dissertation a research paper

How To Write A Dissertation Or Thesis

8 straightforward steps to craft an a-grade dissertation.

By: Derek Jansen (MBA) Expert Reviewed By: Dr Eunice Rautenbach | June 2020

Writing a dissertation or thesis is not a simple task. It takes time, energy and a lot of will power to get you across the finish line. It’s not easy – but it doesn’t necessarily need to be a painful process. If you understand the big-picture process of how to write a dissertation or thesis, your research journey will be a lot smoother.  

In this post, I’m going to outline the big-picture process of how to write a high-quality dissertation or thesis, without losing your mind along the way. If you’re just starting your research, this post is perfect for you. Alternatively, if you’ve already submitted your proposal, this article which covers how to structure a dissertation might be more helpful.

How To Write A Dissertation: 8 Steps

• Clearly understand what a dissertation (or thesis) is
• Find a unique and valuable research topic
• Craft a convincing research proposal
• Write up a strong introduction chapter
• Review the existing literature and compile a literature review
• Design a rigorous research strategy and undertake your own research
• Present the findings of your research
• Draw a conclusion and discuss the implications

Step 1: Understand exactly what a dissertation is

This probably sounds like a no-brainer, but all too often, students come to us for help with their research and the underlying issue is that they don’t fully understand what a dissertation (or thesis) actually is.

So, what is a dissertation?

At its simplest, a dissertation or thesis is a formal piece of research , reflecting the standard research process . But what is the standard research process, you ask? The research process involves 4 key steps:

• Ask a very specific, well-articulated question (s) (your research topic)
• See what other researchers have said about it (if they’ve already answered it)
• If they haven’t answered it adequately, undertake your own data collection and analysis in a scientifically rigorous fashion
• Answer your original question(s), based on your analysis findings

In short, the research process is simply about asking and answering questions in a systematic fashion . This probably sounds pretty obvious, but people often think they’ve done “research”, when in fact what they have done is:

• Started with a vague, poorly articulated question
• Not taken the time to see what research has already been done regarding the question
• Collected data and opinions that support their gut and undertaken a flimsy analysis
• Drawn a shaky conclusion, based on that analysis

If you want to see the perfect example of this in action, look out for the next Facebook post where someone claims they’ve done “research”… All too often, people consider reading a few blog posts to constitute research. Its no surprise then that what they end up with is an opinion piece, not research. Okay, okay – I’ll climb off my soapbox now.

The key takeaway here is that a dissertation (or thesis) is a formal piece of research, reflecting the research process. It’s not an opinion piece , nor a place to push your agenda or try to convince someone of your position. Writing a good dissertation involves asking a question and taking a systematic, rigorous approach to answering it.

If you understand this and are comfortable leaving your opinions or preconceived ideas at the door, you’re already off to a good start!

Step 2: Find a unique, valuable research topic

As we saw, the first step of the research process is to ask a specific, well-articulated question. In other words, you need to find a research topic that asks a specific question or set of questions (these are called research questions ). Sounds easy enough, right? All you’ve got to do is identify a question or two and you’ve got a winning research topic. Well, not quite…

A good dissertation or thesis topic has a few important attributes. Specifically, a solid research topic should be:

Let’s take a closer look at these:

Attribute #1: Clear

Your research topic needs to be crystal clear about what you’re planning to research, what you want to know, and within what context. There shouldn’t be any ambiguity or vagueness about what you’ll research.

Here’s an example of a clearly articulated research topic:

An analysis of consumer-based factors influencing organisational trust in British low-cost online equity brokerage firms.

As you can see in the example, its crystal clear what will be analysed (factors impacting organisational trust), amongst who (consumers) and in what context (British low-cost equity brokerage firms, based online).

Need a helping hand?

Attribute #2:   Unique

Your research should be asking a question(s) that hasn’t been asked before, or that hasn’t been asked in a specific context (for example, in a specific country or industry).

For example, sticking organisational trust topic above, it’s quite likely that organisational trust factors in the UK have been investigated before, but the context (online low-cost equity brokerages) could make this research unique. Therefore, the context makes this research original.

One caveat when using context as the basis for originality – you need to have a good reason to suspect that your findings in this context might be different from the existing research – otherwise, there’s no reason to warrant researching it.

Attribute #3: Important

Simply asking a unique or original question is not enough – the question needs to create value. In other words, successfully answering your research questions should provide some value to the field of research or the industry. You can’t research something just to satisfy your curiosity. It needs to make some form of contribution either to research or industry.

For example, researching the factors influencing consumer trust would create value by enabling businesses to tailor their operations and marketing to leverage factors that promote trust. In other words, it would have a clear benefit to industry.

So, how do you go about finding a unique and valuable research topic? We explain that in detail in this video post – How To Find A Research Topic . Yeah, we’ve got you covered 😊

Step 3: Write a convincing research proposal

Once you’ve pinned down a high-quality research topic, the next step is to convince your university to let you research it. No matter how awesome you think your topic is, it still needs to get the rubber stamp before you can move forward with your research. The research proposal is the tool you’ll use for this job.

So, what’s in a research proposal?

The main “job” of a research proposal is to convince your university, advisor or committee that your research topic is worthy of approval. But convince them of what? Well, this varies from university to university, but generally, they want to see that:

• You have a clearly articulated, unique and important topic (this might sound familiar…)
• You’ve done some initial reading of the existing literature relevant to your topic (i.e. a literature review)
• You have a provisional plan in terms of how you will collect data and analyse it (i.e. a methodology)

At the proposal stage, it’s (generally) not expected that you’ve extensively reviewed the existing literature , but you will need to show that you’ve done enough reading to identify a clear gap for original (unique) research. Similarly, they generally don’t expect that you have a rock-solid research methodology mapped out, but you should have an idea of whether you’ll be undertaking qualitative or quantitative analysis , and how you’ll collect your data (we’ll discuss this in more detail later).

Long story short – don’t stress about having every detail of your research meticulously thought out at the proposal stage – this will develop as you progress through your research. However, you do need to show that you’ve “done your homework” and that your research is worthy of approval .

So, how do you go about crafting a high-quality, convincing proposal? We cover that in detail in this video post – How To Write A Top-Class Research Proposal . We’ve also got a video walkthrough of two proposal examples here .

Step 4: Craft a strong introduction chapter

Once your proposal’s been approved, its time to get writing your actual dissertation or thesis! The good news is that if you put the time into crafting a high-quality proposal, you’ve already got a head start on your first three chapters – introduction, literature review and methodology – as you can use your proposal as the basis for these.

Handy sidenote – our free dissertation & thesis template is a great way to speed up your dissertation writing journey.

What’s the introduction chapter all about?

The purpose of the introduction chapter is to set the scene for your research (dare I say, to introduce it…) so that the reader understands what you’ll be researching and why it’s important. In other words, it covers the same ground as the research proposal in that it justifies your research topic.

What goes into the introduction chapter?

This can vary slightly between universities and degrees, but generally, the introduction chapter will include the following:

• A brief background to the study, explaining the overall area of research
• A problem statement , explaining what the problem is with the current state of research (in other words, where the knowledge gap exists)
• Your research questions – in other words, the specific questions your study will seek to answer (based on the knowledge gap)
• The significance of your study – in other words, why it’s important and how its findings will be useful in the world

As you can see, this all about explaining the “what” and the “why” of your research (as opposed to the “how”). So, your introduction chapter is basically the salesman of your study, “selling” your research to the first-time reader and (hopefully) getting them interested to read more.

How do I write the introduction chapter, you ask? We cover that in detail in this post .

Step 5: Undertake an in-depth literature review

As I mentioned earlier, you’ll need to do some initial review of the literature in Steps 2 and 3 to find your research gap and craft a convincing research proposal – but that’s just scratching the surface. Once you reach the literature review stage of your dissertation or thesis, you need to dig a lot deeper into the existing research and write up a comprehensive literature review chapter.

What’s the literature review all about?

There are two main stages in the literature review process:

Literature Review Step 1: Reading up

The first stage is for you to deep dive into the existing literature (journal articles, textbook chapters, industry reports, etc) to gain an in-depth understanding of the current state of research regarding your topic. While you don’t need to read every single article, you do need to ensure that you cover all literature that is related to your core research questions, and create a comprehensive catalogue of that literature , which you’ll use in the next step.

Reading and digesting all the relevant literature is a time consuming and intellectually demanding process. Many students underestimate just how much work goes into this step, so make sure that you allocate a good amount of time for this when planning out your research. Thankfully, there are ways to fast track the process – be sure to check out this article covering how to read journal articles quickly .

Literature Review Step 2: Writing up

Once you’ve worked through the literature and digested it all, you’ll need to write up your literature review chapter. Many students make the mistake of thinking that the literature review chapter is simply a summary of what other researchers have said. While this is partly true, a literature review is much more than just a summary. To pull off a good literature review chapter, you’ll need to achieve at least 3 things:

• You need to synthesise the existing research , not just summarise it. In other words, you need to show how different pieces of theory fit together, what’s agreed on by researchers, what’s not.
• You need to highlight a research gap that your research is going to fill. In other words, you’ve got to outline the problem so that your research topic can provide a solution.
• You need to use the existing research to inform your methodology and approach to your own research design. For example, you might use questions or Likert scales from previous studies in your your own survey design .

As you can see, a good literature review is more than just a summary of the published research. It’s the foundation on which your own research is built, so it deserves a lot of love and attention. Take the time to craft a comprehensive literature review with a suitable structure .

But, how do I actually write the literature review chapter, you ask? We cover that in detail in this video post .

Step 6: Carry out your own research

Once you’ve completed your literature review and have a sound understanding of the existing research, its time to develop your own research (finally!). You’ll design this research specifically so that you can find the answers to your unique research question.

There are two steps here – designing your research strategy and executing on it:

1 – Design your research strategy

The first step is to design your research strategy and craft a methodology chapter . I won’t get into the technicalities of the methodology chapter here, but in simple terms, this chapter is about explaining the “how” of your research. If you recall, the introduction and literature review chapters discussed the “what” and the “why”, so it makes sense that the next point to cover is the “how” –that’s what the methodology chapter is all about.

In this section, you’ll need to make firm decisions about your research design. This includes things like:

• Your research philosophy (e.g. positivism or interpretivism )
• Your overall methodology (e.g. qualitative , quantitative or mixed methods)
• Your data collection strategy (e.g. interviews , focus groups, surveys)
• Your data analysis strategy (e.g. content analysis , correlation analysis, regression)

If these words have got your head spinning, don’t worry! We’ll explain these in plain language in other posts. It’s not essential that you understand the intricacies of research design (yet!). The key takeaway here is that you’ll need to make decisions about how you’ll design your own research, and you’ll need to describe (and justify) your decisions in your methodology chapter.

2 – Execute: Collect and analyse your data

Once you’ve worked out your research design, you’ll put it into action and start collecting your data. This might mean undertaking interviews, hosting an online survey or any other data collection method. Data collection can take quite a bit of time (especially if you host in-person interviews), so be sure to factor sufficient time into your project plan for this. Oftentimes, things don’t go 100% to plan (for example, you don’t get as many survey responses as you hoped for), so bake a little extra time into your budget here.

Once you’ve collected your data, you’ll need to do some data preparation before you can sink your teeth into the analysis. For example:

• If you carry out interviews or focus groups, you’ll need to transcribe your audio data to text (i.e. a Word document).
• If you collect quantitative survey data, you’ll need to clean up your data and get it into the right format for whichever analysis software you use (for example, SPSS, R or STATA).

Once you’ve completed your data prep, you’ll undertake your analysis, using the techniques that you described in your methodology. Depending on what you find in your analysis, you might also do some additional forms of analysis that you hadn’t planned for. For example, you might see something in the data that raises new questions or that requires clarification with further analysis.

The type(s) of analysis that you’ll use depend entirely on the nature of your research and your research questions. For example:

• If your research if exploratory in nature, you’ll often use qualitative analysis techniques .
• If your research is confirmatory in nature, you’ll often use quantitative analysis techniques
• If your research involves a mix of both, you might use a mixed methods approach

Again, if these words have got your head spinning, don’t worry! We’ll explain these concepts and techniques in other posts. The key takeaway is simply that there’s no “one size fits all” for research design and methodology – it all depends on your topic, your research questions and your data. So, don’t be surprised if your study colleagues take a completely different approach to yours.

Step 7: Present your findings

Once you’ve completed your analysis, it’s time to present your findings (finally!). In a dissertation or thesis, you’ll typically present your findings in two chapters – the results chapter and the discussion chapter .

What’s the difference between the results chapter and the discussion chapter?

While these two chapters are similar, the results chapter generally just presents the processed data neatly and clearly without interpretation, while the discussion chapter explains the story the data are telling  – in other words, it provides your interpretation of the results.

For example, if you were researching the factors that influence consumer trust, you might have used a quantitative approach to identify the relationship between potential factors (e.g. perceived integrity and competence of the organisation) and consumer trust. In this case:

• Your results chapter would just present the results of the statistical tests. For example, correlation results or differences between groups. In other words, the processed numbers.
• Your discussion chapter would explain what the numbers mean in relation to your research question(s). For example, Factor 1 has a weak relationship with consumer trust, while Factor 2 has a strong relationship.

Depending on the university and degree, these two chapters (results and discussion) are sometimes merged into one , so be sure to check with your institution what their preference is. Regardless of the chapter structure, this section is about presenting the findings of your research in a clear, easy to understand fashion.

Importantly, your discussion here needs to link back to your research questions (which you outlined in the introduction or literature review chapter). In other words, it needs to answer the key questions you asked (or at least attempt to answer them).

For example, if we look at the sample research topic:

In this case, the discussion section would clearly outline which factors seem to have a noteworthy influence on organisational trust. By doing so, they are answering the overarching question and fulfilling the purpose of the research .

For more information about the results chapter , check out this post for qualitative studies and this post for quantitative studies .

Step 8: The Final Step Draw a conclusion and discuss the implications

Last but not least, you’ll need to wrap up your research with the conclusion chapter . In this chapter, you’ll bring your research full circle by highlighting the key findings of your study and explaining what the implications of these findings are.

What exactly are key findings? The key findings are those findings which directly relate to your original research questions and overall research objectives (which you discussed in your introduction chapter). The implications, on the other hand, explain what your findings mean for industry, or for research in your area.

Sticking with the consumer trust topic example, the conclusion might look something like this:

Key findings

This study set out to identify which factors influence consumer-based trust in British low-cost online equity brokerage firms. The results suggest that the following factors have a large impact on consumer trust:

While the following factors have a very limited impact on consumer trust:

Notably, within the 25-30 age groups, Factors E had a noticeably larger impact, which may be explained by…

Implications

The findings having noteworthy implications for British low-cost online equity brokers. Specifically:

The large impact of Factors X and Y implies that brokers need to consider….

The limited impact of Factor E implies that brokers need to…

As you can see, the conclusion chapter is basically explaining the “what” (what your study found) and the “so what?” (what the findings mean for the industry or research). This brings the study full circle and closes off the document.

Let’s recap – how to write a dissertation or thesis

You’re still with me? Impressive! I know that this post was a long one, but hopefully you’ve learnt a thing or two about how to write a dissertation or thesis, and are now better equipped to start your own research.

To recap, the 8 steps to writing a quality dissertation (or thesis) are as follows:

• Understand what a dissertation (or thesis) is – a research project that follows the research process.
• Find a unique (original) and important research topic
• Craft a convincing dissertation or thesis research proposal
• Write a clear, compelling introduction chapter
• Undertake a thorough review of the existing research and write up a literature review
• Undertake your own research
• Present and interpret your findings

Once you’ve wrapped up the core chapters, all that’s typically left is the abstract , reference list and appendices. As always, be sure to check with your university if they have any additional requirements in terms of structure or content.  

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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20 Comments

thankfull >>>this is very useful

Thank you, it was really helpful

unquestionably, this amazing simplified way of teaching. Really , I couldn’t find in the literature words that fully explicit my great thanks to you. However, I could only say thanks a-lot.

Great to hear that – thanks for the feedback. Good luck writing your dissertation/thesis.

This is the most comprehensive explanation of how to write a dissertation. Many thanks for sharing it free of charge.

Very rich presentation. Thank you

Thanks Derek Jansen|GRADCOACH, I find it very useful guide to arrange my activities and proceed to research!

Thank you so much for such a marvelous teaching .I am so convinced that am going to write a comprehensive and a distinct masters dissertation

It is an amazing comprehensive explanation

This was straightforward. Thank you!

I can say that your explanations are simple and enlightening – understanding what you have done here is easy for me. Could you write more about the different types of research methods specific to the three methodologies: quan, qual and MM. I look forward to interacting with this website more in the future.

Thanks for the feedback and suggestions 🙂

Hello, your write ups is quite educative. However, l have challenges in going about my research questions which is below; *Building the enablers of organisational growth through effective governance and purposeful leadership.*

Very educating.

Just listening to the name of the dissertation makes the student nervous. As writing a top-quality dissertation is a difficult task as it is a lengthy topic, requires a lot of research and understanding and is usually around 10,000 to 15000 words. Sometimes due to studies, unbalanced workload or lack of research and writing skill students look for dissertation submission from professional writers.

Thank you 💕😊 very much. I was confused but your comprehensive explanation has cleared my doubts of ever presenting a good thesis. Thank you.

thank you so much, that was so useful

Hi. Where is the excel spread sheet ark?

could you please help me look at your thesis paper to enable me to do the portion that has to do with the specification

my topic is “the impact of domestic revenue mobilization.

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• 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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Home » Dissertation – Format, Example and Template

Dissertation – Format, Example and Template

Table of Contents

Dissertation

Definition:

Dissertation is a lengthy and detailed academic document that presents the results of original research on a specific topic or question. It is usually required as a final project for a doctoral degree or a master’s degree.

Dissertation Meaning in Research

In Research , a dissertation refers to a substantial research project that students undertake in order to obtain an advanced degree such as a Ph.D. or a Master’s degree.

Dissertation typically involves the exploration of a particular research question or topic in-depth, and it requires students to conduct original research, analyze data, and present their findings in a scholarly manner. It is often the culmination of years of study and represents a significant contribution to the academic field.

Types of Dissertation

Types of Dissertation are as follows:

Empirical Dissertation

An empirical dissertation is a research study that uses primary data collected through surveys, experiments, or observations. It typically follows a quantitative research approach and uses statistical methods to analyze the data.

Non-Empirical Dissertation

A non-empirical dissertation is based on secondary sources, such as books, articles, and online resources. It typically follows a qualitative research approach and uses methods such as content analysis or discourse analysis.

Narrative Dissertation

A narrative dissertation is a personal account of the researcher’s experience or journey. It typically follows a qualitative research approach and uses methods such as interviews, focus groups, or ethnography.

Systematic Literature Review

A systematic literature review is a comprehensive analysis of existing research on a specific topic. It typically follows a qualitative research approach and uses methods such as meta-analysis or thematic analysis.

Case Study Dissertation

A case study dissertation is an in-depth analysis of a specific individual, group, or organization. It typically follows a qualitative research approach and uses methods such as interviews, observations, or document analysis.

Mixed-Methods Dissertation

A mixed-methods dissertation combines both quantitative and qualitative research approaches to gather and analyze data. It typically uses methods such as surveys, interviews, and focus groups, as well as statistical analysis.

How to Write a Dissertation

Here are some general steps to help guide you through the process of writing a dissertation:

• Choose a topic : Select a topic that you are passionate about and that is relevant to your field of study. It should be specific enough to allow for in-depth research but broad enough to be interesting and engaging.
• Conduct research : Conduct thorough research on your chosen topic, utilizing a variety of sources, including books, academic journals, and online databases. Take detailed notes and organize your information in a way that makes sense to you.
• Create an outline : Develop an outline that will serve as a roadmap for your dissertation. The outline should include the introduction, literature review, methodology, results, discussion, and conclusion.
• Write the introduction: The introduction should provide a brief overview of your topic, the research questions, and the significance of the study. It should also include a clear thesis statement that states your main argument.
• Write the literature review: The literature review should provide a comprehensive analysis of existing research on your topic. It should identify gaps in the research and explain how your study will fill those gaps.
• Write the methodology: The methodology section should explain the research methods you used to collect and analyze data. It should also include a discussion of any limitations or weaknesses in your approach.
• Write the results: The results section should present the findings of your research in a clear and organized manner. Use charts, graphs, and tables to help illustrate your data.
• Write the discussion: The discussion section should interpret your results and explain their significance. It should also address any limitations of the study and suggest areas for future research.
• Write the conclusion: The conclusion should summarize your main findings and restate your thesis statement. It should also provide recommendations for future research.
• Edit and revise: Once you have completed a draft of your dissertation, review it carefully to ensure that it is well-organized, clear, and free of errors. Make any necessary revisions and edits before submitting it to your advisor for review.

Dissertation Format

The format of a dissertation may vary depending on the institution and field of study, but generally, it follows a similar structure:

• Title Page: This includes the title of the dissertation, the author’s name, and the date of submission.
• Abstract : A brief summary of the dissertation’s purpose, methods, and findings.
• Table of Contents: A list of the main sections and subsections of the dissertation, along with their page numbers.
• Introduction : A statement of the problem or research question, a brief overview of the literature, and an explanation of the significance of the study.
• Literature Review : A comprehensive review of the literature relevant to the research question or problem.
• Methodology : A description of the methods used to conduct the research, including data collection and analysis procedures.
• Results : A presentation of the findings of the research, including tables, charts, and graphs.
• Discussion : A discussion of the implications of the findings, their significance in the context of the literature, and limitations of the study.
• Conclusion : A summary of the main points of the study and their implications for future research.
• References : A list of all sources cited in the dissertation.
• Appendices : Additional materials that support the research, such as data tables, charts, or transcripts.

Dissertation Outline

Dissertation Outline is as follows:

Title Page:

• Title of dissertation
• Author name
• Institutional affiliation
• Date of submission
• Brief summary of the dissertation’s research problem, objectives, methods, findings, and implications
• Usually around 250-300 words

Table of Contents:

• List of chapters and sections in the dissertation, with page numbers for each

I. Introduction

• Background and context of the research
• Research problem and objectives
• Significance of the research

II. Literature Review

• Overview of existing literature on the research topic
• Identification of gaps in the literature
• Theoretical framework and concepts

III. Methodology

• Research design and methods used
• Data collection and analysis techniques
• Ethical considerations

IV. Results

• Presentation and analysis of data collected
• Findings and outcomes of the research
• Interpretation of the results

V. Discussion

• Discussion of the results in relation to the research problem and objectives
• Evaluation of the research outcomes and implications
• Suggestions for future research

VI. Conclusion

• Summary of the research findings and outcomes
• Implications for the research topic and field
• Limitations and recommendations for future research

VII. References

• List of sources cited in the dissertation

VIII. Appendices

• Additional materials that support the research, such as tables, figures, or questionnaires.

Example of Dissertation

Here is an example Dissertation for students:

Title : Exploring the Effects of Mindfulness Meditation on Academic Achievement and Well-being among College Students

This dissertation aims to investigate the impact of mindfulness meditation on the academic achievement and well-being of college students. Mindfulness meditation has gained popularity as a technique for reducing stress and enhancing mental health, but its effects on academic performance have not been extensively studied. Using a randomized controlled trial design, the study will compare the academic performance and well-being of college students who practice mindfulness meditation with those who do not. The study will also examine the moderating role of personality traits and demographic factors on the effects of mindfulness meditation.

Chapter Outline:

Chapter 1: Introduction

• Background and rationale for the study
• Research questions and objectives
• Significance of the study
• Overview of the dissertation structure

Chapter 2: Literature Review

• Definition and conceptualization of mindfulness meditation
• Theoretical framework of mindfulness meditation
• Empirical research on mindfulness meditation and academic achievement
• Empirical research on mindfulness meditation and well-being
• The role of personality and demographic factors in the effects of mindfulness meditation

Chapter 3: Methodology

• Research design and hypothesis
• Participants and sampling method
• Intervention and procedure
• Measures and instruments
• Data analysis method

Chapter 4: Results

• Descriptive statistics and data screening
• Analysis of main effects
• Analysis of moderating effects
• Post-hoc analyses and sensitivity tests

Chapter 5: Discussion

• Summary of findings
• Implications for theory and practice
• Limitations and directions for future research
• Conclusion and contribution to the literature

Chapter 6: Conclusion

• Recap of the research questions and objectives
• Summary of the key findings
• Contribution to the literature and practice
• Implications for policy and practice
• Final thoughts and recommendations.

References :

List of all the sources cited in the dissertation

Appendices :

Additional materials such as the survey questionnaire, interview guide, and consent forms.

Note : This is just an example and the structure of a dissertation may vary depending on the specific requirements and guidelines provided by the institution or the supervisor.

How Long is a Dissertation

The length of a dissertation can vary depending on the field of study, the level of degree being pursued, and the specific requirements of the institution. Generally, a dissertation for a doctoral degree can range from 80,000 to 100,000 words, while a dissertation for a master’s degree may be shorter, typically ranging from 20,000 to 50,000 words. However, it is important to note that these are general guidelines and the actual length of a dissertation can vary widely depending on the specific requirements of the program and the research topic being studied. It is always best to consult with your academic advisor or the guidelines provided by your institution for more specific information on dissertation length.

Applications of Dissertation

Here are some applications of a dissertation:

• Advancing the Field: Dissertations often include new research or a new perspective on existing research, which can help to advance the field. The results of a dissertation can be used by other researchers to build upon or challenge existing knowledge, leading to further advancements in the field.
• Career Advancement: Completing a dissertation demonstrates a high level of expertise in a particular field, which can lead to career advancement opportunities. For example, having a PhD can open doors to higher-paying jobs in academia, research institutions, or the private sector.
• Publishing Opportunities: Dissertations can be published as books or journal articles, which can help to increase the visibility and credibility of the author’s research.
• Personal Growth: The process of writing a dissertation involves a significant amount of research, analysis, and critical thinking. This can help students to develop important skills, such as time management, problem-solving, and communication, which can be valuable in both their personal and professional lives.
• Policy Implications: The findings of a dissertation can have policy implications, particularly in fields such as public health, education, and social sciences. Policymakers can use the research to inform decision-making and improve outcomes for the population.

When to Write a Dissertation

Here are some situations where writing a dissertation may be necessary:

• Pursuing a Doctoral Degree: Writing a dissertation is usually a requirement for earning a doctoral degree, so if you are interested in pursuing a doctorate, you will likely need to write a dissertation.
• Conducting Original Research : Dissertations require students to conduct original research on a specific topic. If you are interested in conducting original research on a topic, writing a dissertation may be the best way to do so.
• Advancing Your Career: Some professions, such as academia and research, may require individuals to have a doctoral degree. Writing a dissertation can help you advance your career by demonstrating your expertise in a particular area.
• Contributing to Knowledge: Dissertations are often based on original research that can contribute to the knowledge base of a field. If you are passionate about advancing knowledge in a particular area, writing a dissertation can help you achieve that goal.
• Meeting Academic Requirements : If you are a graduate student, writing a dissertation may be a requirement for completing your program. Be sure to check with your academic advisor to determine if this is the case for you.

Purpose of Dissertation

some common purposes of a dissertation include:

• To contribute to the knowledge in a particular field : A dissertation is often the culmination of years of research and study, and it should make a significant contribution to the existing body of knowledge in a particular field.
• To demonstrate mastery of a subject: A dissertation requires extensive research, analysis, and writing, and completing one demonstrates a student’s mastery of their subject area.
• To develop critical thinking and research skills : A dissertation requires students to think critically about their research question, analyze data, and draw conclusions based on evidence. These skills are valuable not only in academia but also in many professional fields.
• To demonstrate academic integrity: A dissertation must be conducted and written in accordance with rigorous academic standards, including ethical considerations such as obtaining informed consent, protecting the privacy of participants, and avoiding plagiarism.
• To prepare for an academic career: Completing a dissertation is often a requirement for obtaining a PhD and pursuing a career in academia. It can demonstrate to potential employers that the student has the necessary skills and experience to conduct original research and make meaningful contributions to their field.
• To develop writing and communication skills: A dissertation requires a significant amount of writing and communication skills to convey complex ideas and research findings in a clear and concise manner. This skill set can be valuable in various professional fields.
• To demonstrate independence and initiative: A dissertation requires students to work independently and take initiative in developing their research question, designing their study, collecting and analyzing data, and drawing conclusions. This demonstrates to potential employers or academic institutions that the student is capable of independent research and taking initiative in their work.
• To contribute to policy or practice: Some dissertations may have a practical application, such as informing policy decisions or improving practices in a particular field. These dissertations can have a significant impact on society, and their findings may be used to improve the lives of individuals or communities.
• To pursue personal interests: Some students may choose to pursue a dissertation topic that aligns with their personal interests or passions, providing them with the opportunity to delve deeper into a topic that they find personally meaningful.

Advantage of Dissertation

Some advantages of writing a dissertation include:

• Developing research and analytical skills: The process of writing a dissertation involves conducting extensive research, analyzing data, and presenting findings in a clear and coherent manner. This process can help students develop important research and analytical skills that can be useful in their future careers.
• Demonstrating expertise in a subject: Writing a dissertation allows students to demonstrate their expertise in a particular subject area. It can help establish their credibility as a knowledgeable and competent professional in their field.
• Contributing to the academic community: A well-written dissertation can contribute new knowledge to the academic community and potentially inform future research in the field.
• Improving writing and communication skills : Writing a dissertation requires students to write and present their research in a clear and concise manner. This can help improve their writing and communication skills, which are essential for success in many professions.
• Increasing job opportunities: Completing a dissertation can increase job opportunities in certain fields, particularly in academia and research-based positions.

About the author

Muhammad Hassan

Researcher, Academic Writer, Web developer

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Difference between a research paper, dissertation & thesis

When it comes to writing academic papers, students should have the right skills if they must succeed. Whether it is doing a weekly essay assignment, crafting a term paper, or doing research, the best learners are those who have mastered the art of literary composition. You should also note that understanding how each school paper differs from the other puts you ahead of the pack. Most of the schools, universities and institutions require you to undertake research at some point or another in form of coursework .

Often, students mistake research for term papers or thesis for dissertations. The worst-case scenario is when instead of writing a thesis; you end up with a dissertation paper. Such is an occurrence that often denies students marks. And so, the big question we want to answer in this post is what the differences between research, dissertation, and thesis are? Keep reading to learn more.

First things first note that variations between different types of academic papers could be in the form of writing style , definition, presentation of arguments, not to mention the purpose of writing and level of academia.  You should not expect high school students, for example, to partake in thesis writing. But when it comes to writing research papers, it can happen at any level of academia right from high school through college and university.

Note: There are differences in how these terminologies are used. In few countries they are used interchangeably, while in other countries thesis is related to bachelor’s or master’s degree course and dissertation is used in the context of a doctorate degree, whereas in some countries the reverse is true. For example, in Indian context, PhD students are required to submit a “thesis” whereas M. Phil students are required to submit a dissertation. Thesis is considered to be much longer form of research which is opposite in case of USA.

Differences based on the definition

Definitive differences between academic papers simplify things for a college newbie yet to write his or her academic paper. Now, on defining the thesis, research and dissertation, the following are worth noting:

• A research paper refers to a piece of literary composition, often a class requirement. The most notable aspect of research papers is that before you craft them, you must gather knowledge independently. After collecting data and information, students then put together findings in a descriptive format. Learners must also present their arguments based on their evaluation of a subject under study. A good research paper opens the gates to advanced academic writing which will involve the implementation of findings.
• A dissertation is a paper that students write as a requirement for the conferment of a diploma or degree. In some countries, Ph.D. students also write dissertations.
• A thesis is a paper students craft as a requirement for a degree at college or university level. You do realize that all the three types of academic papers lead to something, often an academic qualification that would see one earn a degree or get admitted to the next level of academia.

Length of paper and methodology

While the methodology of writing these papers is similar, often constituting sections such as introduction, abstract, literature review, research method, presentation/finings, discussions, conclusion and recommendations, the length of each paper does vary. Research papers and dissertations are generally long. However, thesis papers tend to be short hence requiring less time to write. Dissertations and research require a comprehensive study of a study and gathering information/data. You, therefore, spend more time on them before and during writing. You may even use an editing service to help you research, write, and proofread your dissertation properly.

Differences based on knowledge inference and hypothesis

A hypothesis is an educated guess. Before you conduct a study, assumptions have to be made that something will turn out in some way. Most importantly, how the outcome will impact a population informs the construction of a hypothesis/thesis statement. In research and dissertation writing, students must exhibit a rigorous understanding of a subject based on a study. It is on this premise that they must come up with/infer a meaningful conclusion. However, when writing thesis papers, the formulation of a hypothesis comes after researching and writing on a subject.

Differences based on the approach

How students go about crafting research, dissertation and thesis is another way of differentiating the three papers. In writing research and dissertation papers, students must use existing pieces of literature to back their findings. However, thesis papers more often rely on existing research work to prove a point. You can, for example, sample different research papers on climate change to prove your study on the same. Ostensibly, you are using existing and published academic papers to ascertain that phenomena or a problem exist.

Mode of publication and utilization

You should also note that academic papers exhibit differences based on the reason for which they get published and also how people use them. Dissertation papers are like complete and newly published books given their voluminous nature. You could refer to yours as an academic book. It makes you a published author. However, thesis and research work are like articles that shed light on a subject but not as comprehensively as dissertations.

Differences based on the level of academia

While students can write research papers at any level, they are most common at the undergraduate level. Completion of a research paper often leads to the conferment of an undergraduate degree. And when it comes to writing dissertation papers, the bargain is qualifying for a master’s degree, thusly; postgraduate, Mphil or MBA.  It means if you are not writing a dissertation to obtain a postgraduate degree, you do so as a means of enrolling in a postgraduate program. Thesis papers lead to the conferment of a Ph.D. degree or a doctorate as some scholars call it. Students who write thesis papers do so within the last two years of their academic life.

Final Thoughts

Many factors distinguish academic papers. But regardless of the methodology or purpose of these papers, the most important thing is that students showcase their literary skills. Moreover, academic paper tests the knowledge of students on different issues and subjects. Whether it is writing about how past events led to present-day situations or how human activities will lead to something happening in the future, knowledge dispensation helps societies grow.

In the interest of time, research work involved in crafting academic papers is meant to unearth critical findings on a subject and provide solutions to an existing problem. As a rule of the thumb, students who write research, dissertation or thesis papers must demonstrate their understanding of the society and problems that bedevil it. It is through doing so that recommendations for solving a problem become trustworthy, dependable, acceptable and applicable. Most importantly, learners must meet a set academic threshold before writing the above papers.

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Open Access Theses and Dissertations

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About OATD.org

OATD.org aims to be the best possible resource for finding open access graduate theses and dissertations published around the world. Metadata (information about the theses) comes from over 1100 colleges, universities, and research institutions . OATD currently indexes 7,241,108 theses and dissertations.

About OATD (our FAQ) .

Visual OATD.org

We’re happy to present several data visualizations to give an overall sense of the OATD.org collection by county of publication, language, and field of study.

You may also want to consult these sites to search for other theses:

• Google Scholar
• NDLTD , the Networked Digital Library of Theses and Dissertations. NDLTD provides information and a search engine for electronic theses and dissertations (ETDs), whether they are open access or not.
• Proquest Theses and Dissertations (PQDT), a database of dissertations and theses, whether they were published electronically or in print, and mostly available for purchase. Access to PQDT may be limited; consult your local library for access information.

Harvard University Theses, Dissertations, and Prize Papers

The Harvard University Archives ’ collection of theses, dissertations, and prize papers document the wide range of academic research undertaken by Harvard students over the course of the University’s history.

Beyond their value as pieces of original research, these collections document the history of American higher education, chronicling both the growth of Harvard as a major research institution as well as the development of numerous academic fields. They are also an important source of biographical information, offering insight into the academic careers of the authors.

Spanning from the ‘theses and quaestiones’ of the 17th and 18th centuries to the current yearly output of student research, they include both the first Harvard Ph.D. dissertation (by William Byerly, Ph.D . 1873) and the dissertation of the first woman to earn a doctorate from Harvard ( Lorna Myrtle Hodgkinson , Ed.D. 1922).

Other highlights include:

• The collection of Mathematical theses, 1782-1839
• The 1895 Ph.D. dissertation of W.E.B. Du Bois, The suppression of the African slave trade in the United States, 1638-1871
• Ph.D. dissertations of astronomer Cecilia Payne-Gaposchkin (Ph.D. 1925) and physicist John Hasbrouck Van Vleck (Ph.D. 1922)
• Undergraduate honors theses of novelist John Updike (A.B. 1954), filmmaker Terrence Malick (A.B. 1966),  and U.S. poet laureate Tracy Smith (A.B. 1994)
• Undergraduate prize papers and dissertations of philosophers Ralph Waldo Emerson (A.B. 1821), George Santayana (Ph.D. 1889), and W.V. Quine (Ph.D. 1932)
• Undergraduate honors theses of U.S. President John F. Kennedy (A.B. 1940) and Chief Justice John Roberts (A.B. 1976)

What does a prize-winning thesis look like?

If you're a Harvard undergraduate writing your own thesis, it can be helpful to review recent prize-winning theses. The Harvard University Archives has made available for digital lending all of the Thomas Hoopes Prize winners from the 2019-2021 academic years.

Accessing These Materials

How to access materials at the Harvard University Archives

How to find and request dissertations, in person or virtually

How to find and request undergraduate honors theses

How to find and request Thomas Temple Hoopes Prize papers

How to find and request Bowdoin Prize papers

• email: Email
• Phone number 617-495-2461

Related Collections

Harvard faculty personal and professional archives, harvard student life collections: arts, sports, politics and social life, access materials at the harvard university archives.

How to Write a Research Paper 

• Smodin Editorial Team
• Updated: May 17, 2024

Most students hate writing research papers. The process can often feel long, tedious, and sometimes outright boring. Nevertheless, these assignments are vital to a student’s academic journey. Want to learn how to write a research paper that captures the depth of the subject and maintains the reader’s interest? If so, this guide is for you.

Today, we’ll show you how to assemble a well-organized research paper to help you make the grade. You can transform any topic into a compelling research paper with a thoughtful approach to your research and a persuasive argument.

In this guide, we’ll provide seven simple but practical tips to help demystify the process and guide you on your way. We’ll also explain how AI tools can expedite the research and writing process so you can focus on critical thinking.

By the end of this article, you’ll have a clear roadmap for tackling these essays. You will also learn how to tackle them quickly and efficiently. With time and dedication, you’ll soon master the art of research paper writing.

Ready to get started?

What Is a Research Paper?

A research paper is a comprehensive essay that gives a detailed analysis, interpretation, or argument based on your own independent research. In higher-level academic settings, it goes beyond a simple summarization and includes a deep inquiry into the topic or topics.

The term “research paper” is a broad term that can be applied to many different forms of academic writing. The goal is to combine your thoughts with the findings from peer-reviewed scholarly literature.

By the time your essay is done, you should have provided your reader with a new perspective or challenged existing findings. This demonstrates your mastery of the subject and contributes to ongoing scholarly debates.

7 Tips for Writing a Research Paper

Often, getting started is the most challenging part of a research paper. While the process can seem daunting, breaking it down into manageable steps can make it easier to manage. The following are seven tips for getting your ideas out of your head and onto the page.

1. Understand Your Assignment

It may sound simple, but the first step in writing a successful research paper is to read the assignment. Sit down, take a few moments of your time, and go through the instructions so you fully understand your assignment.

Misinterpreting the assignment can not only lead to a significant waste of time but also affect your grade. No matter how patient your teacher or professor may be, ignoring basic instructions is often inexcusable.

If you read the instructions and are still confused, ask for clarification before you start writing. If that’s impossible, you can use tools like Smodin’s AI chat to help. Smodin can help highlight critical requirements that you may overlook.

This initial investment ensures that all your future efforts will be focused and efficient. Remember, thinking is just as important as actually writing the essay, and it can also pave the wave for a smoother writing process.

2. Gather Research Materials

Now comes the fun part: doing the research. As you gather research materials, always use credible sources, such as academic journals or peer-reviewed papers. Only use search engines that filter for accredited sources and academic databases so you can ensure your information is reliable.

To optimize your time, you must learn to master the art of skimming. If a source seems relevant and valuable, save it and review it later. The last thing you want to do is waste time on material that won’t make it into the final paper.

To speed up the process even more, consider using Smodin’s AI summarizer . This tool can help summarize large texts, highlighting key information relevant to your topic. By systematically gathering and filing research materials early in the writing process, you build a strong foundation for your thesis.

3. Write Your Thesis

Creating a solid thesis statement is the most important thing you can do to bring structure and focus to your research paper. Your thesis should express the main point of your argument in one or two simple sentences. Remember, when you create your thesis, you’re setting the tone and direction for the entire paper.

Of course, you can’t just pull a winning thesis out of thin air. Start by brainstorming potential thesis ideas based on your preliminary research. And don’t overthink things; sometimes, the most straightforward ideas are often the best.

You want a thesis that is specific enough to be manageable within the scope of your paper but broad enough to allow for a unique discussion. Your thesis should challenge existing expectations and provide the reader with fresh insight into the topic. Use your thesis to hook the reader in the opening paragraph and keep them engaged until the very last word.

4. Write Your Outline

An outline is an often overlooked but essential tool for organizing your thoughts and structuring your paper. Many students skip the outline because it feels like doing double work, but a strong outline will save you work in the long run.

Here’s how to effectively structure your outline.

• Introduction: List your thesis statement and outline the main questions your essay will answer.
• Literature Review: Outline the key literature you plan to discuss and explain how it will relate to your thesis.
• Methodology: Explain the research methods you will use to gather and analyze the information.
• Discussion: Plan how you will interpret the results and their implications for your thesis.
• Conclusion: Summarize the content above to elucidate your thesis fully.

To further streamline this process, consider using Smodin’s Research Writer. This tool offers a feature that allows you to generate and tweak an outline to your liking based on the initial input you provide. You can adjust this outline to fit your research findings better and ensure that your paper remains well-organized and focused.

5. Write a Rough Draft

Once your outline is in place, you can begin the writing process. Remember, when you write a rough draft, it isn’t meant to be perfect. Instead, use it as a working document where you can experiment with and rearrange your arguments and evidence.

Don’t worry too much about grammar, style, or syntax as you write your rough draft. Focus on getting your ideas down on paper and flush out your thesis arguments. You can always refine and rearrange the content the next time around.

Follow the basic structure of your outline but with the freedom to explore different ways of expressing your thoughts. Smodin’s Essay Writer offers a powerful solution for those struggling with starting or structuring their drafts.

After you approve the outline, Smodin can generate an essay based on your initial inputs. This feature can help you quickly create a comprehensive draft, which you can then review and refine. You can even use the power of AI to create multiple rough drafts from which to choose.

6. Add or Subtract Supporting Evidence

Once you have a rough draft, but before you start the final revision, it’s time to do a little cleanup. In this phase, you need to review all your supporting evidence. You want to ensure that there is nothing redundant and that you haven’t overlooked any crucial details.

Many students struggle to make the required word count for an essay and resort to padding their writing with redundant statements. Instead of adding unnecessary content, focus on expanding your analysis to provide deeper insights.

A good essay, regardless of the topic or format, needs to be streamlined. It should convey clear, convincing, relevant information supporting your thesis. If you find some information doesn’t do that, consider tweaking your sources.

Include a variety of sources, including studies, data, and quotes from scholars or other experts. Remember, you’re not just strengthening your argument but demonstrating the depth of your research.

If you want comprehensive feedback on your essay without going to a writing center or pestering your professor, use Smodin. The AI Chat can look at your draft and offer suggestions for improvement.

7. Revise, Cite, and Submit

The final stages of crafting a research paper involve revision, citation, and final review. You must ensure your paper is polished, professionally presented, and plagiarism-free. Of course, integrating Smodin’s AI tools can significantly streamline this process and enhance the quality of your final submission.

Start by using Smodin’s Rewriter tool. This AI-powered feature can help rephrase and refine your draft to improve overall readability. If a specific section of your essay just “doesn’t sound right,” the AI can suggest alternative sentence structures and word choices.

Proper citation is a must for all academic papers. Thankfully, thanks to Smodin’s Research Paper app, this once tedious process is easier than ever. The AI ensures all sources are accurately cited according to the required style guide (APA, MLA, Chicago, etc.).

Plagiarism Checker:

All students need to realize that accidental plagiarism can happen. That’s why using a Plagiarism Checker to scan your essay before you submit it is always useful. Smodin’s Plagiarism Checker can highlight areas of concern so you can adjust accordingly.

Final Submission

After revising, rephrasing, and ensuring all citations are in order, use Smodin’s AI Content Detector to give your paper one last review. This tool can help you analyze your paper’s overall quality and readability so you can make any final tweaks or improvements.

Mastering Research Papers

Mastering the art of the research paper cannot be overstated, whether you’re in high school, college, or postgraduate studies. You can confidently prepare your research paper for submission by leveraging the AI tools listed above.

Research papers help refine your abilities to think critically and write persuasively. The skills you develop here will serve you well beyond the walls of the classroom. Communicating complex ideas clearly and effectively is one of the most powerful tools you can possess.

With the advancements of AI tools like Smodin , writing a research paper has become more accessible than ever before. These technologies streamline the process of organizing, writing, and revising your work. Write with confidence, knowing your best work is yet to come!

Innovative Statistics Project Ideas for Insightful Analysis

Table of contents

• 1.1 AP Statistics Topics for Project
• 1.2 Statistics Project Topics for High School Students
• 1.3 Statistical Survey Topics
• 1.4 Statistical Experiment Ideas
• 1.5 Easy Stats Project Ideas
• 1.6 Business Ideas for Statistics Project
• 1.7 Socio-Economic Easy Statistics Project Ideas
• 1.8 Experiment Ideas for Statistics and Analysis
• 2 Conclusion: Navigating the World of Data Through Statistics

Diving into the world of data, statistics presents a unique blend of challenges and opportunities to uncover patterns, test hypotheses, and make informed decisions. It is a fascinating field that offers many opportunities for exploration and discovery. This article is designed to inspire students, educators, and statistics enthusiasts with various project ideas. We will cover:

• Challenging concepts suitable for advanced placement courses.
• Accessible ideas that are engaging and educational for younger students.
• Ideas for conducting surveys and analyzing the results.
• Topics that explore the application of statistics in business and socio-economic areas.

Each category of topics for the statistics project provides unique insights into the world of statistics, offering opportunities for learning and application. Let’s dive into these ideas and explore the exciting world of statistical analysis.

Top Statistics Project Ideas for High School

Statistics is not only about numbers and data; it’s a unique lens for interpreting the world. Ideal for students, educators, or anyone with a curiosity about statistical analysis, these project ideas offer an interactive, hands-on approach to learning. These projects range from fundamental concepts suitable for beginners to more intricate studies for advanced learners. They are designed to ignite interest in statistics by demonstrating its real-world applications, making it accessible and enjoyable for people of all skill levels.

Need help with statistics project? Get your paper written by a professional writer Get Help Reviews.io 4.9/5

AP Statistics Topics for Project

• Analyzing Variance in Climate Data Over Decades.
• The Correlation Between Economic Indicators and Standard of Living.
• Statistical Analysis of Voter Behavior Patterns.
• Probability Models in Sports: Predicting Outcomes.
• The Effectiveness of Different Teaching Methods: A Statistical Study.
• Analysis of Demographic Data in Public Health.
• Time Series Analysis of Stock Market Trends.
• Investigating the Impact of Social Media on Academic Performance.
• Survival Analysis in Clinical Trial Data.
• Regression Analysis on Housing Prices and Market Factors.

Statistics Project Topics for High School Students

• The Mathematics of Personal Finance: Budgeting and Spending Habits.
• Analysis of Class Performance: Test Scores and Study Habits.
• A Statistical Comparison of Local Public Transportation Options.
• Survey on Dietary Habits and Physical Health Among Teenagers.
• Analyzing the Popularity of Various Music Genres in School.
• The Impact of Sleep on Academic Performance: A Statistical Approach.
• Statistical Study on the Use of Technology in Education.
• Comparing Athletic Performance Across Different Sports.
• Trends in Social Media Usage Among High School Students.
• The Effect of Part-Time Jobs on Student Academic Achievement.

Statistical Survey Topics

• Public Opinion on Environmental Conservation Efforts.
• Consumer Preferences in the Fast Food Industry.
• Attitudes Towards Online Learning vs. Traditional Classroom Learning.
• Survey on Workplace Satisfaction and Productivity.
• Public Health: Attitudes Towards Vaccination.
• Trends in Mobile Phone Usage and Preferences.
• Community Response to Local Government Policies.
• Consumer Behavior in Online vs. Offline Shopping.
• Perceptions of Public Safety and Law Enforcement.
• Social Media Influence on Political Opinions.

Statistical Experiment Ideas

• The Effect of Light on Plant Growth.
• Memory Retention: Visual vs. Auditory Information.
• Caffeine Consumption and Cognitive Performance.
• The Impact of Exercise on Stress Levels.
• Testing the Efficacy of Natural vs. Chemical Fertilizers.
• The Influence of Color on Mood and Perception.
• Sleep Patterns: Analyzing Factors Affecting Sleep Quality.
• The Effectiveness of Different Types of Water Filters.
• Analyzing the Impact of Room Temperature on Concentration.
• Testing the Strength of Different Brands of Batteries.

Easy Stats Project Ideas

• Average Daily Screen Time Among Students.
• Analyzing the Most Common Birth Months.
• Favorite School Subjects Among Peers.
• Average Time Spent on Homework Weekly.
• Frequency of Public Transport Usage.
• Comparison of Pet Ownership in the Community.
• Favorite Types of Movies or TV Shows.
• Daily Water Consumption Habits.
• Common Breakfast Choices and Their Nutritional Value.
• Steps Count: A Week-Long Study.

Business Ideas for Statistics Project

• Analyzing Customer Satisfaction in Retail Stores.
• Market Analysis of a New Product Launch.
• Employee Performance Metrics and Organizational Success.
• Sales Data Analysis for E-commerce Websites.
• Impact of Advertising on Consumer Buying Behavior.
• Analysis of Supply Chain Efficiency.
• Customer Loyalty and Retention Strategies.
• Trend Analysis in Social Media Marketing.
• Financial Risk Assessment in Investment Decisions.
• Market Segmentation and Targeting Strategies.

Socio-Economic Easy Statistics Project Ideas

• Income Inequality and Its Impact on Education.
• The Correlation Between Unemployment Rates and Crime Levels.
• Analyzing the Effects of Minimum Wage Changes.
• The Relationship Between Public Health Expenditure and Population Health.
• Demographic Analysis of Housing Affordability.
• The Impact of Immigration on Local Economies.
• Analysis of Gender Pay Gap in Different Industries.
• Statistical Study of Homelessness Causes and Solutions.
• Education Levels and Their Impact on Job Opportunities.
• Analyzing Trends in Government Social Spending.

Experiment Ideas for Statistics and Analysis

• Multivariate Analysis of Global Climate Change Data.
• Time-Series Analysis in Predicting Economic Recessions.
• Logistic Regression in Medical Outcome Prediction.
• Machine Learning Applications in Statistical Modeling.
• Network Analysis in Social Media Data.
• Bayesian Analysis of Scientific Research Data.
• The Use of Factor Analysis in Psychology Studies.
• Spatial Data Analysis in Geographic Information Systems (GIS).
• Predictive Analysis in Customer Relationship Management (CRM).
• Cluster Analysis in Market Research.

Conclusion: Navigating the World of Data Through Statistics

In this exploration of good statistics project ideas, we’ve ventured through various topics, from the straightforward to the complex, from personal finance to global climate change. These ideas are gateways to understanding the world of data and statistics, and platforms for cultivating critical thinking and analytical skills. Whether you’re a high school student, a college student, or a professional, engaging in these projects can deepen your appreciation of how statistics shapes our understanding of the world around us. These projects encourage exploration, inquiry, and a deeper engagement with the world of numbers, trends, and patterns – the essence of statistics.

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Can ‘forever’ chemicals become less so this senior thesis works toward smarter cleanup of pfas..

By Molly Sharlach

May 20, 2024

For her senior thesis, Amélie Lemay worked with Ian Bourg, an associate professor of civil and environmental engineering and the High Meadows Environmental Institute. She developed complex simulations of how PFAS molecules, a critical class of environmental contaminants, move and interact at the interface of water and air. Photos by Sameer A. Khan/Fotobuddy

The class of chemicals known as PFAS — used in firefighting foams, some nonstick cookware, and many other products — can resist heat and repel water. Their chemical bonds are hard to break, and they persist in water sources for decades.

Exposure to them has been associated with cancers, “impacts to the liver and heart, and immune and developmental damage to infants and children,” according to the Environmental Protection Agency, which recently set national limits for PFAS in drinking water.

For her thesis research, Princeton senior Amélie Lemay has crafted computer simulations that could one day help lead the way to removing PFAS pollution from the environment.

Lemay, a civil and environmental engineering major, used simulations to investigate how seven types of molecules behave above bodies of water, where the water meets the air. She modeled their tendencies to mix with water or stick to the water-air boundary, and probed how mixtures of PFAS molecules interact — mimicking the messy reality of contaminated water.

Detailed knowledge of this chemistry could be key to understanding how remediation methods will work in settings like water treatment plants. Over the next few years, utilities across the United States will need to find effective ways to remove PFAS (per- and polyfluoroalkyl substances) from drinking water to comply with the EPA limits.

“Most of our drinking water treatment plants are not set up to deal with these compounds,” said Lemay. “This type of research can eventually lead to better ways to be able to take PFAS out of water.”

Lemay, of Wynnewood, Pennsylvania, came to Princeton with aspirations of using engineering to address environmental challenges. But using computer simulations to understand pollution was not part of her plan.

The summer after her first year, in 2021, Lemay secured internship support from Princeton’s High Meadows Environmental Institute to conduct field work with associate professor Ian Bourg on how rocks weather in the Princeton area and in the French Alps — research with implications for soil nutrients and atmospheric CO2 forecasting.

But COVID-19 travel restrictions were still in place that summer, so Bourg worked remotely with Lemay and several other students to set up simulations exploring the behavior of pollutants ranging from PFAS to anti-inflammatory drugs to insecticides.

“I actually ended up really liking this alternative project, and I think it’s even better suited for me than the original project would have been,” said Lemay, who earned certificates in statistics and machine learning and sustainable energy .

The research was an excellent opportunity for Lemay to build her computer coding skills and learn the intricacies of molecular dynamics simulation software.

“When I first started with Professor Bourg, he had to walk me through step by step how to create a file” simulating a single chemical compound, Lemay said. Over time, she learned to add more complexity, accounting for variables like salinity and surface tension. Now the work is “like second nature.”

The summer project was a new direction in the lab’s research. Bourg, an associate professor of civil and environmental engineering and the High Meadows Environmental Institute, said he was learning along with the students. He quickly realized that he could rely on Lemay: “She’s been thinking like a grad student since the very beginning, in terms of being super conscientious and questioning the way we do things,” said Bourg.

Lemay and Ethan Sontarp, a geosciences major, continued the project as research assistants in Bourg’s group for the next two years. Eventually, they modeled the behavior of more than 80 organic pollutants at the water-air interface.

Lemay and Sontarp were co-first authors of a 2023 paper reporting the results in the journal Environmental Science and Technology. The article has been downloaded more than 2,000 times and is Bourg’s most-read research paper from last year — a testament to its value as a resource for researchers looking to improve the tracking and remediation of pollutants, said Bourg.

In her junior year, Lemay conducted independent work with Professor Barry Rand , who studies the properties of new materials for solar cells, analyzing factors that influence the adoption of rooftop solar energy. She published this analysis last year in the journal Energy Policy.

For her senior thesis with Bourg, she developed complex simulations of how multiple PFAS molecules move and interact at the interface of water and air. Her results have revealed that the contaminants’ movements are not limited only by physical space but also by complex charge interactions among neighboring PFAS molecules.

Lemay is now submitting this work for scientific publication. The simulations are a powerful way to understand how pollutants move in the environment, potentially helping to explain how rain interacts with contaminants, and why sea spray and lake spray aerosols are an important source of PFAS exposure in coastal communities. Lemay hopes this understanding can inform strategies to clean up PFAS pollution.

Lemay turned to engineering in high school, when she took part in a summer research program on biomolecular engineering. “In science, you’re seeking to uncover the unknown, which is very important,” she said. “But I found that the problem-solving and design aspects of engineering really appealed to me. I loved how practical and pragmatic the applications were.”

After nearly three years of research at Princeton, Lemay has gained comfort with the uncertainties of the process. “If you pursue something, and you don’t fully understand what the data are showing you at first — that used to be distressing to me,” she said. “But I’ve come to realize that it’s part of the process. You’re trying to do something that’s never been done before. No one has the right answer.”

This summer, Lemay will pursue a project advised by Professor Mark Zondlo analyzing electric vehicle use and neighborhood-level air pollution.

In the fall, she will begin a Ph.D. program in civil and environmental engineering at the Massachusetts Institute of Technology. She’s interested in using computational methods to design chemicals for programmed degradation, to prevent problems with environmental contamination in the future.

“I think Princeton’s focus on undergraduate research really sets this institution apart,” said Lemay. “I’m grateful to have had the chance to work with multiple mentors who have shown me … how to design solutions and search for knowledge, and then share that with the greater community.”

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• 09 May 2024

Cubic millimetre of brain mapped in spectacular detail

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Rendering based on electron-microscope data, showing the positions of neurons in a fragment of the brain cortex. Neurons are coloured according to size. Credit: Google Research & Lichtman Lab (Harvard University). Renderings by D. Berger (Harvard University)

Researchers have mapped a tiny piece of the human brain in astonishing detail. The resulting cell atlas, which was described today in Science 1 and is available online , reveals new patterns of connections between brain cells called neurons, as well as cells that wrap around themselves to form knots, and pairs of neurons that are almost mirror images of each other.

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CS&E Announces 2024-25 Doctoral Dissertation Fellowship (DDF) Award Winners

Seven Ph.D. students working with CS&E professors have been named Doctoral Dissertation Fellows for the 2024-25 school year. The Doctoral Dissertation Fellowship is a highly competitive fellowship that gives the University’s most accomplished Ph.D. candidates an opportunity to devote full-time effort to an outstanding research project by providing time to finalize and write a dissertation during the fellowship year. The award includes a stipend of $25,000, tuition for up to 14 thesis credits each semester, and subsidized health insurance through the Graduate Assistant Health Plan.

CS&E congratulates the following students on this outstanding accomplishment:

• Athanasios Bacharis (Advisor: Nikolaos Papanikolopoulos )
• Karin de Langis (Advisor:  Dongyeop Kang )
• Arshia Zernab Hassan (Advisors: Chad Myers )
• Xinyue Hu (Advisors: Zhi-Li Zhang )
• Lucas Kramer (Advisors: Eric Van Wyk )
• Yijun Lin (Advisors: Yao-Yi Chiang )
• Mingzhou Yang (Advisors: Shashi Shekhar )

Athanasios Bacharis

Bacharis’ work centers around the robot-vision area, focusing on making autonomous robots act on visual information. His research includes active vision approaches, namely, view planning and next-best-view, to tackle the problem of 3D reconstruction via different optimization frameworks. The acquisition of 3D information is crucial for automating tasks, and active vision methods obtain it via optimal inference. Areas of impact include agriculture and healthcare, where 3D models can lead to reduced use of fertilizers via phenotype analysis of crops and effective management of cancer treatments. Bacharis has a strong publication record, with two peer-reviewed conference papers and one journal paper already published. He also has one conference paper under review and two journal papers in the submission process. His publications are featured in prestigious robotic and automation venues, further demonstrating his expertise and the relevance of his research in the field.

Karin de Langis

Karin's thesis works at the intersection of Natural Language Processing (NLP) and cognitive science. Her work uses eye-tracking and other cognitive signals to improve NLP systems in their performance and cognitive interpretability, and to create NLP systems that process language more similarly to humans. Her human-centric approach to NLP is motivated by the possibility of addressing the shortcomings of current statistics-based NLP systems, which often become stuck on explainability and interpretability, resulting in potential biases. This work has most recently been accepted and presented at SIGNLL Conference on Computational Natural Language Learning (CoNLL) conference which has a special focus on theoretically, cognitively and scientifically motivated approaches to computational linguistics.

Arshia Zernab Hassan

Hassan's thesis work delves into developing computational methods for interpreting data from genome wide CRISPR/Cas9 screens. CRISPR/Cas9 is a new approach for genome editing that enables precise, large-scale editing of genomes and construction of mutants in human cells. These are powerful data for inferring functional relationships among genes essential for cancer growth. Moreover, chemical-genetic CRISPR screens, where population of mutant cells are grown in the presence of chemical compounds, help us understand the effect the chemicals have on cancer cells and formulate precise drug solutions. Given the novelty of these experimental technologies, computational methods to process and interpret the resulting data and accurately quantify the various genetic interactions are still quite limited, and this is where Hassan’s dissertation is focused on. Her research extends to developing deep-learning based methods that leverage CRISPR chemical-genetic and other genomic datasets to predict cancer sensitivity to candidate drugs. Her methods on improving information content in CRISPR screens was published in the Molecular Systems Biology journal, a highly visible journal in the computational biology field. 

Hu's Ph.D. dissertation is concentrated on how to effectively leverage the power of artificial intelligence and machine learning (AI/ML) – especially deep learning – to tackle challenging and important problems in the design and development of reliable, effective and secure (independent) physical infrastructure networks. More specifically, her research focuses on two critical infrastructures: power grids and communication networks, in particular, emerging 5G networks, both of which not only play a critical role in our daily life but are also vital to the nation’s economic well-being and security. Due to the enormous complexity, diversity, and scale of these two infrastructures, traditional approaches based on (simplified) theoretical models and heuristics-based optimization are no longer sufficient in overcoming many technical challenges in the design and operations of these infrastructures: data-driven machine learning approaches have become increasingly essential. The key question now is: how does one leverage the power of AI/ML without abandoning the rich theory and practical expertise that have accumulated over the years? Hu’s research has pioneered a new paradigm – (domain) knowledge-guided machine learning (KGML) – in tackling challenging and important problems in power grid and communications (e.g., 5G) network infrastructures.

Lucas Kramer

Kramer is now the driving force in designing tools and techniques for building extensible programming languages, with the Minnesota Extensible Language Tools (MELT) group. These are languages that start with a host language such as C or Java, but can then be extended with new syntax (notations) and new semantics (e.g. error-checking analyses or optimizations) over that new syntax and the original host language syntax. One extension that Kramer created was to embed the domain-specific language Halide in MELT's extensible specification of C, called ableC. This extension allows programmers to specify how code working on multi-dimensional matrices is transformed and optimized to make efficient use of hardware. Another embeds the logic-programming language Prolog into ableC; yet another provides a form of nondeterministic parallelism useful in some algorithms that search for a solution in a structured, but very large, search space. The goal of his research is to make building language extensions such as these more practical for non-expert developers.  To this end he has made many significant contributions to the MELT group's Silver meta-language, making it easier for extension developers to correctly specify complex language features with minimal boilerplate. Kramer is the lead author of one journal and four conference papers on his work at the University of Minnesota, winning the distinguished paper award for his 2020 paper at the Software Language Engineering conference, "Strategic Tree Rewriting in Attribute Grammars".

Lin’s doctoral dissertation focuses on a timely, important topic of spatiotemporal prediction and forecasting using multimodal and multiscale data. Spatiotemporal prediction and forecasting are important scientific problems applicable to diverse phenomena, such as air quality, ambient noise, traffic conditions, and meteorology. Her work also couples the resulting prediction and forecasting with multimodal (e.g., satellite imagery, street-view photos, census records, and human mobility data) and multiscale geographic information (e.g., census records focusing on small tracts vs. neighborhood surveys) to characterize the natural and built environment, facilitating our understanding of the interactions between and within human social systems and the ecosystem. Her work has a wide-reaching impact across multiple domains such as smart cities, urban planning, policymaking, and public health.

Mingzhou Yang

Yang is developing a thesis in the broad area of spatial data mining for problems in transportation. His thesis has both societal and theoretical significance. Societally, climate change is a grand challenge due to the increasing severity and frequency of climate-related disasters such as wildfires, floods, droughts, etc. Thus, many nations are aiming at carbon neutrality (also called net zero) by mid-century to avert the worst impacts of global warming. Improving energy efficiency and reducing toxic emissions in transportation is important because transportation accounts for the vast majority of U.S. petroleum consumption as well as over a third of GHG emissions and over a hundred thousand U.S. deaths annually via air pollution. To accurately quantify the expected environmental cost of vehicles during real-world driving, Yang's thesis explores ways to incorporate physics in the neural network architecture complementing other methods of integration: feature incorporation, and regularization. This approach imposes stringent physical constraints on the neural network model, guaranteeing that its outputs are consistently in accordance with established physical laws for vehicles. Extensive experiments including ablation studies demonstrated the efficacy of incorporating physics into the model. 

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Math discovery provides new method to study cell activity, aging, MSU research shows

Contact: Meg Henderson

STARKVILLE, Miss.—New mathematical tools revealing how quickly cell proteins break down are poised to uncover deeper insights into how we age, according to a recently published paper co-authored by a Mississippi State researcher and his colleagues from Harvard Medical School and the University of Cambridge.

Galen Collins, assistant professor in MSU’s Department of Biochemistry, Molecular Biology, Entomology and Plant Pathology, co-authored the groundbreaking paper published in the Proceedings of the National Academy of Sciences, or PNAS, in April.

“We already understand how quickly proteins are made, which can happen in a matter of minutes,” said Collins, who is also a scientist in the Mississippi Agricultural and Forestry Experiment Station. “Until now, we’ve had a very poor understanding of how much time it takes them to break down.”

The paper in applied mathematics, “ Maximum entropy determination of mammalian proteome dynamics ,” presents the new tools that quantify the degradation rates of cell proteins—how quickly they break down—helping us understand how cells grow and die and how we age. Proteins—complex molecules made from various combinations of amino acids—carry the bulk of the workload within a cell, providing its structure, responding to messages from outside the cell and removing waste. 

The results proved that not all proteins degrade at the same pace but instead fall into one of three categories, breaking down over the course of minutes, hours or days. While previous research has examined cell protein breakdown, this study was the first to quantify mathematically the degradation rates of all cell protein molecules, using a technique called maximum entropy.

“For certain kinds of scientific questions, experiments can often reveal infinitely many possible answers; however, they are not all equally plausible,” said lead author Alexander Dear, research fellow in applied mathematics at Harvard University. “The principle of maximum entropy is a mathematical law that shows us how to precisely calculate the plausibility of each answer—its ‘entropy’—so that we can choose the one that is the most likely.”

“This kind of math is sort of like a camera that zooms in on your license plate from far away and figures out what the numbers should be,” Collins said. “Maximum entropy gives us a clear and precise picture of how protein degradation occurs in cells.”

In addition, the team used these tools to study some specific implications of protein degradation for humans and animals. For one, they examined how those rates change as muscles develop and adapt to starvation.

“We found that starvation had the greatest impact on the intermediate group of proteins in muscular cells, which have a half-life of a few hours, causing the breakdown to shift and accelerate,” Collins said. “This discovery could have implications for cancer patients who experience cachexia, or muscle wasting due to the disease and its treatments.”

They also explored how a shift in the breakdown of certain cell proteins contributes to neurodegenerative disease.

“These diseases occur when waste proteins, which usually break down quickly, live longer than they should,” Collins said. “The brain becomes like a teenager’s bedroom, accumulating trash, and when you don’t clean it up, it becomes uninhabitable.”

Dear affirmed the study’s value lies not only in what it revealed about cell protein degeneration, but also in giving scientists a new method to investigate cell activity with precision.

“Our work provides a powerful new experimental method for quantifying protein metabolism in cells,” he said. “Its simplicity and rapidity make it particularly well-suited for studying metabolic changes.”

Collins’s post-doctoral advisor at Harvard and a co-author of the article, the late Alfred Goldberg, was a pioneer in studying the life and death of proteins. Collins noted this study was built on nearly five decades of Goldberg’s research and his late-career collaboration with mathematicians from the University of Cambridge. After coming to MSU a year ago, Collins continued collaborating with his colleagues to complete the paper.

“It’s an incredible honor to be published in PNAS, but it was also a lot of fun being part of this team,” Collins said. “And it’s very meaningful to see my former mentor’s body of work wrapped up and published.”

Since 1914, PNAS has been one of the most authoritative publications of high-impact research in the biological, physical and social sciences. More information and past issues can be found at www.pnas.org . The Mississippi Agricultural and Forestry Experiment Station conducts research that improves human health and well-being. Learn more at www.mafes.msstate.edu .  

Mississippi State University is taking care of what matters. Learn more at  www.msstate.edu .

Monday, May 20, 2024 - 2:58 pm

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It is considered that thesis help services improve the quality of your research paper in several ways. The thesis help is accessed by a large strength of students to make their thesis meaningful. Below mention are some of them:

Expert Guidance: They provide access to the most experienced professionals who offer the best possible insights related to enhancing the quality of your research.

Structural Support: The service also assists in organising the whole paper logically. It ensures a clear flow of ideas. The thesis writing makes sure that the thesis has a logical flow in all the chapters.

Editing: The services thoroughly check all the areas of the writing like grammar, spelling, and many more. It improves the readability of the paper.

Research Assistance: They help in terms of identifying credible sources. It ensures that your paper is supported by relevant information.

Plagiarism Check: They also conduct the process of plagiarism checks to make sure that the content is original. It is a very essential practice to do. The thesis writing services provide the most authentic piece of work that meets the academic standard of the writing and institution.

Customised Feedback: They make sure to provide tailored feedback that is specific to your topic. It helps in refining the arguments of the paper.

Confidence Boost: It is a fact that by improving the quality of paper, these services boost the level of confidence in your work.

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Call for High School Projects

Machine learning for social impact .

The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024) is an interdisciplinary conference that brings together researchers in machine learning, neuroscience, statistics, optimization, computer vision, natural language processing, life sciences, natural sciences, social sciences, and other adjacent fields. 

This year, we invite high school students to submit research papers on the topic of machine learning for social impact.  A subset of finalists will be selected to present their projects virtually and will have their work spotlighted on the NeurIPS homepage.  In addition, the leading authors of up to five winning projects will be invited to attend an award ceremony at NeurIPS 2024 in Vancouver.  

Each submission must describe independent work wholly performed by the high school student authors.  We expect each submission to highlight either demonstrated positive social impact or the potential for positive social impact using machine learning. Application areas may include but are not limited to the following:

• Agriculture
• Climate change
• Homelessness
• Food security
• Mental health
• Water quality

Authors will be asked to confirm that their submissions accord with the NeurIPS code of conduct and the NeurIPS code of ethics .

Submission deadline: All submissions must be made by June 27th, 4pm EDT. The system will close after this time, and no further submissions will be possible.

We are using OpenReview to manage submissions. Papers should be submitted here . Submission will open June 1st.  Submissions under review will be visible only to their assigned program committee. We will not be soliciting comments from the general public during the reviewing process. Anyone who plans to submit a paper as an author or a co-author will need to create (or update) their OpenReview profile by the full paper submission deadline. 

Formatting instructions:   All submissions must be in PDF format. Submissions are limited to four content pages , including all figures and tables; additional pages containing only references are allowed. You must format your submission using the NeurIPS 2024 LaTeX style file using the “preprint” option for non-anonymous submission. The maximum file size for submissions is 50MB. Submissions that violate the NeurIPS style (e.g., by decreasing margins or font sizes) or page limits may be rejected without further review.  Papers may be rejected without consideration of their merits if they fail to meet the submission requirements, as described in this document. 

Mentorship and collaboration:  The submitted research can be a component of a larger research endeavor involving external collaborators, but the submission should describe only the authors’ contributions.  The authors can also have external mentors but must disclose the nature of the mentorship.  At the time of submission, the authors will be asked to describe the involvement of any mentors or external collaborators and to distinguish mentor and collaborator contributions from those of the authors.  In addition, the authors may (optionally) include an acknowledgements section acknowledging the contributions of others following the content sections of the submission. The acknowledgements section will not count toward the submission page limit.

Proof of high school attendance: Submitting authors will also be asked to upload a signed letter, on school letterhead, from each author’s high school confirming that the author was enrolled in high school during the 2023-2024 academic year.

Supplementary artifacts:  In their submission, authors may link to supplementary artifacts including videos, working demonstrations, digital posters, websites, or source code.  Please do not link to additional text.  All such supplementary material should be wholly created by the authors and should directly support the submission content. 

Review process:   Each submission will be reviewed by anonymous referees. The authors, however, should not be anonymous. No written feedback will be provided to the authors.  

Use of Large Language Models (LLMs): We welcome authors to use any tool that is suitable for preparing high-quality papers and research. However, we ask authors to keep in mind two important criteria. First, we expect papers to fully describe their methodology.  Any tool that is important to that methodology, including the use of LLMs, should be described also. For example, authors should mention tools (including LLMs) that were used for data processing or filtering, visualization, facilitating or running experiments, or proving theorems. It may also be advisable to describe the use of LLMs in implementing the method (if this corresponds to an important, original, or non-standard component of the approach). Second, authors are responsible for the entire content of the paper, including all text and figures, so while authors are welcome to use any tool they wish for writing the paper, they must ensure that all text is correct and original.

Dual submissions:  Submissions that are substantially similar to papers that the authors have previously published or submitted in parallel to other peer-reviewed venues with proceedings or journals may not be submitted to NeurIPS. Papers previously presented at workshops or science fairs are permitted, so long as they did not appear in a conference proceedings (e.g., CVPRW proceedings), a journal, or a book.  However, submissions will not be published in formal proceedings, so work submitted to this call may be published elsewhere in the future. Plagiarism is prohibited by the NeurIPS Code of Conduct .

Paper checklist: In order to improve the rigor and transparency of research submitted to and published at NeurIPS, authors are required to complete a paper checklist . The paper checklist is intended to help authors reflect on a wide variety of issues relating to responsible machine learning research, including reproducibility, transparency, research ethics, and societal impact. The checklist does not count towards the page limit and will be entered in OpenReview.

Contact:   [email protected]

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Jamshidi earns recognition for most influential paper

When someone in academia publishes a research paper, one of the goals is to have the paper cited by other professors and researchers. A paper published 10 years ago by Computer Science and Engineering Assistant Professor Pooyan Jamshidi was recently recognized for its significant impact.

Jamshidi received the Most Influential Paper Award in April at the 19th International Conference on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) in Lisbon, Portugal. Jamshidi’s paper, “ Autonomic Resource Provision for Cloud-based Software ,” was submitted, accepted and published just prior to earning his Ph.D. from Dublin City University in Ireland in 2014. It was presented at the 2014 SEAMS Conference in India.

For the most influential paper award, a select committee considers conference publications published approximately 10 years previously and selects those that have made the most impact according to several criteria, including the number of citations, practical applications and industry adoption, and influence on subsequent research. The most influential award is selected from this short list.

“I wanted to publish the most important part of my Ph.D. research at SEAMS because it was a special community, and their work was close to mine,” Jamshidi says. “Receiving this award is important because this was my first paper with the community. I kept publishing with SEAMS and remained engaged.” 

The paper’s title referred to a groundbreaking approach to fundamentally transform how resources are managed and allocated in cloud environments. The key innovation was to enable multiple tenants to describe their adaptation rules for cloud and multi-cloud resource provisioning using a specific language that enables the incorporation of reasoning, inference and resolution of conflicting adaptation rules.

Since the paper was published, it has received 188 citations according to Google Scholar . In addition, the autonomic resource provision technique has been integrated with Microsoft Azure and OpenStack . The concepts and methods introduced in the paper have also led to follow-up research in cloud autoscaling, Edge-and-Internet of Things resource scaling, and networking and autonomous driving.

The paper has impacted the field of software engineering, especially in the context of adaptive and self-managing systems in the cloud, research, industry practices and the broader technological landscape.

While Jamshidi admits that autonomous autoscaling system for cloud-based software is not as a hot topic as it was when his paper was published, it is still a relevant research area that is leading to new ideas, methods, and approaches.

“The most exciting direction in cloud auto-scaling and resource provisioning overall is sustainability-aware approaches to enable sustainable computer usage for modern applications, such as AI systems,” Jamshidi says. “We plan to continue this line of research. For example, thanks to funds provided by the National Science Foundation and collaborators from Carnegie Mellon University and Rochester Institute of Technology, we are investigating software-driven sustainability.” 

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