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dissertation

Definition of dissertation

Examples of dissertation in a sentence.

These examples are programmatically compiled from various online sources to illustrate current usage of the word 'dissertation.' Any opinions expressed in the examples do not represent those of Merriam-Webster or its editors. Send us feedback about these examples.

Word History

1651, in the meaning defined above

Dictionary Entries Near dissertation

dissertative

Cite this Entry

“Dissertation.” Merriam-Webster.com Dictionary , Merriam-Webster, https://www.merriam-webster.com/dictionary/dissertation. Accessed 9 Jun. 2024.

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Kids definition of dissertation, more from merriam-webster on dissertation.

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What is a Dissertation? Everything You Need to Know 

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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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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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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• Knowledge Base
• Dissertation

How to Write a Dissertation | A Guide to Structure & Content

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).

The most common dissertation structure in the sciences and social sciences includes:

• An introduction to your topic
• A literature review that surveys relevant sources
• An explanation of your methodology
• An overview of the results of your research
• A discussion of the results and their implications
• A conclusion that shows what your research has contributed

Dissertations in the humanities are often structured more like a long essay , building an argument by analysing primary and secondary sources . Instead of the standard structure outlined here, you might organise your chapters around different themes or case studies.

Other important elements of the dissertation include the title page , abstract , and reference list . If in doubt about how your dissertation should be structured, always check your department’s guidelines and consult with your supervisor.

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Table of contents

Acknowledgements, table of contents, list of figures and tables, list of abbreviations, introduction, literature review / theoretical framework, methodology, reference list.

The very first page of your document contains your dissertation’s title, your name, department, institution, degree program, and submission date. Sometimes it also includes your student number, your supervisor’s name, and the university’s logo. Many programs have strict requirements for formatting the dissertation title page .

The title page is often used as cover when printing and binding your dissertation .

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The acknowledgements section is usually optional, and gives space for you to thank everyone who helped you in writing your dissertation. This might include your supervisors, participants in your research, and friends or family who supported you.

The abstract is a short summary of your dissertation, usually about 150-300 words long. You should write it at the very end, when you’ve completed the rest of the dissertation. In the abstract, make sure to:

• State the main topic and aims of your research
• Describe the methods you used
• Summarise the main results
• State your conclusions

Although the abstract is very short, it’s the first part (and sometimes the only part) of your dissertation that people will read, so it’s important that you get it right. If you’re struggling to write a strong abstract, read our guide on how to write an abstract .

In the table of contents, list all of your chapters and subheadings and their page numbers. The dissertation contents page gives the reader an overview of your structure and helps easily navigate the document.

All parts of your dissertation should be included in the table of contents, including the appendices. You can generate a table of contents automatically in Word.

If you have used a lot of tables and figures in your dissertation, you should itemise them in a numbered list . You can automatically generate this list using the Insert Caption feature in Word.

If you have used a lot of abbreviations in your dissertation, you can include them in an alphabetised list of abbreviations so that the reader can easily look up their meanings.

If you have used a lot of highly specialised terms that will not be familiar to your reader, it might be a good idea to include a glossary . List the terms alphabetically and explain each term with a brief description or definition.

In the introduction, you set up your dissertation’s topic, purpose, and relevance, and tell the reader what to expect in the rest of the dissertation. The introduction should:

• Establish your research topic , giving necessary background information to contextualise your work
• Narrow down the focus and define the scope of the research
• Discuss the state of existing research on the topic, showing your work’s relevance to a broader problem or debate
• Clearly state your objectives and research questions , and indicate how you will answer them
• Give an overview of your dissertation’s structure

Everything in the introduction should be clear, engaging, and relevant to your research. By the end, the reader should understand the what , why and how of your research. Not sure how? Read our guide on how to write a dissertation introduction .

Before you start on your research, you should have conducted a literature review to gain a thorough understanding of the academic work that already exists on your topic. This means:

• Collecting sources (e.g. books and journal articles) and selecting the most relevant ones
• Critically evaluating and analysing each source
• Drawing connections between them (e.g. themes, patterns, conflicts, gaps) to make an overall point

In the dissertation literature review chapter or section, you shouldn’t just summarise existing studies, but develop a coherent structure and argument that leads to a clear basis or justification for your own research. For example, it might aim to show how your research:

• Addresses a gap in the literature
• Takes a new theoretical or methodological approach to the topic
• Proposes a solution to an unresolved problem
• Advances a theoretical debate
• Builds on and strengthens existing knowledge with new data

The literature review often becomes the basis for a theoretical framework , in which you define and analyse the key theories, concepts and models that frame your research. In this section you can answer descriptive research questions about the relationship between concepts or variables.

The methodology chapter or section describes how you conducted your research, allowing your reader to assess its validity. You should generally include:

• The overall approach and type of research (e.g. qualitative, quantitative, experimental, ethnographic)
• Your methods of collecting data (e.g. interviews, surveys, archives)
• Details of where, when, and with whom the research took place
• Your methods of analysing data (e.g. statistical analysis, discourse analysis)
• Tools and materials you used (e.g. computer programs, lab equipment)
• A discussion of any obstacles you faced in conducting the research and how you overcame them
• An evaluation or justification of your methods

Your aim in the methodology is to accurately report what you did, as well as convincing the reader that this was the best approach to answering your research questions or objectives.

Next, you report the results of your research . You can structure this section around sub-questions, hypotheses, or topics. Only report results that are relevant to your objectives and research questions. In some disciplines, the results section is strictly separated from the discussion, while in others the two are combined.

For example, for qualitative methods like in-depth interviews, the presentation of the data will often be woven together with discussion and analysis, while in quantitative and experimental research, the results should be presented separately before you discuss their meaning. If you’re unsure, consult with your supervisor and look at sample dissertations to find out the best structure for your research.

In the results section it can often be helpful to include tables, graphs and charts. Think carefully about how best to present your data, and don’t include tables or figures that just repeat what you have written  –  they should provide extra information or usefully visualise the results in a way that adds value to your text.

Full versions of your data (such as interview transcripts) can be included as an appendix .

The discussion  is where you explore the meaning and implications of your results in relation to your research questions. Here you should interpret the results in detail, discussing whether they met your expectations and how well they fit with the framework that you built in earlier chapters. If any of the results were unexpected, offer explanations for why this might be. It’s a good idea to consider alternative interpretations of your data and discuss any limitations that might have influenced the results.

The discussion should reference other scholarly work to show how your results fit with existing knowledge. You can also make recommendations for future research or practical action.

The dissertation conclusion should concisely answer the main research question, leaving the reader with a clear understanding of your central argument. Wrap up your dissertation with a final reflection on what you did and how you did it. The conclusion often also includes recommendations for research or practice.

In this section, it’s important to show how your findings contribute to knowledge in the field and why your research matters. What have you added to what was already known?

You must include full details of all sources that you have cited in a reference list (sometimes also called a works cited list or bibliography). It’s important to follow a consistent reference style . Each style has strict and specific requirements for how to format your sources in the reference list.

The most common styles used in UK universities are Harvard referencing and Vancouver referencing . Your department will often specify which referencing style you should use – for example, psychology students tend to use APA style , humanities students often use MHRA , and law students always use OSCOLA . M ake sure to check the requirements, and ask your supervisor if you’re unsure.

To save time creating the reference list and make sure your citations are correctly and consistently formatted, you can use our free APA Citation Generator .

Your dissertation itself should contain only essential information that directly contributes to answering your research question. Documents you have used that do not fit into the main body of your dissertation (such as interview transcripts, survey questions or tables with full figures) can be added as appendices .

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What is a dissertation?

Sabrina Collier

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Table of contents

• Introduction

What are the two types of dissertations?

Skills you need to show, how long is a dissertation, oral examinations (vivas), don’t cheat.

The majority of degrees end with this assignment, but just what is a dissertation?  

Sometimes known as a thesis (in some countries, this term is used only for the final assignments of PhD degrees, while in other countries ‘thesis’ and ‘dissertation’ are interchangeable), a dissertation is a research project completed as part of an undergraduate or postgraduate degree. Typically, a dissertation allows students present their findings in response to a question or proposition that they choose themselves. The aim of the project is to test the independent research skills students have acquired during their time at university, with the assessment used to help determine their final grade. Although there is usually some guidance from your tutors, the dissertation project is largely independent.

For most students this will be the longest, most difficult and most important assignment completed at university, requiring months of preparation and hard work (the library might become a second home). However, it can also be very rewarding, particularly if you’re passionate about your choice of topic. It’s therefore definitely a good idea to make sure you choose a subject you’re genuinely interested in.

The type of dissertation you complete will vary depending on your course of study. One of the main differences is between empirical and non-empirical dissertations.

Empirical dissertation s are dissertations which involve collecting data, for example in a psychology degree. This may mean putting into practice professional and ethical guidelines when collecting data from members of the public. Empirical dissertations in natural and life science subjects may involve or be entirely centered on laboratory work.

Non-empirical dissertations are based on existing data and arguments in the work of others. This is likely to mean spending a lot of time with your head in a book! In this type of dissertation, you need to make sure you don’t just describe what others are saying, but critically analyze the work and explore its practical applications.

No matter what type of dissertation you write, and what topic you choose, you’ll need to demonstrate the following skills:

• Defining and outlining a research area with a clear question
• Identifying the leading issues
• Sourcing the relevant information
• Assessing its reliability and legitimacy
• Evaluating the evidence on all sides of a debate
• Coming to a well-argued conclusion
• Organizing and presenting the outcomes of your work critically, convincingly, and articulately, following all the guidelines on how to format your essay

The length of a dissertation varies between study level and country, but is generally around 10,000-12,000 words at undergraduate level, 15,000-25,000 words at master’s level and up to 50,000 words or more at PhD level.

For some advanced degrees (particularly PhDs) you may need to attend an oral examination, which is known as a viva in some countries (short for viva voce, which is Latin for ‘live voice’). The viva will usually start with you giving a short presentation of your work to two or three professors, which is then followed by a questioning/answering period which could last up to two hours.  

Finally, it pretty much goes without saying, but it’s definitely not advisable to pay someone to write your dissertation for you or otherwise cheat in any way. It’s not worth the risk, and the dissertation is meant to be your chance to let your skills shine through. However, asking a supervisor, friend or family member to take a look at your dissertation is fine. Your supervisor is on hand to guide you, so don’t worry if you need to ask for help.

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The former Assistant Editor of TopUniversities.com, Sabrina wrote and edited articles to guide students from around the world on a wide range of topics. She has a bachelor's degree in English Literature and Creative Writing from Aberystwyth University and grew up in Staffordshire, UK. 

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dissertation

[ dis-er- tey -sh uh n ]

• a written essay, treatise, or thesis, especially one written by a candidate for the degree of Doctor of Philosophy.
• any formal discourse in speech or writing.

/ ˌdɪsəˈteɪʃən /

• a written thesis, often based on original research, usually required for a higher degree
• a formal discourse

Discover More

Derived forms.

• ˌdisserˈtational , adjective
• ˌdisserˈtationist , noun

Other Words From

• disser·tation·al adjective
• disser·tation·ist noun

Word History and Origins

Origin of dissertation 1

Example Sentences

Thirteen years ago, while working on her PHD dissertation in Madagascar’s Masoala Peninsula, Borgerson encountered a problem.

At Harvard, he received a PhD in government and wrote his dissertation under Henry Kissinger, who became a lifelong friend.

I planned to go back to physics after a couple of years and then return to wrap up my dissertation.

My buba’s lived experience helped shape me into the girl who wrote her college dissertation on the gender pay gap, arguing for equal parental leave for dads and moms, almost 20 years before any major employer implemented any such thing.

My PhD dissertation was a highly theoretical model representing computer systems that were framed as a mathematical model, and if they were interconnected in such a way that these interconnected computers would communicate like cells in the body.

A terrific cultural studies dissertation awaits on how the fortunes of the Cheneys provide a mirror on a changing America.

Today, he visits online forums and bombards them with dissertation-length comments.

In her dissertation, McFate had asked whether ‘good anthropology’ might lead to ‘better killing.’

Heritage has distanced itself from Richwine and his dissertation.

No single dissertation will alter the status quo on its own.

I've never had time to write home about it, for I felt that it required a dissertation in itself to do it justice.

Dr. Pitcairn, published at Leyden his dissertation on the circulation of the blood through the veins.

Start not, reader, I am not going to trouble you with a poetical dissertation; no, no!

Dissertation sur les Assassins, Académie des Inscriptions, tom.

This dissertation, which is illustrated by several plates, will repay for the time spent in reading it.

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Tips for Online Students , Tips for Students

Dissertation Explained: A Grad Student’s Guide

Updated: August 7, 2023

Published: March 10, 2020

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.

Related Articles

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 .

*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.

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).

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 .

Need a helping hand?

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.

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).

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 .

Psst... there’s more!

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

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36 Comments

many thanks i found it very useful

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

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!

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

Thanks so much this helped me a lot!

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

Thanks Ade!

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

You’re welcome!

Hi! How many words maximum should contain the abstract?

Thank you so much 😊 Find this at the right moment

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

best ever benefit i got on right time thank you

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.

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

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

Thanks ! so concise and valuable

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

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

Really useful to me. Thanks a thousand times

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

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

Usefull, thanks a lot. Really clear

Very nice and easy to understand. Thank you .

That was incredibly useful. Thanks Grad Coach Crew!

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!

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 🙂

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

Great video; I appreciate that helpful information

It is so necessary or avital course

This blog is very informative for my research. Thank you

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

wow this is an amazing gain in my life

This is so good

How can i arrange my specific objectives in my dissertation?

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Definition of dissertation noun from the Oxford Advanced Learner's Dictionary

• dissertation
• He wrote his Master's dissertation on rats.
• Students can either do a dissertation or take part in a practical project.
• hall of residence
• Candidates are required to present a dissertation of between 8 000 and 12 000 words.
• She is writing her dissertation on the history of the Knights Templar.
• dissertation on

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Meaning of dissertation in English

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• boilerplate
• composition
• corresponding author
• essay question
• peer review

dissertation | Intermediate English

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• Capella University Blog
• PhD/Doctorate

What is a dissertation?

October 31, 2019

A dissertation is a written document that summarizes research.

It is the final step of a PhD program, and the culmination of a student’s doctoral studies.

“The dissertation is a source of pride for doctoral students,” Dinah Manns, PhD, faculty chair at Capella University, says. “The dissertation is often a compilation of academic and practical knowledge, and in many cases, it can be the student’s first publication.”

Here, Manns explains the content and format of this important piece of scholarship.

From student to scholar

The major objective of any doctoral program is to assist a student in becoming an independent researcher, and a dissertation is a large part of that. “Not all doctoral programs require a dissertation, but all PhD programs do,” Manns notes. “Dissertation work varies by program.”

Initial coursework helps narrow down the research topic and develop it into something that will add to the body of knowledge in the chosen field. Sometimes the research contributes something entirely new to the field, and other times it expands or deepens previous studies.

By the time the doctoral coursework is finished, the topic should be selected and ready for formal research. At this point the student develops a proposal, which encompasses the research plan and methodology as it pertains to the selected topic.

At Capella, once the proposal has been approved by the student’s mentor, committee, and the Institutional Review Board (IRB), the research and analysis begin. The dissertation is largely an independent project that essentially turns the student into a scholar; they’ll dive more deeply into research and writing then they have done before.

“Capella PhD candidates will be prepared for this step through their coursework and residency,” says Manns, noting that they will have learned how to approach this critical phase as part of their pre-dissertation learning.

Format of the dissertation

The dissertation is a much deeper exploration of a research topic than a traditional essay would be. It’s in the form of a book, with at least five chapters (some universities require a sixth chapter in the form of a recap of the previous chapters). Manns outlines the chapters this way:

• Overview. This is a brief look at the research question, containing a preview of the subsequent chapters.
• Literature review. The literature review is an extensive critique and synthesis of the current literature in the field.
• Methodology. This section contains details of the procedures and methods used to collect and analyze data.
• Analysis. The PhD candidate details how the data analysis applies to the collected data.
• Findings. This section provides interpretation of the data and comparison to existing literature, as well as future research possibilities.

The order of the chapters follows a logical progression in which PhD candidates build on their theories and explain research choices in detail before coming to the final chapter that gives weight to the value of the study itself.

Manns recommends that pre-dissertation students review completed dissertations in the field and research various types of methodology and design in the field as well. “That will help give them a feel for the depth of research and discussion, and see how the chapters work together,” Manns explains. “And remember—someday, it may be your dissertation being read!”

Capella University offers PhD and professional doctoral degrees in programs ranging from business to education and health to technology. Learn more about Capella’s doctoral programs.

You may also like

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December 11, 2019

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November 25, 2019

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Dissertation, /ˈdɪsərˌteɪʃən/, /dɪsəˈteɪʃən/.

Other forms: dissertations

A dissertation is a long piece of writing that uses research to bring to light an original idea. Don't go to grad school unless you're prepared to write, say, a 300-page dissertation on some topic.

In everyday speech, we sometimes accuse people of delivering dissertations when they overload us with dull information. If you're annoyed with a long memo from your office manager about keeping the kitchen clean, you could mutter to a coworker, “How’d you like that dissertation Felix posted about rinsing out our mugs?”

• noun a treatise advancing a new point of view resulting from research; usually a requirement for an advanced academic degree synonyms: thesis see more see less type of: tractate , treatise a formal exposition

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Find lists of SAT words organized by every letter of the alphabet here: A , B , C , D , E , F , G , H , I , J, K & L , M , N , O , P , Q , R , S , T , U , V , and W, X, Y & Z .

Set in Afghanistan during a time of political and social upheaval, this novel traces the decades-long friendship of two boys from different social classes.

A group of extraordinarily talented African-American women help NASA achieve some of its greatest successes, even as they face discrimination and oppression.

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Methodology

• How to Write a Literature Review | Guide, Examples, & Templates

How to Write a Literature Review | Guide, Examples, & Templates

Published on January 2, 2023 by Shona McCombes . Revised on September 11, 2023.

What is a literature review? A literature review is a survey of scholarly sources on a specific topic. It provides an overview of current knowledge, allowing you to identify relevant theories, methods, and gaps in the existing research that you can later apply to your paper, thesis, or dissertation topic .

There are five key steps to writing a literature review:

• Search for relevant literature
• Evaluate sources
• Identify themes, debates, and gaps
• Outline the structure
• Write your literature review

A good literature review doesn’t just summarize sources—it analyzes, synthesizes , and critically evaluates to give a clear picture of the state of knowledge on the subject.

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Table of contents

What is the purpose of a literature review, examples of literature reviews, step 1 – search for relevant literature, step 2 – evaluate and select sources, step 3 – identify themes, debates, and gaps, step 4 – outline your literature review’s structure, step 5 – write your literature review, free lecture slides, other interesting articles, frequently asked questions, introduction.

• Quick Run-through
• Step 1 & 2

When you write a thesis , dissertation , or research paper , you will likely have to conduct a literature review to situate your research within existing knowledge. The literature review gives you a chance to:

• Demonstrate your familiarity with the topic and its scholarly context
• Develop a theoretical framework and methodology for your research
• Position your work in relation to other researchers and theorists
• Show how your research addresses a gap or contributes to a debate
• Evaluate the current state of research and demonstrate your knowledge of the scholarly debates around your topic.

Writing literature reviews is a particularly important skill if you want to apply for graduate school or pursue a career in research. We’ve written a step-by-step guide that you can follow below.

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See an example

Writing literature reviews can be quite challenging! A good starting point could be to look at some examples, depending on what kind of literature review you’d like to write.

• Example literature review #1: “Why Do People Migrate? A Review of the Theoretical Literature” ( Theoretical literature review about the development of economic migration theory from the 1950s to today.)
• Example literature review #2: “Literature review as a research methodology: An overview and guidelines” ( Methodological literature review about interdisciplinary knowledge acquisition and production.)
• Example literature review #3: “The Use of Technology in English Language Learning: A Literature Review” ( Thematic literature review about the effects of technology on language acquisition.)
• Example literature review #4: “Learners’ Listening Comprehension Difficulties in English Language Learning: A Literature Review” ( Chronological literature review about how the concept of listening skills has changed over time.)

You can also check out our templates with literature review examples and sample outlines at the links below.

Download Word doc Download Google doc

Before you begin searching for literature, you need a clearly defined topic .

If you are writing the literature review section of a dissertation or research paper, you will search for literature related to your research problem and questions .

Make a list of keywords

Start by creating a list of keywords related to your research question. Include each of the key concepts or variables you’re interested in, and list any synonyms and related terms. You can add to this list as you discover new keywords in the process of your literature search.

• Social media, Facebook, Instagram, Twitter, Snapchat, TikTok
• Body image, self-perception, self-esteem, mental health
• Generation Z, teenagers, adolescents, youth

Search for relevant sources

Use your keywords to begin searching for sources. Some useful databases to search for journals and articles include:

• Your university’s library catalogue
• Google Scholar
• Project Muse (humanities and social sciences)
• Medline (life sciences and biomedicine)
• EconLit (economics)
• Inspec (physics, engineering and computer science)

You can also use boolean operators to help narrow down your search.

Make sure to read the abstract to find out whether an article is relevant to your question. When you find a useful book or article, you can check the bibliography to find other relevant sources.

You likely won’t be able to read absolutely everything that has been written on your topic, so it will be necessary to evaluate which sources are most relevant to your research question.

For each publication, ask yourself:

• What question or problem is the author addressing?
• What are the key concepts and how are they defined?
• What are the key theories, models, and methods?
• Does the research use established frameworks or take an innovative approach?
• What are the results and conclusions of the study?
• How does the publication relate to other literature in the field? Does it confirm, add to, or challenge established knowledge?
• What are the strengths and weaknesses of the research?

Make sure the sources you use are credible , and make sure you read any landmark studies and major theories in your field of research.

You can use our template to summarize and evaluate sources you’re thinking about using. Click on either button below to download.

Take notes and cite your sources

As you read, you should also begin the writing process. Take notes that you can later incorporate into the text of your literature review.

It is important to keep track of your sources with citations to avoid plagiarism . It can be helpful to make an annotated bibliography , where you compile full citation information and write a paragraph of summary and analysis for each source. This helps you remember what you read and saves time later in the process.

To begin organizing your literature review’s argument and structure, be sure you understand the connections and relationships between the sources you’ve read. Based on your reading and notes, you can look for:

• Trends and patterns (in theory, method or results): do certain approaches become more or less popular over time?
• Themes: what questions or concepts recur across the literature?
• Debates, conflicts and contradictions: where do sources disagree?
• Pivotal publications: are there any influential theories or studies that changed the direction of the field?
• Gaps: what is missing from the literature? Are there weaknesses that need to be addressed?

This step will help you work out the structure of your literature review and (if applicable) show how your own research will contribute to existing knowledge.

• Most research has focused on young women.
• There is an increasing interest in the visual aspects of social media.
• But there is still a lack of robust research on highly visual platforms like Instagram and Snapchat—this is a gap that you could address in your own research.

There are various approaches to organizing the body of a literature review. Depending on the length of your literature review, you can combine several of these strategies (for example, your overall structure might be thematic, but each theme is discussed chronologically).

Chronological

The simplest approach is to trace the development of the topic over time. However, if you choose this strategy, be careful to avoid simply listing and summarizing sources in order.

Try to analyze patterns, turning points and key debates that have shaped the direction of the field. Give your interpretation of how and why certain developments occurred.

If you have found some recurring central themes, you can organize your literature review into subsections that address different aspects of the topic.

For example, if you are reviewing literature about inequalities in migrant health outcomes, key themes might include healthcare policy, language barriers, cultural attitudes, legal status, and economic access.

Methodological

If you draw your sources from different disciplines or fields that use a variety of research methods , you might want to compare the results and conclusions that emerge from different approaches. For example:

• Look at what results have emerged in qualitative versus quantitative research
• Discuss how the topic has been approached by empirical versus theoretical scholarship
• Divide the literature into sociological, historical, and cultural sources

Theoretical

A literature review is often the foundation for a theoretical framework . You can use it to discuss various theories, models, and definitions of key concepts.

You might argue for the relevance of a specific theoretical approach, or combine various theoretical concepts to create a framework for your research.

Like any other academic text , your literature review should have an introduction , a main body, and a conclusion . What you include in each depends on the objective of your literature review.

The introduction should clearly establish the focus and purpose of the literature review.

Depending on the length of your literature review, you might want to divide the body into subsections. You can use a subheading for each theme, time period, or methodological approach.

As you write, you can follow these tips:

• Summarize and synthesize: give an overview of the main points of each source and combine them into a coherent whole
• Analyze and interpret: don’t just paraphrase other researchers — add your own interpretations where possible, discussing the significance of findings in relation to the literature as a whole
• Critically evaluate: mention the strengths and weaknesses of your sources
• Write in well-structured paragraphs: use transition words and topic sentences to draw connections, comparisons and contrasts

In the conclusion, you should summarize the key findings you have taken from the literature and emphasize their significance.

When you’ve finished writing and revising your literature review, don’t forget to proofread thoroughly before submitting. Not a language expert? Check out Scribbr’s professional proofreading services !

This article has been adapted into lecture slides that you can use to teach your students about writing a literature review.

Scribbr slides are free to use, customize, and distribute for educational purposes.

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If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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 thesis, dissertation , or research paper , in order to situate your work in relation to existing knowledge.

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

• To familiarize 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.

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

A literature review is a survey of credible sources on a topic, often used in dissertations , theses, and research papers . Literature reviews give an overview of knowledge on a subject, helping you identify relevant theories and methods, as well as gaps in existing research. Literature reviews are set up similarly to other  academic texts , with an introduction , a main body, and a conclusion .

An  annotated bibliography is a list of  source references that has a short description (called an annotation ) for each of the sources. It is often assigned as part of the research process for a  paper .  

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2024 Theses Doctoral

Romanticism’s Children: Nostalgia and Fantasy in Music from Schumann to The Legend of Zelda

Shahmehri, Demetrius

This dissertation comparatively examines musical nostalgia, particularly nostalgia for childhood, in video games and post-Romantic classical music. An introductory chapter lays out several key concepts drawn from video games—loops, gameworlds, and role-play—and suggests the correspondences these have in Romantic music and thought. The central chapters offer case studies of pieces by Robert Schumann, Brahms, Debussy, and Ravel, each along with a corresponding concept drawn from video games. Each chapter articulates ways that works by these composers provide analogies for practices in contemporary role-playing and adventure video games and, conversely, suggests that features drawn from those games might illuminate how these pieces create musical meaning out of dwelling on the past or imagining distant places. The central chapters draw video games and classical music more closely together over their course. In an analysis of Schumann’s Kinderszenen, I suggest that Schumann’s music could be conceived as offering the player a form of role-play, allowing its players and listeners to play as an imagined child and gain access to otherwise inaccessible space. Brahms’s works often dwell in the past (and are often analyzed as such), especially when that past is metaphorically conceived as childhood or the classical tradition. I suggest that we might hear Brahms’s music as preoccupied with the “unrevisitable location,” a feature of video games in which certain spaces are visitable only a fixed number of times and therefore charged with melancholy and loss. Debussy’s Children’s Corner extends role-play to an extreme degree, while at the same time suggesting distant, unreachable vistas. In particular, I borrow Jay David Bolter and Richard Grusin’s ideas on mediation and Christopher Goetz’s notion of “nostalgic travel” to suggest ways that Debussy’s music incorporates impossible distance into its sound and structure. Video games and classical music converge as much as possible in an analysis of Ravel’s Ma mère l’Oye, which I read alongside Nintendo’s open-world game The Legend of Zelda: Breath of the Wild. I suggest that Ravel’s music offers space for its players to explore similar to this video game. In particular, we might hear the music as allowing linear narrative to give way to a freer, open-ended exploration, suggesting the opening of a world. Finally, a concluding chapter examines nostalgia in video games themselves, specifically Undertale, Final Fantasy VII, and Final Fantasy VII Remake, while revisiting elements of the Romantic musical past as they have accrued in the dissertation so far. The argument in this final chapter is that of the dissertation as a whole: that the same desires for fantasy and adventure animate both traditions, and that the two provide meaningful contexts for each other, in ways that studies of the two have until now overlooked.

• Video games
• Nostalgia in music
• Romanticism in music
• Schumann, Robert, 1810-1856
• Brahms, Johannes, 1833-1897
• Debussy, Claude, 1862-1918
• Ravel, Maurice, 1875-1937
• Kinderszenen (Schumann, Robert)
• Children's corner (Debussy, Claude)
• Ma mère l'oye (Piano duet) (Ravel, Maurice)

More About This Work

• DOI Copy DOI to clipboard

EFFICIENT INFERENCE AND DOMINANT-SET BASED CLUSTERING FOR FUNCTIONAL DATA

This dissertation addresses three progressively fundamental problems for functional data analysis: (1) To do efficient inference for the functional mean model accounting for within-subject correlation, we propose the refined and bias-corrected empirical likelihood method. (2) To identify functional subjects potentially from different populations, we propose the dominant-set based unsupervised clustering method using the similarity matrix. (3) To learn the similarity matrix from various similarity metrics for functional data clustering, we propose the modularity guided and dominant-set based semi-supervised clustering method.

In the first problem, the empirical likelihood method is utilized to do inference for the mean function of functional data by constructing the refined and bias-corrected estimating equation. The proposed estimating equation not only improves efficiency but also enables practically feasible empirical likelihood inference by properly incorporating within-subject correlation, which has not been achieved by previous studies.

In the second problem, the dominant-set based unsupervised clustering method is proposed to maximize the within-cluster similarity and applied to functional data with a flexible choice of similarity measures between curves. The proposed unsupervised clustering method is a hierarchical bipartition procedure under the penalized optimization framework with the tuning parameter selected by maximizing the clustering criterion called modularity of the resulting two clusters, which is inspired by the concept of dominant set in graph theory and solved by replicator dynamics in game theory. The advantage offered by this approach is not only robust to imbalanced sizes of groups but also to outliers, which overcomes the limitation of many existing clustering methods.

In the third problem, the metric-based semi-supervised clustering method is proposed with similarity metric learned by modularity maximization and followed by the above proposed dominant-set based clustering procedure. Under semi-supervised setting where some clustering memberships are known, the goal is to determine the best linear combination of candidate similarity metrics as the final metric to enhance the clustering performance. Besides the global metric-based algorithm, another algorithm is also proposed to learn individual metrics for each cluster, which permits overlapping membership for the clustering. This is innovatively different from many existing methods. This method is superiorly applicable to functional data with various similarity metrics between functional curves, while also exhibiting robustness to imbalanced sizes of groups, which are intrinsic to the dominant-set based clustering approach.

In all three problems, the advantages of the proposed methods are demonstrated through extensive empirical investigations using simulations as well as real data applications.

Research supported in part by NSF awards DMS-2212928 (2024).

Degree type.

• Doctor of Philosophy
• Mathematics

Campus location

• Indianapolis

Advisor/Supervisor/Committee Chair

Additional committee member 2, additional committee member 3, additional committee member 4, usage metrics.

• Applied statistics

Artificial Intelligence Doesn’t ‘Get’ Memes. Here’s Why That Could Save Us From the Singularity

Our silly little jokes totally confuse AI, which proves “humans have the upper hand over machines,” an expert tells us.

At least, for now.

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On the path to receiving a Ph.D. in electrical and computer engineering at Delaware University in 2021, Ishaani Priyadarshini wrote her dissertation on the topic of AI’s inability to decipher memes, and how that could help us in the battle toward singularity. “Internet memes serve as excellent checkpoints to ensure humans have the upper hand over machines, thereby preventing machines from understanding memes and surpassing human intelligence,” she tells Popular Mechanics .

Memes vs. Superintelligent Machines

Before pursuing artificial intelligence, Priyadarshini’s background was in cybersecurity , and she observed that over 50 percent of the internet is made up of bots—some of these bots are good, while others have malicious intent . This confirmed her worst fear: if AI were to achieve sentience and go rogue, it could spell disaster for your online data and privacy. “They would be able to gain every piece of information that is out there in the cyberspace … it could lead to catastrophic results in the future,” says Priyadarshini.

Her goal was to find a security measure that could defeat artificial intelligence before it ever reaches this point. The solution? Memes. These surprisingly complex amalgamations of text and images often pick apart the more humorous bits of pop culture and current events—and are usually posted across multiple social media platforms. (Picture Grumpy Cat and Doge.)

Priyadarshini wanted to find out why AI was so poor at decoding memes, along with how the humorous posts could be used as a cybersecurity tool in the future. AI’s inability to comprehend memes is multifaceted, but much of it has to do with the fact that they tend to be ambiguous. Priyadarshini says that our understanding of memes relies heavily on our own life experiences. “For a machine, memes are merely a bunch of text and images,” she explains.

We already have AIs that are able to recognize text and facial expressions , but there are really no rules with memes. Sure, Optical Character Recognition (an advanced system, able to recognize text in images) can already be used to accurately read license plates, but this type of machine learning already has a very good idea of where to look—decoding the text from memes is a completely different story.

“There’s no template that memes follow, which is why extracting the text from them is really challenging,” says Priyadarshini. You could argue that most memes are just variations on the same template, but the same meme could still be interpreted wildly differently depending on the content that’s been injected.

Memes Are Much More Complex Than We Think

We currently have no idea if AI has the ability to be sentient, meaning it would be able to think for itself and make its own decisions; even if we did know, it’s unclear how we’d measure just how sentient an AI is. That being said, we can measure AI’s ability to extract emotions from text and facial expressions—and it’s already pretty awful at picking up emotions from snippets of text. The billions of permutations you’ll find in both text and facial expressions make it difficult for AI to crack the code. That’s before we even bring in the context of the meme itself.

“Understanding memes could forever be a challenge for AI and remain an unsolvable problem,” Priyadarshini says in her dissertation .

Despite memes’ reputation as nothing more than mindless images on the internet, the process of unpacking them is actually much more complex than we thought. The human brain has an uncanny knack for parsing through an unimaginable amount of data very quickly—helping us understand memes in a matter of seconds. “Superintelligent machines” ... not so much.

✅ Understanding Context

Without life experiences, AI doesn’t have much context to lean on. Remember all the Suez Canal memes from back in 2021? Let’s use the meme below as an example:

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An AI might be able to recognize that there’s a container ship in the video. However, can it properly identify it as the Ever Given that had run aground in the Suez Canal? To add another layer of complexity on top of that, why is Austin Powers in the background making a 27-point turn? Does it know that the Austin Powers movie series is supposed to be funny? “It may not be an easy task for AI to comprehend internet memes given the plethora and variety of memes found on the internet, along with the different patterns each of the memes can generate,” Priyadarshini says in her dissertation, which was published in the journal Computers, Materials, and Continua .

Meanwhile, the human brain is able to pick up the pieces with very little effort and register the clever parallel between Austin Powers’ multi-point turn and the container ship maneuvering out of the Suez canal.

An NPR exclusive with behavioral and data scientist Pragya Agarwal, Ph.D., reveals that the human brain can process roughly 11 million bits of information every second—that’s 0.011 gigabits per second. However, our conscious mind (filled with thoughts we’re aware of) can only grab onto about 40 to 50 bits per second. Thankfully, our brain’s amygdala is able to drink from this firehose of information by taking shortcuts to get the bigger picture; Agarwal mentions that the amygdala (the part of your brain responsible for your “gut” feeling) is able to match new information with pre-existing stereotypes and templates to make sense of it.

AI Databases Are Difficult and Labor Intensive to Train

Even if AI could successfully decode memes, that’s only one part of the puzzle. Internet memes are moving at, well , the speed of the internet —meaning AI has to keep up. Something that was funny last week could be considered old news in a matter of days. To offer some perspective, ChatGPT (an AI chatbot) has only been trained with a snapshot of the internet from 2021 . Anything after that simply doesn’t exist to it.

Think of the memes that we saw in 2022, like those about the distribution of 1 billion free COVID-19 tests . Sure, the meme involves a photograph of the family from Full House , which AI would likely be able to recognize. However, without any context that the U.S. government was giving out free COVID-19 test kits, how would AI know what on Earth was going on in this image?

It would have to extrapolate the fact that every home in the United States is only eligible for just four free covid tests. We can clearly deduce that four test kits won’t nearly be enough for most families, but AI isn’t that sophisticated. Plus, artificial intelligence doesn’t really have a sense of humor.

Humor and AI Don’t Mix (Yet)

Being funny is an incredibly sophisticated skill that can mean different things to different people. This subjectivity makes it difficult for AI to understand humor—remember that only certain people might find one piece of content inherently funny. Priyadarshini mentions that AI would be able to parse through screen grabs from The Office and know that it’s a comedy, but it wouldn’t be able to unpack the humor within each scene; it has more of a binary is-this-funny-or-not type of understanding.

“The real challenge comes from identifying the different kinds of humor that are in those sentences or the videos,” says Priyadarshini. We’re just talking about general humor here, but there are also jokes that might involve dark humor, witty humor, or even dry humor. It really brings into sharp focus the psychology of what makes something funny. “We also don’t know what is the true sense of humor … it is different for everyone,” says Priyadarshini.

Without AI being sentient, it’s not clear if it will ever be able to have a complete understanding of humor.

A Futuristic CAPTCHA

Riffing on Full House is all well and good, but what will this next-level CAPTCHA —short for Completely Automated Public Turing to tell Computers and Humans Apart—look like in a real-world application? Priyadarshini simply thinks of it as a much more three-dimensional test to differentiate humans from machines; instead of reading weird text or picking which boxes have bridges in them, you’ll instead have to decode the meaning of a meme.

She gave a theoretical example of an authentication system for a nuclear power station . The employee would begin as usual by entering their username and password. Once that’s done, they’ll be prompted with a meme. In this instance, Priyadarshini used the case of the Chubby Bubbles meme (see below) where the user will be given four prompts to identify what is going on in the meme. There are still more questions than answers about how this type of test would work in practice, but it’s a novel idea that could revolutionize the future of cybersecurity.

We love the remote possibility of nuclear power station workers deciphering random memes before getting their day going. Sure, we’re most likely not giving up the nuclear football system anytime soon, but it certainly poses the question of improving security measures elsewhere. Above all, we’re happy to report the future of cybersecurity is looking bright—and full of hilarious memes.

Matt Crisara is a native Austinite who has an unbridled passion for cars and motorsports, both foreign and domestic. He was previously a contributing writer for Motor1 following internships at Circuit Of The Americas F1 Track and Speed City, an Austin radio broadcaster focused on the world of motor racing. He earned a bachelor’s degree from the University of Arizona School of Journalism, where he raced mountain bikes with the University Club Team. When he isn’t working, he enjoys sim-racing, FPV drones, and the great outdoors.

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Enrollment Groups Frequently Asked Questions

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• Starting in autumn quarter 2023, Stanford will introduce a staggered approach to the opening of enrollment. Enrollment groups consisting of 2,000 students each, will initiate the enrollment process in a staggered manner. These groups will be spaced at intervals of 30 minutes, allowing for a smooth and efficient progression throughout the enrollment period. 
• To ensure the system can handle the load, we are limiting the number of enrollment transactions  students can submit per minute. You will be able to submit a maximum of five individual classes and up to  two batch enroll requests within a minute. These measures aim to prevent the misuse of bots and promote a fair and equitable enrollment experience for all students.
• We’re staggering enrollment in response to student feedback and the need to optimize your enrollment experience. By strategically staggering students into groups, we can prioritize students who are closer to graduation, and greatly reduce the excessive load on our system that typically arises during the opening of enrollment, ensuring a smoother and more stable student experience.
• To prepare for enrollment, there are a few things you can do prior to your enrollment group start time. In order to ensure that Axess and SimpleEnroll are displaying and behaving as expected, it would be best to clear your browser's cache before logging in to Axess or SimpleEnroll. Be sure to review your Axess account to resolve any enrollment holds or to-do items. 
• A week before enrollment, you will receive an email with your enrollment group and unique start time. This information will also be available in Axess in the Enroll in Classes section under the My Academics menu. Your unique start time will also display as a banner in SimpleEnroll: simpleenroll.stanford.edu

Enrollment Group Assignment

• For undergraduates, we are prioritizing those with the most enrolled quarters at Stanford. Transfer students will require fewer completed quarters to enroll at similar times to their social cohort.
• For graduate and professional students students, second-year students will get first access to enroll, followed by first-year, third-year and beyond, and then Terminal Graduate Registration (TGR) students.
• We evaluated multiple student-centered criteria in order to determine the most equitable and optimal way to group students in a way that promotes fairness, considers time to degree completion, and the spread of students across our different campus populations. We strived to implement a process that would discourage any practices that could lead to students overextending themselves to earn an advantage in future quarters. Evaluating enrollment groups on completed quarters was identified as the best way to accomplish the goal of providing a smooth and equitable enrollment process for all groups across campus.
• The assignment of enrollment groups is based on the number of quarters completed, meaning students closer to graduation will have earlier start times than those who are newer in their academic journey. For that reason, we are unable to accommodate requests to change these groups. We appreciate your understanding and encourage you to make the most of the available options during your assigned enrollment start time.
• Enrollment group start times were designed to support students in the fairest way possible across all of our student populations by assigning them based on students' proximity to graduation based upon the typical time for degree completion. At this time we are unable to consider individual circumstances to adjust the assignment of enrollment start times. To ensure an equitable outcome, all students will be evaluated based on the number of completed quarters. 
• Your enrollment group could change from quarter to quarter as you continue to accumulate completed quarters and other students graduate. Each enrollment group is a mix of all student levels: undergraduate, graduate, and professional school students. There is no guarantee that you will have the same or an earlier start time from quarter to quarter.
• Students are assigned to an enrollment group with a unique identifier that cannot be traded or changed. There is no appeals process to get a different enrollment group assignment.
• To ensure equity across all student types, each enrollment group is a mix of undergraduate, graduate, and professional school students. This means you could have a slightly earlier or later start time than those of your peers. Please note that all enrolled quarters are counted, including summers and programs tied to enrollment that last a portion of the summer, such as SoCo and AI.
• Students on approved TGR status have been placed in the last enrollment group priority regardless of the number of quarters they have completed. This is applicable for all TGR students across all graduate degree-seeking program types: MA, MS, PhD.

To ensure equity for across students while maintaining equal sizes for each enrollment group (~2,000 students), we randomly assigned students of the same priority level into multiple groups. For example, the first four enrollment groups (Groups 1-4) are designated for undergraduate seniors, 2nd-year graduate students, and professional school students. The entire cohort of students (~7,800) that met this eligibility criterion was randomly divided into one of the four time-slots (~1950 per group). A 5:30 p.m. start time does not represent any prioritization over a 6:00 p.m., 6:30 p.m., or 7:00 p.m. start time; sorting students of equal priority into these groups was entirely random. 

We understand that receiving the last enrollment group time might feel discouraging but note that your enrollment group time may change in future quarters. Additionally, some of our most sought-after courses, such as PHYSWELL, utilize a feature called reserve seating . This feature allows the course to have seats reserved for particular groups of students during the enrollment period. For example, many PHYSWELL courses reserve seats specifically designated for Frosh, Sophomores, Juniors, and Seniors to ensure that all cohorts have an equal opportunity to enroll in these courses. Due to the popularity of these courses, students are allowed to register for only one PHYSWELL course during the first 24 hours of registration.

Multiple Degree Programs (coterms & dual-degree graduates)

• Your billing career will determine if you’re prioritized as an undergraduate or graduate student (e.g. if you are on graduate billing, your enrollment group will be assigned based on the assignment logic for graduate students). If your billing career changes after you’ve been assigned an enrollment group, you will remain in your original group. There will be no changes to enrollment groups once assigned. 

For coterms on graduate billing, the number of completed quarters is derived from the number of quarters you have completed since you began your coterminal program, or more clearly, your first graduate quarter. Your first graduate quarter can be identified on the first page on your unofficial graduate transcript, in the top left section, as seen in the image below. Coterminal “quarters back” are not being considered in this evaluation. 

• Coterminal and dual degree students will be assigned the same enrollment group and start time for both active degree programs. Please be sure to select the correct career designation for each course when making your enrollment decisions. 
• We began counting completed quarters from your earliest active graduate program, based on your billing group. For example, if you have an active PhD program but have previously conferred a master's degree, we are only counting quarters since the first quarter of the active PhD program; prior quarters completed for the master's program (if opened before the PhD program was added) would not count. If you have two open programs with different associated billing groups (i.e. GSB program & regular graduate program), we are counting quarters completed in the degree program associated with your billing group (i.e. GSB billing = counting quarters completed since the beginning of the GSB program).  

General Enrollment Questions

• There will be no specific end times for these groups. Once your enrollment group begins, you are free to enroll and make adjustments to your study list until the Final Study List deadline.
• As always, for classes that are full, students are encouraged to join the waitlist for a class, if available, in case space becomes available.
• Your enrollment group designates the beginning of your access to the enrollment system for autumn quarter. You will have the ability to make adjustments to your study list immediately and through the entire open enrollment period.
• The enrollment group designates the time you are able to begin enrolling. If your start time has past, you can simply log in to enroll anytime. Enrollment will remain open until the Final Study List deadline.

Still need help?

If you have additional questions, reach out to the Registrar's office.

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Stanford Online

Artificial intelligence professional program.

Stanford School of Engineering

Per course $1,750 USD

10 weeks per course, 10-15 hours per week

Get Started

Artificial intelligence is transforming the world and helping organizations of all sizes grow, innovate, and make smarter decisions. The Artificial Intelligence Professional Program will equip you with knowledge of the principles, tools, techniques, and technologies driving this transformation. This online program provides rigorous coverage of the most important topics in modern artificial intelligence, including:

Machine Learning

• Deep Learning
• Natural Language Processing and Understanding
• Supervised and Unsupervised Learning

Reinforcement Learning

• Graph Neural Networks (GNNs)
• Multi-Task and Meta-Learning

The courses will equip you with the skills and confidence to:

• Build your own AI models and algorithms without the constraints of off-the-shelf solutions.
• Innovate and create new models, tools, and algorithms to tackle real-world challenges in AI.
• Effectively debug your code.
• Fine-tune and optimize model parameters for better results.
• Evaluate performance of AI models accurately.
• Implement generative language models.
• Perform few-shot and zero-shot learning with pre-trained language models.
• Understand research results and conduct your own research in the field.

Artificial Intelligence Professional Program FAQs

What you can expect

What you need to get started

Prior to enrolling in your first course, you must complete a short application (15-20 minutes). The application allows you to share more about your interest in joining, as well as verify that you meet the prerequisite requirements needed to make the most of the experience:

• Proficiency in Python: Coding assignments will be in Python. Some assignments will require familiarity with basic Linux command line workflows.
• College Calculus and Linear Algebra: You should be comfortable taking (multivariable) derivatives and understand matrix/vector notation and operations.
• Probability Theory: You should be familiar with basic probability distributions (Continuous, Gaussian, Bernoulli, etc.) and be able to define concepts for both continuous and discrete random variables: Expectation, independence, probability distribution functions, and cumulative distribution functions.

NOT SURE IF THIS PROGRAM IS RIGHT FOR YOU?

Learn about the differences between the graduate and professional AI Programs .

• Preview Image
• Course/Course #
• Time Commitment
• Availability

Deep Generative Models

• Aug 19 - Oct 27, 2024

Natural Language Understanding

• Aug 26 - Nov 3, 2024

Artificial Intelligence: Principles and Techniques

• Sep 9 - Nov 17, 2024

Natural Language Processing with Deep Learning

• Sep 16 - Nov 24, 2024

Machine Learning with Graphs

• Oct 7 - Dec 15, 2024

• Nov 4, 2024 - Jan 26, 2025

• Nov 11, 2024 - Feb 2, 2025

Flexible Enrollment Options

Individual enrollments.

$1,750 per course

Courses are online and the pace is set by the instructor. You will be part of a group of learners going through the course together. You will have scheduled assignments to apply what you've learned and will receive direct feedback from course facilitators.

Groups and Teams

Special Pricing

Have a group of five or more? Enroll as a group and learn together! By participating together, your group will develop a shared knowledge, language, and mindset to tackle challenges ahead. We can advise you on the best options to meet your organization’s training and development goals.

What You'll Earn

You’ll earn a Stanford Professional Certificate in Artificial Intelligence when you successfully complete either:

• Three courses in the AI professional education program, OR
• Two courses in the AI professional education program AND one course in the AI Graduate Program.

Your blockchain-verified digital certificate will allow you to showcase your achievements on LinkedIn and other platforms, validate credentials with employers, and highlight your expertise.

Academic Director

Christopher Manning

Thomas M. Siebel Professor of Machine Learning

Computer Science

Christopher Manning is a Professor of Computer Science and Linguistics at Stanford University and Director of the Stanford Artificial Intelligence Laboratory. He works on software that can intelligently process, understand, and generate human language material. He is a leader in applying Deep Learning to Natural Language Processing, including exploring Tree Recursive Neural Networks, neural network dependency parsing, the GloVe model of word vectors, neural machine translation, question answering, and deep language understanding. He also focuses on computational linguistic approaches to parsing, robust textual inference and multilingual language processing, including being a principal developer of Stanford Dependencies and Universal Dependencies. Manning is an ACM Fellow, a AAAI Fellow, an ACL Fellow, and a Past President of ACL. He has coauthored leading textbooks on statistical natural language processing and information retrieval. He is a member of the Stanford NLP group (@stanfordnlp) and manages development of the Stanford CoreNLP software.

Teaching Team

Emma Brunskill

Associate Professor

Emma Brunskill is an Assistant Professor at Stanford University. Her goal is to increase human potential through advancing interactive machine learning. Revolutions in storage and computation have made it easy to capture and react to sequences of decisions made and their outcomes. Simultaneously, due to the rise of chronic health conditions, and demand for educated workers, there is an urgent need for more scalable solutions to assist people to reach their full potential. Interactive machine learning systems could be a key part of the solution. To enable this, her lab's work spans from advancing theoretical understanding of reinforcement learning, to developing new self-optimizing tutoring systems that they test with learners and in the classroom. Their applications focus on education since education can radically transform the opportunities available to an individual.

Stefano Ermon

Stefano Ermon is an Assistant Professor in the Department of Computer Science at Stanford University, where he is affiliated with the Artificial Intelligence Laboratory and a fellow of the Woods Institute for the Environment. His research is centered on techniques for scalable and accurate inference in graphical models, statistical modeling of data, large-scale combinatorial optimization, and robust decision making under uncertainty, and is motivated by a range of applications, in particular ones in the emerging field of computational sustainability.

Jure Leskovec

Jure Leskovec is an Associate Professor of Computer Science at Stanford University. Leskovec's research focuses on the analyzing and modeling of large social and information networks as the study of phenomena across the social, technological, and natural worlds. He focuses on statistical modeling of network structure, network evolution, and spread of information, influence and viruses over networks. Problems he investigates are motivated by large scale data, the Web and other on-line media. He also does work on text mining and applications of machine learning.

Percy Liang

Associate Professor Computer Science

Percy Liang is an Assistant Professor in the Computer Science department. He works on methods that infer representations of meaning from sentences given limited supervision. What's particularly exciting to him is the interface between rich semantic representations (e.g., programs or logical forms) for capturing deep linguistic phenomena, and probabilistic modeling for allowing these representations to be learned from data. More generally, he is interested in modeling both natural and programming languages, and exploring the semantic and pragmatic connections between the two. 

Assistant Professor

Tengyu Ma is an Assistant Professor of Computer Science and Statistics at Stanford University. His research interests broadly include topics in machine learning and algorithms, such as non-convex optimization, deep learning and its theory, reinforcement learning, representation learning, distributed optimization, convex relaxation (e.g. sum of squares hierarchy), and high-dimensional statistics. He received my Ph.D. from the Computer Science Department at Princeton University where he was advised by Professor Sanjeev Arora. As an undergrad, Tengyu Ma studied at Andrew Chi-Chih Yao's CS pilot class at Tsinghua University.

Christopher Potts

Linguistics

Christopher Potts is a Professor of Linguistics and, by courtesy, of Computer Science and the Director of The Center for the Study of Language and Information (CSLI). In his research, he uses computational methods to explore how emotion is expressed in language and how linguistic production and interpretation are influenced by the context of utterance. He is the author of the 2005 book The Logic of Conventional Implicatures as well as numerous scholarly papers in computational and theoretical linguistics.

Christopher Ré

Christopher (Chris) Ré is an Associate Professor in the Department of Computer Science at Stanford University in the InfoLab who is affiliated with the Statistical Machine Learning Group, Pervasive Parallelism Lab, and Stanford AI Lab. His work's goal is to enable users and developers to build applications that more deeply understand and exploit data. His contributions span database theory, database systems, and machine learning, and his work has won best paper at a premier venue in each area, respectively, at PODS 2012, SIGMOD 2014, and ICML 2016. In addition, work from his group has been incorporated into major scientific and humanitarian efforts, including the IceCube neutrino detector, PaleoDeepDive and MEMEX in the fight against human trafficking, and into commercial products from major web and enterprise companies. He cofounded a company, based on his research, that was acquired by Apple in 2017. He received a SIGMOD Dissertation Award in 2010, an NSF CAREER Award in 2011, an Alfred P. Sloan Fellowship in 2013, a Moore Data Driven Investigator Award in 2014, the VLDB early Career Award in 2015, the MacArthur Foundation Fellowship in 2015, and an Okawa Research Grant in 2016.

Dorsa Sadigh

Dorsa Sadigh is an Assistant Professor in the Computer Science Department and Electrical Engineering Department at Stanford University. Her work is focused on the design of algorithms for autonomous systems that safely and reliably interact with people.

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Jürgen Moltmann, 2014

In Memoriam: Jürgen Moltmann (1926 – 2024)

Remembering a Theologian of Hope

Miroslav Volf

https://faith.yale.edu/media/in-memoriam-jurgen-moltmann-1926-2024

Information

New episodes drop every Wednesday. Subscribe anywhere podcasts are found.

Jürgen Moltmann

Jessica Hooten Wilson

Episode Summary

Miroslav Volf remembers his mentor and friend, German theologian Jürgen Moltmann, who passed away on June 3, 2024.

Jürgen Moltmann (April 8, 1926 – June 3, 2024)

On June 3,2024, Jürgen Moltmann died. He was one of the greatest theologians of our time. I met him for the first time when, in April of 1979, on my way from California back home to Yugoslavia, I stopped in Germany to inquire whether I could do doctoral work under his supervision. In the summer of 1980, I moved to Tübingen (where he taught from 1967 until his retirement in 1994), and in the fall he became, as Germans say, my Doktorvater —doctoral father. We soon became friends. His influence on my life and my theology has been profound.

Moltmann had become world famous some 15 years earlier. Publication of the English translation of his Theology of Hope was front page news in the New York Times . Many people in the United States read it as a response to the so-called “death of God” theology; at the time, “death of God” theology seemed like a tsunami in the ocean of theology, but turned out to be no more than a small ripple. Moltmann’s work, however, left a major mark on modern theology. Eloquent witness to his influence are the more than 500 (!) doctoral dissertations on his theology written thus far; I know of one more being written even now. He was a brilliant theologian, and a highly creative one as well. The great attraction of his theology is that it is “fresh,” close to the pulse of life. He wrote about things that move people—about suffering and joy, about exploitation, discrimination and solidarity, about the travails of God’s creatures under human greed, about life and death. And he wrote about life by exploring the great themes of Christian faith: God, Christ, Spirit, creation, redemption, and new creation.

Moltmann acquired a reputation of being a “political theologian,” and this he certainly was. But he was a champion of the church as well, especially those churches which he saw pulsating with new life. He himself was a convert to the Christian faith, and for him the Gospel was always a message of life-giving hope. Incongruous as it may sound to many, he was a friend of both Paul Yonggi Cho, the pastor of the largest Christian congregation in the world, and of Robert Schuller, so flamboyant in his TV presence; Moltmann preached in both the Yoido Full Gospel Church in Seoul, Korea and the Crystal Cathedral in California.

My last contact with Moltmann was 9 days before he died. On May 25, I sent him an email inquiring how he was doing and giving him a bit of an update on what was happening in my life. The next day, I received a longish response, which started with, “Es geht mir gut”—“I am well.” He was positive and full of hope until the very end.

Last April, I received from him a copy of his talk at the celebration of his 97 th birthday. In it, he reflects about his impending death:

Every morning I am amazed that I am still here. ... To die means to let go. I am preparing myself for this. To die means to give one’s life over to God. I am preparing myself for that, too. The raising to eternal life is my hope in life and in death. The eternal life will also be lived. This is the life of God’s new creation. Death is like a birthday to new life in God’s kingdom. Every morning of every new day that hope gives me new courage to live. But I did not invite you here to ponder things with me but to rejoice with me. Let us toast to life—here and there!

I mourn his passing. But perhaps his death is not just an occasion for mourning but for celebration as well. “Let us toast to his life — here and there!”

Miroslav Volf June 5, 2024

Download the PDF Version

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September 1, 2020

The Joy of Humility

The true meaning of humility persistently drives debate, largely because we cannot agree on the word’s definition. The "correctness" of normative terms matters, and humility carries a distinctive normative weight. How we understand humility is not a matter of mere semantics. It is a pursuit of inquiry with the potential to inform—perhaps even to transform—our lives. The Joy of Humility takes up this task with a view toward the perennial question of what entails a truly flourishing life. Here, philosophers, theologians, ethicists, and psychologists work to frame the debate in such a way that the conversation can move forward.

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Exclusion and Embrace

If the healing word of the Gospel is to be heard today, Christian theology must find ways of speaking that address the hatred of the other. Is there any hope of embracing our enemies? Of opening the door to reconciliation?

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June 5, 2024

Theologian of Hope: Remembering Jürgen Moltmann (1926 – 2024)

Miroslav Volf remembers his mentor and friend, German theologian Jürgen Moltmann. Followed by Moltmann's reflections on joy, hope, and how he came to faith during World War II as a conscripted German soldier.

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Peaceable Assembly

Protests dominate the news. But what is the freedom of assembly? What the First Amendment calls “the right of the people peaceably to assemble”? Legal scholar John Inazu (Washington University, St. Louis) joins Evan Rosa for a discussion of the freedom of assembly—its history, meaning, interpretation, and application—as well as how it impacts the ability for citizens to gather to demonstrate and protest.

April 17, 2024

Poet Micheal O'Siadhail discusses his latest collection of poetry, Desire—reading several poems and commenting on how he dealt with the pandemic and sought to understand it through verse. With Evan Rosa, he discusses his poetry as a living and synthetic record of human history, the nature of human greed and avarice and how it has marred the earth, and the calling to reshape our desires toward what's truly worth desiring: a desire for the sacred, for the transcendent, and ultimately, a desire of God for God's own sake.

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