhD programs in the United States.

Additionally, a thesis typically calls for heavy research and compilation of existing knowledge and literature on a subject. A dissertation requires candidates to conduct their own research to prove their own theory, concept, or hypothesis – adding to the existing body of knowledge in their chosen field of study.

How Long Is a Thesis vs. a Dissertation?

One of the primary differences between thesis and dissertation papers is their length. While a thesis might be anywhere from 40 to 80 pages long, a dissertation can easily run from 100 to 300. It’s important to note that these numbers depend on the specific program and university.

Does a PhD Require a Thesis or a Dissertation?

It all depends on where you are! While a US-based PhD requires you to complete a dissertation, a thesis (or “doctoral thesis”) is more commonly required for PhD candidates in Europe. In the US, a thesis is more commonly reserved for master’s degree programs and occasionally undergraduate programs. In Europe, a “master’s dissertation” is typically required for the completion of a master’s degree.

So, there you have it: an in-depth comparison of the dissertation vs. thesis academic requirements. Now that you know the primary similarities and differences between the two, it might become easier to decide your academic path. Just remember, you may be able to find a master’s program without a thesis or a doctorate without a dissertation requirement if you prefer. Good luck!

Are you ready to jump into your doctorate? Find out if you need a master’s degree to get a PhD .

dissertation academic or professional

Chriselle Sy

Chriselle has been a passionate professional content writer for over 10 years. She writes educational content for The Grad Cafe, Productivity Spot, The College Monk, and other digital publications.  When she isn't busy writing, she spends her time streaming video games and learning new skills.

  • Chriselle Sy https://blog.thegradcafe.com/author/chriselle-sy/ Graduate Certificate vs Degree: What’s the Difference? [2024 Guide]
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Published by Nicolas at January 17th, 2024 , Revised On January 23, 2024

Dissertation Vs Thesis: How Are They Different

Dissertation vs thesis! What are you writing? 

Table of Contents

Many graduate students from universities in Canada often get confused and mix both terms. While these terms are often used interchangeably, they carry distinct meanings and purposes in academia. Read this blog to fully understand the difference between a thesis and a dissertation. 

What Is A Dissertation

A dissertation is a substantial piece of academic writing typically required to complete a doctoral degree (such as a Ph.D.). It represents an original and significant contribution to the field of study and is usually the culmination of several years of research and study.

What Is A Thesis

A thesis is a scholarly piece of writing, usually at the master’s or undergraduate level, that presents an original research question, methodology, and findings. It represents the culmination of a student’s academic work and demonstrates their ability to contribute to the field of study.

The Evolution Of Dissertation Vs Thesis

The history of the thesis and dissertation dates back several centuries, and the evolution of these academic documents reflects changes in scholarly practices, educational systems, and the expectations of advanced degree programs. 

Medieval Origins

The concept of a scholarly thesis has roots in medieval universities. In the 12th and 13th centuries, institutions like the University of Paris introduced the practice of disputations, where students defended their theses in a public forum. These early theses were often theological or philosophical in nature.

Renaissance And Early Modern Period

During the Renaissance, the practice of defending theses continued to evolve. The 16th and 17th centuries saw an increasing emphasis on empirical observation and scientific inquiry. The thesis became more diverse, covering topics in natural philosophy, mathematics, and other emerging disciplines.

18th And 19th Centuries

The 18th century marked the formalization of the thesis as a requirement for academic degrees. Universities started to mandate the submission of a written document along with the oral defence. This practice became more standardized in the 19th century as universities across Europe and North America adopted similar academic norms.

Evolution Of The Dissertation

The term “dissertation” has its roots in the Latin word “dissertatio,” meaning “discussion.” Dissertations, as we understand them today, emerged in the 19th century, primarily in German universities. Doctoral candidates were required to produce substantial research demonstrating their ability to contribute original knowledge to their field.

20th Century

The 20th century saw a global expansion of higher education and an increase in the number of doctoral programs. The thesis and dissertation became integral components of graduate education worldwide. The structure, format (eg, APA or MLA ), and expectations for these documents varied among disciplines and institutions.

Electronic Theses And Dissertations (ETDs)

With the advent of digital technology in the late 20th century, there was a shift toward electronic submission of theses and dissertations. This made research papers more accessible and facilitated the dissemination of knowledge. Many universities now require the submission of ETDs.

Contemporary Trends In Dissertation Vs Thesis

In the 21st century, the thesis and dissertation continue to evolve. Educational institutions are adapting to new forms of scholarship , interdisciplinary research, and varied modes of dissemination. The focus is often on producing high-quality, original research that contributes significantly to the academic community.

What Is The Difference Between A Dissertation And A Thesis 

Thesis vs dissertation: length and depth.

One of the key differences between a thesis vs dissertation lies in their length and depth of research:

Theses are typically shorter in length, ranging from 50 to 100 pages, depending on the institution and program requirements. The research conducted for a thesis is expected to contribute to the existing literature but may not need to be as exhaustive as that of a dissertation.

Dissertation

Dissertations, being the pinnacle of doctoral research, are substantially longer, often exceeding 100 pages and sometimes reaching several hundred pages. Doctoral candidates are expected to delve deeply into their chosen topic, conducting extensive research and offering a unique contribution to the academic community.

Dissertation Vs Thesis: Scope And Purpose

Another significant distinction between a dissertation vs thesis is the scope and purpose of the research:

The primary goal of a thesis is to demonstrate a student’s understanding of the subject and their ability to conduct independent research within a defined scope. A thesis is often more focused and may be an exploration or analysis of a specific aspect of a broader topic. For example, a finance thesis could be about any topic within the subject. 

Dissertations, being doctoral-level projects, have a broader scope. Doctoral candidates are expected to make an original and substantial contribution to the field, advancing existing knowledge and addressing gaps in the current literature. Dissertations often involve more extensive data collection, analysis, and synthesis of information.

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Dissertation Vs Thesis: The Similarities

While there are distinct differences between a thesis vs dissertation, they also share several similarities, reflecting their common purpose within academic research papers . Here are some key similarities between a dissertation and a thesis.

Research Component

Both dissertations and theses involve original research and scholarly inquiry. Students are expected to engage in a systematic investigation of a chosen topic, demonstrate a deep understanding of existing literature, and contribute new knowledge or insights to their field.

Academic Rigour

Both documents adhere to high standards of academic rigour and integrity. They require meticulous attention to detail, adherence to citation and referencing styles, and a commitment to intellectual honesty.

Formal Structure

Dissertations and theses typically follow a formal structure, including elements such as a thesis statement , an introduction, a literature review, methodology, results, a discussion, and a conclusion. This structured format ensures a comprehensive presentation of the research.

Faculty Guidance

In both cases, students work closely with faculty advisors or mentors throughout the research process. Advisors guide research design, literature review, data analysis, and other aspects of the project.

Oral Defense

A commonality between dissertations and theses is the requirement for an oral defence. In many academic institutions, students must defend their research findings before a committee of faculty members. This defence allows students to articulate their research methods, results, and conclusions, while also responding to questions and critiques.

Degree Requirement

Both a thesis and a dissertation serve as a crucial component for the completion of an academic degree. Thesis is typically associated with master’s programs, while dissertations are a requirement for doctoral degrees. In both cases, successfully completing the research project is essential for obtaining the respective degrees.

Contribution To Knowledge

Whether a thesis or a dissertation, the primary goal is to contribute to the existing body of knowledge in a particular field. Both documents aim to advance understanding, address gaps in the literature, and offer meaningful insights that can inform future research.

Literature Review

A comprehensive literature review is a common element in both dissertations and theses. This section provides context for the research by summarizing and critiquing relevant scholarly works, helping establish the rationale and significance of the study.

Frequently Asked Questions

What is the difference between a dissertation and a thesis.

A thesis is a shorter, master’s-level research document demonstrating mastery of a subject. A dissertation, typically for a doctoral degree, is longer and requires a more extensive, original contribution to the field.

What is the difference between a master thesis and dissertation?

A master’s thesis is a shorter research document showcasing mastery of a specific subject. A dissertation, associated with a doctoral degree, is more extensive, requiring a substantial, original contribution to the field.

Are thesis and dissertation the same thing?

No, a thesis and a dissertation are not the same. A thesis is a research document associated with a master’s degree, demonstrating mastery of a subject. A dissertation is a more extensive research document required for a doctoral degree, emphasizing original contribution to the field.

Where to find thesis and dissertations?

There are several online sources that can help you in finding the perfect thesis and dissertation for your research. ResearchProspect Canada is one of the leading and trustworthy brands, helping students achieve academic excellence.

What is electronic thesis and dissertation?

An Electronic Thesis and Dissertation (ETD) is a digital version of a student’s thesis or dissertation. It is submitted and stored electronically, allowing easy access, distribution, and archiving, reflecting the shift towards digital formats in academia.

How to cite theses and dissertation?

To cite theses and dissertations, follow the citation style specified by your academic institution or the preferred style guide (e.g., APA, MLA, Chicago). Include author, title, publication year, institution, and retrieval information for online sources, ensuring consistency and accuracy.

How to cite pro quest dissertation and theses APA?

To cite a ProQuest dissertation or thesis in APA format, use the following template: Author, A. A. (Year). Title of dissertation/thesis (Publication No.). ProQuest Dissertations and Theses Global. Include the ProQuest publication number for online sources.

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What Is Academic Writing? | Dos and Don’ts for Students

Academic writing is a formal style of writing used in universities and scholarly publications. You’ll encounter it in journal articles and books on academic topics, and you’ll be expected to write your essays , research papers , and dissertation in academic style.

Academic writing follows the same writing process as other types of texts, but it has specific conventions in terms of content, structure and style.

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Types of academic writing, academic writing is…, academic writing is not…, useful tools for academic writing, academic writing checklist.

Academics mostly write texts intended for publication, such as journal articles, reports, books, and chapters in edited collections. For students, the most common types of academic writing assignments are listed below.

Different fields of study have different priorities in terms of the writing they produce. For example, in scientific writing it’s crucial to clearly and accurately report methods and results; in the humanities, the focus is on constructing convincing arguments through the use of textual evidence. However, most academic writing shares certain key principles intended to help convey information as effectively as possible.

Whether your goal is to pass your degree, apply to graduate school , or build an academic career, effective writing is an essential skill.

Prevent plagiarism. Run a free check.

Formal and unbiased.

Academic writing aims to convey information in an impartial way. The goal is to base arguments on the evidence under consideration, not the author’s preconceptions. All claims should be supported with relevant evidence, not just asserted.

To avoid bias, it’s important to represent the work of other researchers and the results of your own research fairly and accurately. This means clearly outlining your methodology  and being honest about the limitations of your research.

The formal style used in academic writing ensures that research is presented consistently across different texts, so that studies can be objectively assessed and compared with other research.

Because of this, it’s important to strike the right tone with your language choices. Avoid informal language , including slang, contractions , clichés, and conversational phrases:

  • Also , a lot of the findings are a little unreliable.
  • Moreover , many of the findings are somewhat unreliable.

Clear and precise

It’s important to use clear and precise language to ensure that your reader knows exactly what you mean. This means being as specific as possible and avoiding vague language :

  • People have been interested in this thing for a long time .
  • Researchers have been interested in this phenomenon for at least 10 years .

Avoid hedging your claims with words like “perhaps,” as this can give the impression that you lack confidence in your arguments. Reflect on your word choice to ensure it accurately and directly conveys your meaning:

  • This could perhaps suggest that…
  • This suggests that…

Specialist language or jargon is common and often necessary in academic writing, which generally targets an audience of other academics in related fields.

However, jargon should be used to make your writing more concise and accurate, not to make it more complicated. A specialist term should be used when:

  • It conveys information more precisely than a comparable non-specialist term.
  • Your reader is likely to be familiar with the term.
  • The term is commonly used by other researchers in your field.

The best way to familiarize yourself with the kind of jargon used in your field is to read papers by other researchers and pay attention to their language.

Focused and well structured

An academic text is not just a collection of ideas about a topic—it needs to have a clear purpose. Start with a relevant research question or thesis statement , and use it to develop a focused argument. Only include information that is relevant to your overall purpose.

A coherent structure is crucial to organize your ideas. Pay attention to structure at three levels: the structure of the whole text, paragraph structure, and sentence structure.

Well sourced

Academic writing uses sources to support its claims. Sources are other texts (or media objects like photographs or films) that the author analyzes or uses as evidence. Many of your sources will be written by other academics; academic writing is collaborative and builds on previous research.

It’s important to consider which sources are credible and appropriate to use in academic writing. For example, citing Wikipedia is typically discouraged. Don’t rely on websites for information; instead, use academic databases and your university library to find credible sources.

You must always cite your sources in academic writing. This means acknowledging whenever you quote or paraphrase someone else’s work by including a citation in the text and a reference list at the end.

There are many different citation styles with different rules. The most common styles are APA , MLA , and Chicago . Make sure to consistently follow whatever style your institution requires. If you don’t cite correctly, you may get in trouble for plagiarism . A good plagiarism checker can help you catch any issues before it’s too late.

You can easily create accurate citations in APA or MLA style using our Citation Generators.

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Correct and consistent

As well as following the rules of grammar, punctuation, and citation, it’s important to consistently apply stylistic conventions regarding:

  • How to write numbers
  • Introducing abbreviations
  • Using verb tenses in different sections
  • Capitalization of terms and headings
  • Spelling and punctuation differences between UK and US English

In some cases there are several acceptable approaches that you can choose between—the most important thing is to apply the same rules consistently and to carefully proofread your text before you submit. If you don’t feel confident in your own proofreading abilities, you can get help from Scribbr’s professional proofreading services or Grammar Checker .

Academic writing generally tries to avoid being too personal. Information about the author may come in at some points—for example in the acknowledgements or in a personal reflection—but for the most part the text should focus on the research itself.

Always avoid addressing the reader directly with the second-person pronoun “you.” Use the impersonal pronoun “one” or an alternate phrasing instead for generalizations:

  • As a teacher, you must treat your students fairly.
  • As a teacher, one must treat one’s students fairly.
  • Teachers must treat their students fairly.

The use of the first-person pronoun “I” used to be similarly discouraged in academic writing, but it is increasingly accepted in many fields. If you’re unsure whether to use the first person, pay attention to conventions in your field or ask your instructor.

When you refer to yourself, it should be for good reason. You can position yourself and describe what you did during the research, but avoid arbitrarily inserting your personal thoughts and feelings:

  • In my opinion…
  • I think that…
  • I like/dislike…
  • I conducted interviews with…
  • I argue that…
  • I hope to achieve…

Long-winded

Many students think their writing isn’t academic unless it’s over-complicated and long-winded. This isn’t a good approach—instead, aim to be as concise and direct as possible.

If a term can be cut or replaced with a more straightforward one without affecting your meaning, it should be. Avoid redundant phrasings in your text, and try replacing phrasal verbs with their one-word equivalents where possible:

  • Interest in this phenomenon carried on in the year 2018 .
  • Interest in this phenomenon continued in 2018 .

Repetition is a part of academic writing—for example, summarizing earlier information in the conclusion—but it’s important to avoid unnecessary repetition. Make sure that none of your sentences are repeating a point you’ve already made in different words.

Emotive and grandiose

An academic text is not the same thing as a literary, journalistic, or marketing text. Though you’re still trying to be persuasive, a lot of techniques from these styles are not appropriate in an academic context. Specifically, you should avoid appeals to emotion and inflated claims.

Though you may be writing about a topic that’s sensitive or important to you, the point of academic writing is to clearly communicate ideas, information, and arguments, not to inspire an emotional response. Avoid using emotive or subjective language :

  • This horrible tragedy was obviously one of the worst catastrophes in construction history.
  • The injury and mortality rates of this accident were among the highest in construction history.

Students are sometimes tempted to make the case for their topic with exaggerated , unsupported claims and flowery language. Stick to specific, grounded arguments that you can support with evidence, and don’t overstate your point:

  • Charles Dickens is the greatest writer of the Victorian period, and his influence on all subsequent literature is enormous.
  • Charles Dickens is one of the best-known writers of the Victorian period and has had a significant influence on the development of the English novel.

There are a a lot of writing tools that will make your writing process faster and easier. We’ll highlight three of them below.

Paraphrasing tool

AI writing tools like ChatGPT and a paraphrasing tool can help you rewrite text so that your ideas are clearer, you don’t repeat yourself, and your writing has a consistent tone.

They can also help you write more clearly about sources without having to quote them directly. Be warned, though: it’s still crucial to give credit to all sources in the right way to prevent plagiarism .

Grammar checker

Writing tools that scan your text for punctuation, spelling, and grammar mistakes. When it detects a mistake the grammar checke r will give instant feedback and suggest corrections. Helping you write clearly and avoid common mistakes .

You can use a summarizer if you want to condense text into its most important and useful ideas. With a summarizer tool, you can make it easier to understand complicated sources. You can also use the tool to make your research question clearer and summarize your main argument.

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Use the checklist below to assess whether you have followed the rules of effective academic writing.

  • Checklist: Academic writing

I avoid informal terms and contractions .

I avoid second-person pronouns (“you”).

I avoid emotive or exaggerated language.

I avoid redundant words and phrases.

I avoid unnecessary jargon and define terms where needed.

I present information as precisely and accurately as possible.

I use appropriate transitions to show the connections between my ideas.

My text is logically organized using paragraphs .

Each paragraph is focused on a single idea, expressed in a clear topic sentence .

Every part of the text relates to my central thesis or research question .

I support my claims with evidence.

I use the appropriate verb tenses in each section.

I consistently use either UK or US English .

I format numbers consistently.

I cite my sources using a consistent citation style .

Your text follows the most important rules of academic style. Make sure it's perfect with the help of a Scribbr editor!

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How to Choose the Best Topic for Research: Top 100 Dissertation Topics

dissertation academic or professional

Are you searching for inspiration while writing your research paper? In this case, try looking up interesting research topics online. This article contains an abundance of dissertation topics, for every imaginable subject, like fashion or business leadership dissertation topics. You are going to find interesting examples! Don't forget that you can also get research paper help from our professional writing team.

Top 100 Dissertation Ideas 2023

Scholars often believe that today there is a lack of new dissertation topics. Indeed, people conduct research non-stop, and it seems like there is nothing new to discuss. So how to become a professional writer and avoid breaking intellectual property rights then?

Luckily for all enthusiastic scientists out there, there are topics for dissertation that cater to any taste. Our essay writers service presents various research topics suitable for multiple degrees. Do you study the job market, quantum physics, or human behavioral patterns? These and even more dissertation ideas are waiting for you.

How to Opt for a Dissertation Topic?

Sometimes, the immense choice of examples of dissertation topics makes you question your decision about your academic paper. Writers get recommendations from multiple sources. Before you write a dissertation, turn to more experienced people, like counselors or professors. They are likely to suggest great topics for dissertation. We also recommend that you read about how to write a dissertation .

For research and reference purposes, go online to discover new engaging themes. Your colleagues in the field of science communicate via special forums or websites, so join them! Some generous people even publish dissertation ideas and samples for free. Hence, you can develop your unique topic by looking at other people’s works.

Which Topic Suits Best for Dissertation?

Whether you search healthy lifestyle, economic crisis, or leadership dissertation topics, the strategy is the same for all of them. These topics for dissertation should meet the following requirements:

  • Bring novelty to the science field
  • Cover newsworthy issues
  • Have enough background data for an academic paper

Undeniably, it is better if the theme heavily appeals to you personally. Then, a sparkle of interest lights up whenever you write your work! On the contrary, less engaging dissertation topics make the whole writing process inefficient. Therefore, opt for themes that draw your attention the most.

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Enter the requirements for your work and get your task done asap.

Where to Find a Unique Dissertation Topic?

Throughout life, people constantly have to present something new to the world. Middle school and high-school students show their skills via essays, college students write a thesis, and Ph.D. candidates compose dissertations. Fortunately, emergency methods, like dissertation writing service , are available for quick and quality results. Still, you might suggest your topics for dissertation.

What is the key to creating a one-of-a-kind topic? First, you have to know well enough what other scholars have already studied. Then, perform further research even if your counterparts have covered all nuances. For instance, higher education dissertation topics can cover themes of college-age population or school bullying. Meanwhile, leadership dissertation topics may connect to ethical issues dealing within companies.

Dissertation Title: How to Make It Sound Perfect

In real life, titles are essential in drawing public attention to anything. Would you rather watch a movie with a boring name or pick a film with a short, witty title? The same goes for books, essays, and other scholarly work. The word becomes an anchor, something that pushes a random person to read your written piece. Here is how you properly compose it.

Let’s say that you ponder over higher education dissertation topics. For instance, do you want to study anxiety disorders among students or how online schools are affecting libraries? Raising awareness is crucial in both cases, but you must specify the issue first. For instance, attempt to study an unexpected correlation that current research fails to cover. Use the “how,” “what,” and “why” words to form several topic ideas.

Once you have specified your exact subject of study, your goal is to fit the title in under fifty words. This task seems unproblematic, but it requires talent. Just two sentences must sum up the contents of the humongous dissertation. So, make the title clear and concise!

What are Some Relevant Ideas to Research in 2023?

How long is a dissertation? It ranges from ten thousand to a hundred thousand words, but length is only the first requirement. Without a doubt, all topics for dissertation have one crucial characteristic: relevancy. To develop top-tier academic work, you need to know the global trends and latest tendencies in your specific science field. It would be detrimental to your success to pick dissertation ideas that scholars have recycled multiple times. So instead, look at what people find exciting in 2022:

Best Dissertation Topics

  • Artificial intelligence

Although the theme of AI has been around for a while, it remains fresh and full of potential. One possible research subject is the Metaverse, a virtual reality universe. This concept is quite new, so there are many branches to study. Besides, cybersecurity, especially in the banking sector, would stand out among the interesting examples of dissertation topics.

  • Neuroscience and neurobiology

As much as scientists study human brains, there are still too many white spots in their knowledge of the human body. Choosing a topic related to cognitive development, brain implants, etc., could lead to a breakthrough in this sphere.

  • Agriculture

With the negative trends in the global food industry, the theme of agriculture is at its peak importance. Food is something that everybody relates to, regardless of ethnicity, age, job, or social status. Therefore, a dissertation could critically analyze the current state of things and solutions for the food industry in crisis.

List of Dissertation Topics 2023

Today, you can do anything with the Internet, like pay someone to write an essay or find information on the necessary subject. Likewise, you may find business dissertation topics examples or dissertation topics in education, world politics, or other themes. This article suggests multiple ideas for your academic work to make things easier.

Top Dissertation Topics in Accounting

Here is a list of engaging dissertation topics in accounting:

  • “Financial accounting's contribution to business strategy development.”
  • “The things to take into account when investing in financial markets.”
  • “How project accounting uses risk factors analysis.”
  • “Systematic examination of art galleries cost accounting.”
  • “Can computerized bookkeeping gradually replace accountants?”
  • “The effect of cryptocurrency on current accounting procedures.”
  • “Predicting new professions in the accounting industry.”
  • “How are auditing standards becoming more international?”
  • “An examination of the differences and parallels between accounting ethics and organizational culture.”
  • “Investigation of potential new revenue streams for a bank.”

Best Public Health Dissertation Topics

In case you are looking for interesting public health dissertation topics, here are a few research questions:

  • “How is it possible to increase Middle Eastern countries' access to clean, safe drinking water?”
  • “What is the contribution of technological progress to bettering public health in affluent nations?”
  • “Examining sexual abuse in an Indian public health environment.”
  • “Evaluation of several US programs to increase kids' physical activity.”
  • “The impact of poverty on public health in African nations.”
  • “A study of the effectiveness of the Italian current healthcare system.”
  • “Disastrous effects of antibiotic resistance in the upcoming year.”
  • “Patient’s immune system and drug addiction.”
  • “How does modern technology harm public health?”
  • “Impact of the recession on social conditions and public health.”

Sociology Ideas for Dissertation

You should go online if interested in the social work dissertation topics. Articles like this share newsworthy sociology dissertation topics:

  • “An analysis of American religious institutions and their impact on social structure.”
  • “Examining attitudes toward and reactions to female child sex offenders.”
  • “Studying the cultural differences in Scandinavian countries.”
  • “Determining the social origins of domestic violence in Russian families.”
  • “Global labor market stratification following the Great Recession.”
  • “Research on how society influences gender relations.”
  • “Analysis of the rise and fall in Japan's fertility rates and their underlying causes.”
  • “The practice of social work with bereaved families.”
  • “Analyze the racial stratification in European nations.”
  • “How can government decrease the stress that social workers endure?”

Dissertation Topics in Education

Whether you want to discover new primary, college, or higher education dissertation topics, you are at the right place:

  • “Looking at the effect of financial restraints on female education in east Asia.”
  • “Investigating the effects of food sharing in primary education.”
  • “Analysis of the covid pandemic's impact on the education sector.”
  • “Do stress levels among students and performance on standardized tests correlate?”
  • “What difficulties do parents of Muslim immigrants believe their children will encounter in European schools?”
  • “What do teachers think about how technology affects students' learning?”
  • “What difficulties do teachers encounter throughout their first three years of teaching?”
  • “What do parents think the purpose of sex education is?”
  • “What learning differences exist between neurodivergent and neurotypical students?”
  • “How does the number of students in each class influence grades?”

Business Dissertation Topics

Someone who takes an interest in entrepreneurship would be glad to find the following business or mba dissertation topics:

  • “The modern challenges for startups and small businesses in the USA.”
  • “The impact of competence and leadership style on emerging business leaders in Europe.”
  • “Analyzing how social media and digital platforms will impact business branding in the future.”
  • “Do male subordinates' egos feel threatened by the presence of women in leadership positions?”
  • “Is Facebook right to create targeted adverts using the user data it collects?”
  • “Is a business's dispersed leadership more effective than its lone power center?”
  • “TikTok influencer marketing's contribution to higher sales.”
  • “An analysis of how globalization has affected Chinese companies' operations.”
  • “The socio-cultural context of management and how it affects the dynamics of leadership in Denmark.”
  • “What elements influence the probability of a business filing for bankruptcy?”

Political Science Dissertation Topics

Provided that your field of study is politics, consider the next dissertation topics:

  • “Contrasting the responses of the Chinese and UK governments to the COVID-19 pandemic.”
  • “Emotion's effect on deliberative democracy.”
  • “Analysis of the single-party political system, including drawbacks and advantages.”
  • “Political choices and environmental management tradeoffs.”
  • “Eastern European social movements in the years following World War II.”
  • “Ukraine's fragmentation and the competing political forces.”
  • “Media bias in the reporting of political news.”
  • “The impact of extremism on political life in the West.”
  • “Political leaders and their individual goals.”
  • “How does US foreign policy affect other nations throughout the world?”

Psychology Dissertation Topics

What if a person struggles to find extensive psychology dissertation topics? The solution is here:

  • “Examining the connection between technology and postnatal depression.”
  • “Why are some people more prone to feeling depressed in difficult situations?”
  • “The long-term effects of childhood trauma on adults.” 
  • “Patient's mental health during the coronavirus pandemic.”
  • “Children who are suffering from oncology: modern recovery programs.”
  • “Comparison of cyberbullying and physical bullying psychological impact.”
  • “What elements alter our personalities throughout our lives?”
  • “What are the key indicators of burnout among executive staff?”
  • “Effect of physical appearance on how others perceive us.”
  • “Teaching dyslexic kids: potential difficulties.”

PhD Dissertation Topics

A Ph.D. candidate might consider historical, mathematical, or art dissertation topics. So let’s pick a great research topic:

  • “US legal system and international criminal law: a comparative study.”
  • “Examination of how globalization leads to changes in international law.”
  • “The initial causes of cultural appropriation in first-world countries.”
  • “What is the social networks’ impact on online marketing and creating demand?”
  • “Cyber-diplomacy is the development of a global civilization in the digital era.”
  • “What differences exist between US and EU immigration laws?”
  • “Changing careers: information seeking by newcomers.” 
  • “The African-focused foreign policy of China.”
  • “How have feminists' objectives evolved over the last ten years?”
  • “Bringing the internet of things research and implementation together.”

Economics Dissertation Topics

Let’s see which dissertation topics in finance and economics can draw attention today:

  • “Evaluating the cryptocurrency market using behavioral finance perspectives.”
  • “Comparative analysis of financial improvements in China and the US.”
  • “Issues with older adults and online banking.”
  • “Shareholders' effects on the decision-making procedures at banks.”
  • “Unscrupulous bank executives' effects on the organization's sustainability.”
  • “Possible answers to moral problems of corporate social responsibility.”
  • “What impact do taxes have on financial choices?”
  • “The impact of India's population growth on economic expansion.”
  • “Why are banks so adamantly against digital currency?”
  • “What will internet banking resemble in ten years?”

Fashion Topics for Dissertation

An artsy person would appreciate research themes about style, like the following examples:

  • “Is there a need for change after examining the impact of fast fashion on the environment?”
  • “Comparing fast and ultra-fast supply chain management in the fashion industry.”
  • “Critical analysis of the impact of western fashion on Asia's developing nations.”
  • “How capitalism contributed to the western fashion and cultural values.”
  • “Fashion trends that the K-Pop stars create.”
  • “Examining the Vivienne Westwood brand's appeal to Japanese youth.”
  • “The fixation with attempting an adult look in children's clothing.”
  • “The effects of expensive counterfeit goods on the high-end fashion market.”
  • “The origins of the dark and light academic dress trends.”
  • “How social networks contribute to the development and spread of fashion trends.”

In brief, there are plenty of research subjects, from psychology dissertation topics to higher education dissertation topics. If you do proper factual and historical research and cite sources, get ready to receive recognition for your efforts. The key thing is to choose something that lights up your interest.

Also, don't forget to read what is important to look out for when you buy dissertation .

Set Your Dissertation Apart with Unique Topics

Elevate your academic journey with a standout dissertation topic. Our experts are here to help you select a topic that not only intrigues but also contributes significantly to your field of study.

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Don't miss our Spring 2024 Funding Forecast

Spring Quarter usually marks the end of the academic year, but finding funding is a continuous process! Check out this sample of upcoming deadlines of funding opportunities for postdoctoral, doctoral, graduate, research, and other short-term awards or travel grants. Various deadlines listed. Consult websites for current details and application information.

Funding Forecast

Spring quarter usually marks the end of the academic year, but finding funding is a continuous process! So, if you are looking for financial support for the coming year or next, remember to routinely look at funding postings so you get an idea of what topics or issues are getting funded. Spring and summer are also great times to prepare your fellowship application materials - personal statement, research statement, and academic CV.

Below is a sample list of upcoming deadlines. Regularly inform your faculty adviser about your current research ideas and progress as this is very important when requesting letters of recommendation. Also, be sure to check the program websites regularly for the most updated information on important dates and submission details. Good luck!

NOTE: Please report any broken links to Funding Peer Liliana Garcia

Jump to information about: Postdoctoral Fellowships Dissertation Support Graduate and Doctoral Support Research Support Other (Travel, Short-Term, Award, Summer, etc.)  

POSTDOCTORAL FELLOWSHIPS

Mar 15  The Hindle Postdoctoral Fellowship (history of technology)

Apr 1 German Historical Institute Doctoral and Postdoctoral Fellowships

Apr 1 SHOT- NASA Postdoctoral Fellowship (history of space technology)

Apr 1 Postdoctoral Fellowship in Aerospace History

Apr 1 American Cancer Society Postdoctoral Fellowships

Jul 15 David B. Larson Postdoctoral Fellowship in Health and Spirituality

Sep 15 Fulbright Postdoctoral Fellowships in Israel for U.S. Citizens 2020/2021

Sep TBD American Heart Association Postdoctoral Fellowships

Oct 1 National Institute on Drug Abuse (NIDA) International Program INVEST Drug Abuse Postdoctoral Research Fellowship

Oct 15 American Cancer Society Postdoctoral Fellowships

Oct 18 NSF Mathematical Sciences Postdoctoral Research Fellowships

On-going Incorporating Benefits & Costs of Environmental Regulation in Computable General Equilibrium Models Research with the US Environmental Protection Agency

Various deadlines Funding Opportunities for Postdoctoral Scholars - list via Harvard website

Various deadlines Postdoctoral opportunities in medical research - via Stanford website

Various deadlines Minority Postdoctoral Opportunities List

Various deadlines Oak Ridge Institute for Science and Education (ORISE) Postdoctoral Fellowships

Various deadlines Special Programs for Postdoctoral Fellows - via National Science Foundation

Various deadlines Post-doctoral Opportunities List - from the National Institute of Health

Various deadlines - Postdoctoral Positions at the Lawrence Livermore National Laboratory  

DISSERTATION SUPPORT

Feb 25  Melvin Kranzberg Dissertation Fellowship (history of technology)

April 1 Society for Historians of American Foreign Relations Marilyn Blatt Young Dissertation Completion Fellowship

Apr 1 Association for Slavic, East European, and Eurasian Studies (ASEEES) Dissertation Research Grants

May 1 North American Conference on British Studies Dissertation Research Fellowship

May 1 Grants for Health Services Dissertation Program (R36)

Jul 17 Linguistics Program Doctoral Dissertation Research Improvement - grant application must be submitted with your advisor and through Office of Research

Jul 20 Biological Anthropology Program Doctoral Dissertation Research Improvement - grant application must be submitted with your advisor and through Office of Research

Aug 1 Grants for Health Services Dissertation Program (R36)

Aug 15 Cultural Anthropology Program Doctoral Dissertation Research Improvement - grant application must be submitted with your advisor and through Office of Research

On-going Research Opportunities at the US Forest Service Research and Development (R&D)

On-going Archaeology Program Doctoral Dissertation Research Improvement Awards (Arch-DDRI) - grant application must be submitted with your advisor and through Office of Research

On-going Documenting Endangered Languages Doctoral Dissertation Research Improvement Grants - grant application must be submitted with your advisor and through Office of Research

On-going Geography and Spatial Sciences Program Doctoral Dissertation Research Improvement Grants (GSS-DDRI) , National Science Foundation (NSF)

Various Deadlines Oak Ridge Institute for Science and Education (ORISE) Research Opportunities  

GRADUATE & DOCTORAL SUPPORT

Apr 1 Batten, First Union, and Peter Nicolaisen International Fellowships

Apr 1 SHOT- NASA Predoctoral Fellowship (history of space technology)

Apr 10  National Endowment for the Humanities (NEH) Fellowships

Apr 15 Phi Kappa Phi Honor Society Graduate Fellowship (National Deadline; local chapter deadline is usually 2 weeks earlier)

Apr 15 BHW Group Women in STEM Scholarship

Apr 30 Government of the Slovak Republic approved the establishment of the National Scholarship Programme

May 8  Google India PhD Fellowships

May 8  Google China/Hong Kong/Japan/South Korea Phd Fellowship Program

May 11 American Speech-Language-Hearing Foundation (ASHFoundation) New Century Scholars Doctoral Scholarship

Jun 15  American Institute of Certified Public Accountants (AICPA) Fellowship for Minority Doctoral Students

Sep 7 American Heart Association Predoctoral Fellowships

TBD American Speech-Language-Hearing Foundation (ASHFoundation) Graduate Student Scholarship

TBD PEO International Peace Scholarship (IPS) - also open to international students studying in the US

Various Deadlines Society for Historians of American Foreign Relations Fellowships and Grants  

On-going Gerda Henkel Foundation Ph.D. Scholarships in the Historical Humanities   

RESEARCH SUPPORT

Apr 1 Research Fellowships in Aerospace History

Apr 1 Harry S. Truman Library Institute Research Grants Program Apr 10  National Endowment for the Humanities Fellowships Apr 12 Horton Hydrology Research Grant from American Geophysical Union

Apr 13 Project Management Institute's Research Grant Program for the study of project, program or portfolio management

Apr 15 Emerging Crises Oral History Research Fund

Apr 19 American Speech-Language-Hearing Foundation Student Research Grant in Early Childhood Language Development

Apr 19 American Speech-Language-Hearing Foundation Student Research Grant in Audiology

Apr 24  Japan-US Friendship Commission and the National Endowment for the Humanities Fellowships for Advanced Social Science Research on Japan

Apr 30 International Foundation for Ethical Research (IFER) - Graduate Fellowship Program

Apr TBD Dwight David Eisenhower Transportation Fellowship Program

May 1 NRC Research Associateship Programs (RAP)

May 1  US Department of Energy (DOE) Office of Science (SC) Graduate Student Research Program

May 2 National Institute of Justice Graduate Fellowships in STEM

May 15 Deutsches Akademisches Austaauschdienst (DAAD) Short-Term Research Grants (for research in Germany)

Jul 15 The Leakey Foundation Grants for Research Related to Human Origins

Aug 1 NRC Research Associateship Programs (RAP)

Sep 15 Fulbright Canada-American Scholars Awards

Sep 15 Kluge Fellowships (humanities and social science research)

Oct 15  Harry S. Truman Library Institute Research Grants Program

TBD UCHRI Grants and Fellowships

TBD Graduate Fellowship for Research in Japan

TBD Merck KGaA Research Grant Competition

Various Opportunities New York Public Library Research Fellowships

Various Deadlines Smithsonian Institute Fellowships

Various Deadlines Metropolitan Museum of Art Research Fellowships

Various Deadlines Center for Disease Control (CDC) Fellowships

On-going Dirksen Congressional Research Grant

On-going The Spalding Trust Grants for the Comparative Study of Religions

On-going Statistics Fellowship with the Center for Disease Control and Prevention (CDC)

On-going OCS ORISE Fellowship with the Food and Drug Administration

On-going Digital/New Media Fellowships with Dept of Health and Human Services

On-going Dept of Energy Opportunity in Fuel Cell Research

On-going National Institute of Health Individual Graduate Partnerships Program

On-going Title VIII Research Scholar Program American Councils - in-country, independent research for three consecutive months to nine consecutive months in Russia, Eurasia, and Eastern Europe  

OTHER (Travel, Short-Term, Award, Summer etc.)

Mar 31 Sara Finney-Johnson Scholarship - Delta Sigma Theta Sorority

Apr 1 Digital Archaeological Archive of Comparative Slavery

Apr 7 Short-Term Carter Center Graduate Assistantships in Atlanta

Apr 8 Charles Koch Institute Summer Internship

Apr 10  National Endowment for the Arts Fellowships

Apr 28 Mary Murphy Graduate Scholarship - Delta Sigma Theta Sorority

Apr TBD Interfaces Graduate Training Program at UCSD - in biological, engineering, physical and health sciences

Apr TBD Lupus Foundation of America Summer Fellowships

May 1  Academy Nicholl Fellowships in Screenwriting (no citizenship requirements)

May 1 James P. Danky Fellowship in Print and Digital Culture

May 15 Catherine Prelinger Award (women's history)

May 31 PSA/Journal of Postcolonial Writing Postgraduate Essay Competition

Jun 5  SACNAS Travel Fellowships

Jun 26  LGBT Studies One-Month Research Fellowship at Yale University

July TBA  National Air and Space Administration (NASA) Internships *NOTE: Select opportunities are also open to citizens from countries participating in the NASA International Internship Program.

Sep 1 Samuel H. Kress Foundation Conservation Grants Programs

Sep 1 Samuel H. Kress Foundation Art History Digital Art History Grant Programs

Fall TBD Presidential Management Fellows Program US Office of Personnel Management

Rolling Deadline - Veteran Research Supplement with the Center for Integrated Access Networks

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  1. What Is a Dissertation?

    A dissertation is a long-form piece of academic writing based on original research conducted by you. It is usually submitted as the final step in order to finish a PhD program. Your dissertation is probably the longest piece of writing you've ever completed. It requires solid research, writing, and analysis skills, and it can be intimidating ...

  2. What (Exactly) Is A Dissertation Or Thesis?

    A dissertation (or thesis) is a process. Okay, so now that you understand that a dissertation is a research project (which is testing your ability to undertake quality research), let's go a little deeper into what that means in practical terms. The best way to understand a dissertation is to view it as a process - more specifically a ...

  3. Guide to Writing Your Thesis/Dissertation : Graduate School

    Definition of Dissertation and Thesis. The dissertation or thesis is a scholarly treatise that substantiates a specific point of view as a result of original research that is conducted by students during their graduate study. At Cornell, the thesis is a requirement for the receipt of the M.A. and M.S. degrees and some professional master's ...

  4. What Is a Dissertation?

    Revised on 5 May 2022. A dissertation is a large research project undertaken at the end of a degree. It involves in-depth consideration of a problem or question chosen by the student. It is usually the largest (and final) piece of written work produced during a degree. The length and structure of a dissertation vary widely depending on the ...

  5. What is a Dissertation? Everything You Need to Know

    A dissertation is designed to be your own. Meaning that what you write about should be a new idea, a new topic, or question that is still unanswered in your field. Something that you will need to collect new data on, potentially interview people for and explore what information is already available. Generally, an idea will need to be approved ...

  6. What Is a Thesis?

    A thesis is a long-form piece of academic writing, often taking more than a full semester to complete. It is generally a degree requirement for Master's programs, and is also sometimes required to complete a bachelor's degree in liberal arts colleges. ... Consider using a professional thesis editing service or grammar checker to make sure ...

  7. Dissertation Explained: A Grad Student's Guide

    A dissertation also signifies the completion of your PhD program. It is required to earn a PhD degree, which stands for Doctor of Philosophy. A PhD is created from knowledge acquired from: 1. Coursework: A PhD program consists of academic courses that are usually small in size and challenging in content.

  8. How to Write a Dissertation or Thesis Proposal

    Writing a proposal or prospectus can be a challenge, but we've compiled some examples for you to get your started. Example #1: "Geographic Representations of the Planet Mars, 1867-1907" by Maria Lane. Example #2: "Individuals and the State in Late Bronze Age Greece: Messenian Perspectives on Mycenaean Society" by Dimitri Nakassis.

  9. Dissertation Structure & Layout 101 (+ Examples)

    Time to recap…. And there you have it - the traditional dissertation structure and layout, from A-Z. To recap, the core structure for a dissertation or thesis is (typically) as follows: Title page. Acknowledgments page. Abstract (or executive summary) Table of contents, list of figures and tables.

  10. How to Write a Dissertation

    A dissertation or thesis is a long piece of academic writing based on original research, submitted as part of an undergraduate or postgraduate degree. The structure of a dissertation depends on your field, but it is usually divided into at least four or five chapters (including an introduction and conclusion chapter).

  11. Thesis vs. Dissertation: What's the difference?

    Review: Dissertation reviews are typically more rigorous, often involving external reviewers, while thesis reviews are usually internal. Defense: A dissertation defense is generally more intense and formal, as it often involves a presentation to the wider academic community, while a thesis defense might be more confined and informal.

  12. What is the difference between a dissertation and a thesis?

    The words ' dissertation ' and 'thesis' both refer to a large written research project undertaken to complete a degree, but they are used differently depending on the country: In the UK, you write a dissertation at the end of a bachelor's or master's degree, and you write a thesis to complete a PhD. In the US, it's the other way ...

  13. Dissertation vs Thesis: Understanding the Key Differences

    Lastly, one of the main differences between a dissertation and a thesis is the potential for publication. As the dissertation is more extensive and requires original research contributing to the academic field, theses are less likely to be published in a peer-reviewed journal. Although a master's thesis is more narrowly focused, it can still ...

  14. Thesis and Dissertation: Getting Started

    The resources in this section are designed to provide guidance for the first steps of the thesis or dissertation writing process. They offer tools to support the planning and managing of your project, including writing out your weekly schedule, outlining your goals, and organzing the various working elements of your project.

  15. Dissertation vs Thesis: Your 2024 Guide

    Much like a thesis, dissertations are also academic papers that aim to prove a student's expertise - while adding to the current body of knowledge - in their field. ... Chriselle has been a passionate professional content writer for over 10 years. She writes educational content for The Grad Cafe, Productivity Spot, The College Monk, and ...

  16. Thesis

    A thesis ( pl.: theses ), or dissertation [note 1] (abbreviated diss. ), [2] is a document submitted in support of candidature for an academic degree or professional qualification presenting the author's research and findings. [3]

  17. What Is the Difference Between a Doctoral Study and a Dissertation

    A PhD is an academic degree focused on original research, data analysis, and the evaluation of theory. The result of that research is a dissertation. People who earn a PhD often pursue careers in research, academia, and leadership. A PhD is also called an academic doctoral degree or a terminal degree. What Is a Dissertation in a PhD Program?

  18. Dissertation Vs Thesis: How Are They Different

    What Is A Dissertation. A dissertation is a substantial piece of academic writing typically required to complete a doctoral degree (such as a Ph.D.). It represents an original and significant contribution to the field of study and is usually the culmination of several years of research and study.

  19. What Is Academic Writing?

    Academic writing is a formal style of writing used in universities and scholarly publications. You'll encounter it in journal articles and books on academic topics, and you'll be expected to write your essays, research papers, and dissertation in academic style. Academic writing follows the same writing process as other types of texts, but ...

  20. 150+ Dissertation Topics That Are Relevant In 2024

    Here are ten good topics for a dissertation. The Role of Technology in Enhancing Learning Outcomes in K-12 Education. Evaluating the Impact of Montessori Methods on Early Childhood Education. The Effectiveness of Bilingual Education in Improving Students' Linguistic Competence.

  21. Top 100 Dissertation Topics

    Here is a list of engaging dissertation topics in accounting: "Financial accounting's contribution to business strategy development.". "The things to take into account when investing in financial markets.". "How project accounting uses risk factors analysis.". "Systematic examination of art galleries cost accounting.".

  22. (PDF) Teachers as Builders: Professional Development and ...

    Teachers as Builders: Professional Development and Community Participation of Public School Teachers in Metro Manila, Philippines (Dissertation) August 2022 DOI: 10.13140/RG.2.2.14617.29286

  23. Don't miss our Spring 2024 Funding Forecast

    Various deadlines listed. Consult websites for current details and application information. By Liliana Garcia, Funding Peer. Tuesday, April 9th, 2024 - 9:48am. Funding Forecast. Spring quarter usually marks the end of the academic year, but finding funding is a continuous process! So, if you are looking for financial support for the coming year ...

  24. Geosciences Dissertation Defense

    Geosciences Dissertation Defense - Haven Cashwell. Time: Apr 15, 2024 (11:30 AM) Location: ACLC 259A. Details: "Usability, Undergraduates, Understanding: Enhancing Climate Resiliency and Climate Literacy through Co-Production". Dissertation Defense by Haven Cashwell.

  25. Geosciences Thesis Defense

    Geosciences Thesis Defense - Ansleigh Bright. Time: Apr 15, 2024 (02:30 PM) Location: Zoom. Details: "Does Access Imply Usability? Evaluating Social and Physical Barriers to Park Access and Usability within Atlanta, Georgia".