how to write a questionnaire for dissertation

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How to structure quantitative research questions

There is no "one best way" to structure a quantitative research question. However, to create a well-structured quantitative research question, we recommend an approach that is based on four steps : (1) Choosing the type of quantitative research question you are trying to create (i.e., descriptive, comparative or relationship-based); (2) Identifying the different types of variables you are trying to measure, manipulate and/or control, as well as any groups you may be interested in; (3) Selecting the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved; and (4) Writing out the problem or issues you are trying to address in the form of a complete research question. In this article, we discuss each of these four steps , as well as providing examples for the three types of quantitative research question you may want to create: descriptive , comparative and relationship-based research questions .

• STEP ONE: Choose the type of quantitative research question (i.e., descriptive, comparative or relationship) you are trying to create
• STEP TWO: Identify the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in
• STEP THREE: Select the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved
• STEP FOUR: Write out the problem or issues you are trying to address in the form of a complete research question

STEP ONE Choose the type of quantitative research question (i.e., descriptive, comparative or relationship) you are trying to create

The type of quantitative research question that you use in your dissertation (i.e., descriptive , comparative and/or relationship-based ) needs to be reflected in the way that you write out the research question; that is, the word choice and phrasing that you use when constructing a research question tells the reader whether it is a descriptive, comparative or relationship-based research question. Therefore, in order to know how to structure your quantitative research question, you need to start by selecting the type of quantitative research question you are trying to create: descriptive, comparative and/or relationship-based.

STEP TWO Identify the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in

Whether you are trying to create a descriptive, comparative or relationship-based research question, you will need to identify the different types of variable that you are trying to measure , manipulate and/or control . If you are unfamiliar with the different types of variable that may be part of your study, the article, Types of variable , should get you up to speed. It explains the two main types of variables: categorical variables (i.e., nominal , dichotomous and ordinal variables) and continuous variables (i.e., interval and ratio variables). It also explains the difference between independent and dependent variables , which you need to understand to create quantitative research questions.

To provide a brief explanation; a variable is not only something that you measure , but also something that you can manipulate and control for. In most undergraduate and master's level dissertations, you are only likely to measure and manipulate variables. You are unlikely to carry out research that requires you to control for variables, although some supervisors will expect this additional level of complexity. If you plan to only create descriptive research questions , you may simply have a number of dependent variables that you need to measure. However, where you plan to create comparative and/or relationship-based research questions , you will deal with both dependent and independent variables . An independent variable (sometimes called an experimental or predictor variable ) is a variable that is being manipulated in an experiment in order to observe the effect this has on a dependent variable (sometimes called an outcome variable ). For example, if we were interested in investigating the relationship between gender and attitudes towards music piracy amongst adolescents , the independent variable would be gender and the dependent variable attitudes towards music piracy . This example also highlights the need to identify the group(s) you are interested in. In this example, the group of interest are adolescents .

Once you identifying the different types of variable you are trying to measure, manipulate and/or control, as well as any groups you may be interested in, it is possible to start thinking about the way that the three types of quantitative research question can be structured . This is discussed next.

STEP THREE Select the appropriate structure for the chosen type of quantitative research question, based on the variables and/or groups involved

The structure of the three types of quantitative research question differs, reflecting the goals of the question, the types of variables, and the number of variables and groups involved. By structure , we mean the components of a research question (i.e., the types of variables, groups of interest), the number of these different components (i.e., how many variables and groups are being investigated), and the order that these should be presented (e.g., independent variables before dependent variables). The appropriate structure for each of these quantitative research questions is set out below:

Structure of descriptive research questions

• Structure of comparative research questions
• Structure of relationship-based research questions

There are six steps required to construct a descriptive research question: (1) choose your starting phrase; (2) identify and name the dependent variable; (3) identify the group(s) you are interested in; (4) decide whether dependent variable or group(s) should be included first, last or in two parts; (5) include any words that provide greater context to your question; and (6) write out the descriptive research question. Each of these steps is discussed in turn:

Choose your starting phrase

Identify and name the dependent variable

Identify the group(s) you are interested in

Decide whether the dependent variable or group(s) should be included first, last or in two parts

Include any words that provide greater context to your question

Write out the descriptive research question

FIRST Choose your starting phrase

You can start descriptive research questions with any of the following phrases:

How many? How often? How frequently? How much? What percentage? What proportion? To what extent? What is? What are?

Some of these starting phrases are highlighted in blue text in the examples below:

How many calories do American men and women consume per day?

How often do British university students use Facebook each week?

What are the most important factors that influence the career choices of Australian university students?

What proportion of British male and female university students use the top 5 social networks?

What percentage of American men and women exceed their daily calorific allowance?

SECOND Identify and name the dependent variable

All descriptive research questions have a dependent variable. You need to identify what this is. However, how the dependent variable is written out in a research question and what you call it are often two different things. In the examples below, we have illustrated the name of the dependent variable and highlighted how it would be written out in the blue text .

The first two examples highlight that while the name of the dependent variable is the same, namely daily calorific intake , the way that this dependent variable is written out differs in each case.

THIRD Identify the group(s) you are interested in

All descriptive research questions have at least one group , but can have multiple groups . You need to identify this group(s). In the examples below, we have identified the group(s) in the green text .

What are the most important factors that influence the career choices of Australian university students ?

The examples illustrate the difference between the use of a single group (e.g., British university students ) and multiple groups (e.g., American men and women ).

FOURTH Decide whether the dependent variable or group(s) should be included first, last or in two parts

Sometimes it makes more sense for the dependent variable to appear before the group(s) you are interested in, but sometimes it is the opposite way around. The following examples illustrate this, with the group(s) in green text and the dependent variable in blue text :

Group 1st; dependent variable 2nd:

How often do British university students use Facebook each week ?

Dependent variable 1st; group 2nd:

Sometimes, the dependent variable needs to be broken into two parts around the group(s) you are interested in so that the research question flows. Again, the group(s) are in green text and the dependent variable is in blue text :

How many calories do American men and women consume per day ?

Of course, you could choose to restructure the question above so that you do not have to split the dependent variable into two parts. For example:

How many calories are consumed per day by American men and women ?

When deciding whether the dependent variable or group(s) should be included first or last, and whether the dependent variable should be broken into two parts, the main thing you need to think about is flow : Does the question flow? Is it easy to read?

FIFTH Include any words that provide greater context to your question

Sometimes the name of the dependent variable provides all the explanation we need to know what we are trying to measure. Take the following examples:

In the first example, the dependent variable is daily calorific intake (i.e., calories consumed per day). Clearly, this descriptive research question is asking us to measure the number of calories American men and women consume per day. In the second example, the dependent variable is Facebook usage per week. Again, the name of this dependent variable makes it easy for us to understand that we are trying to measure the often (i.e., how frequently; e.g., 16 times per week) British university students use Facebook.

However, sometimes a descriptive research question is not simply interested in measuring the dependent variable in its entirety, but a particular component of the dependent variable. Take the following examples in red text :

In the first example, the research question is not simply interested in the daily calorific intake of American men and women, but what percentage of these American men and women exceeded their daily calorific allowance. So the dependent variable is still daily calorific intake, but the research question aims to understand a particular component of that dependent variable (i.e., the percentage of American men and women exceeding the recommend daily calorific allowance). In the second example, the research question is not only interested in what the factors influencing career choices are, but which of these factors are the most important.

Therefore, when you think about constructing your descriptive research question, make sure you have included any words that provide greater context to your question.

SIXTH Write out the descriptive research question

Once you have these details ? (1) the starting phrase, (2) the name of the dependent variable, (3) the name of the group(s) you are interested in, and (4) any potential joining words ? you can write out the descriptive research question in full. The example descriptive research questions discussed above are written out in full below:

In the section that follows, the structure of comparative research questions is discussed.

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Surveys are a special research tool with strengths, weaknesses, and a language all of their own. There are many different steps to designing and conducting a survey, and survey researchers have specific ways of describing what they do.

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Using a questionnaire survey for your dissertation

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Find out how to use a dissertation questionnaire for your masters.

Prof Martyn Denscombe, author of " The Good Research Guide, 6th edition ", gives expert advice on using a questionnaire survey for your postgraduate dissertation.

Questionnaire surveys are a well-established way of collecting data. They work with relatively small-scale research projects so design and deliver research questionnaires quickly and cheaply. When it comes to conducting research for a master’s dissertation, questionnaire surveys feature prominently as the method of choice.

Using the post for bulky and lengthy surveys is normal. Sometimes questionnaires go by hand. The popularity of questionnaire surveys is principally due to the benefits of using online web-based questionnaires. There are two main aspects to this.

Designing questionnaires

First, the software for producing and delivering web questionnaires. Simple to use features such as drop-down menus and tick-box answers, is user-friendly and inexpensive.

Second, online surveys make it possible to contact people across the globe without travelling anywhere. Given the time and resource constraints faced when producing a dissertation, makes online surveys all the more enticing. Social media such as Facebook, Instagram and WhatsApp is great for contacting people to participate in the survey.

In the context of a master’s dissertation, however, the quality of the survey data is a vital issue. The grade for the dissertation will depend on being able to defend the use of the data from the survey. This is the basis for advanced, master’s level academic enquiry.

Pro's and con's

It is not good enough to simply rely on getting 100 or so people to complete your questionnaire. Be aware of the pros and cons of questionnaire surveys. You need to justify the value of the data you have collected in the face of probing questions, such as:

• Who are the respondents and how they were selected?
• How representative are the respondents of the whole group being studied?
• What response rate was achieved by the survey?
• Are the questions suitable in relation to the topic and the particular respondents?
• What likelihood is there that respondents gave honest answers to the questions?

This is where The Good Research Guide, 6th edition becomes so valuable.

It identifies the key points that need to be addressed in order to conduct a competent questionnaire survey. It gets right to the heart of the matter, with plenty of practical guidance on how to deal with issues.

In a straightforward style, using plain language, this bestselling book covers a range of alternative strategies and methods for conducting small-scale social research projects and outlines some of the main ways in which the data can be analysed.

Read Prof Martyn Denscombe's advice on using a Case Study for your postgraduate dissertation.

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

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

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

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

*The Caveat *

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

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

Overview: S tructuring a dissertation or thesis

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

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

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

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

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

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

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

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

Typically, a good title includes mention of the following:

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

For example:

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

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

Acknowledgements

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

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

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

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

Abstract or executive summary

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

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

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

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

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

Need a helping hand?

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Time to recap…

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

• Acknowledgments page

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

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

Psst... there’s more!

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

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36 Comments

many thanks i found it very useful

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

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

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

Thanks so much this helped me a lot!

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

Thanks Ade!

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

You’re welcome!

Hi! How many words maximum should contain the abstract?

Thank you so much 😊 Find this at the right moment

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

best ever benefit i got on right time thank you

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

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

You have given immense clarity from start to end.

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

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

Thanks ! so concise and valuable

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

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

Really useful to me. Thanks a thousand times

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

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

Usefull, thanks a lot. Really clear

Very nice and easy to understand. Thank you .

That was incredibly useful. Thanks Grad Coach Crew!

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

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

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

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

Great video; I appreciate that helpful information

It is so necessary or avital course

This blog is very informative for my research. Thank you

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

wow this is an amazing gain in my life

This is so good

How can i arrange my specific objectives in my dissertation?

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Dissertation surveys: Questions, examples, and best practices

Collect data for your dissertation with little effort and great results.

Dissertation surveys are one of the most powerful tools to get valuable insights and data for the culmination of your research. However, it’s one of the most stressful and time-consuming tasks you need to do. You want useful data from a representative sample that you can analyze and present as part of your dissertation. At SurveyPlanet, we’re committed to making it as easy and stress-free as possible to get the most out of your study.

With an intuitive and user-friendly design, our templates and premade questions can be your allies while creating a survey for your dissertation. Explore all the options we offer by simply signing up for an account—and leave the stress behind.

How to write dissertation survey questions

The first thing to do is to figure out which group of people is relevant for your study. When you know that, you’ll also be able to adjust the survey and write questions that will get the best results.

The next step is to write down the goal of your research and define it properly. Online surveys are one of the best and most inexpensive ways to reach respondents and achieve your goal.

Before writing any questions, think about how you’ll analyze the results. You don’t want to write and distribute a survey without keeping how to report your findings in mind. When your thesis questionnaire is out in the real world, it’s too late to conclude that the data you’re collecting might not be any good for assessment. Because of that, you need to create questions with analysis in mind.

You may find our five survey analysis tips for better insights helpful. We recommend reading it before analyzing your results.

Once you understand the parameters of your representative sample, goals, and analysis methodology, then it’s time to think about distribution. Survey distribution may feel like a headache, but you’ll find that many people will gladly participate.

Find communities where your targeted group hangs out and share the link to your survey with them. If you’re not sure how large your research sample should be, gauge it easily with the survey sample size calculator.

Need help with writing survey questions? Read our guide on well-written examples of good survey questions .

Dissertation survey examples

Whatever field you’re studying, we’re sure the following questions will prove useful when crafting your own.

At the beginning of every questionnaire, inform respondents of your topic and provide a consent form. After that, start with questions like:

• Please select your gender:
• What is the highest educational level you’ve completed?
• High school
• Bachelor degree
• Master’s degree
• On a scale of 1-7, how satisfied are you with your current job?
• Please rate the following statements:
• I always wait for people to text me first.
• Strongly Disagree
• Neither agree nor disagree
• Strongly agree
• My friends always complain that I never invite them anywhere.
• I prefer spending time alone.
• Rank which personality traits are most important when choosing a partner. Rank 1 - 7, where 1 is the most and 7 is the least important.
• Flexibility
• Independence
• How openly do you share feelings with your partner?
• Almost never
• Almost always
• In the last two weeks, how often did you experience headaches?

Dissertation survey best practices

There are a lot of DOs and DON’Ts you should keep in mind when conducting any survey, especially for your dissertation. To get valuable data from your targeted sample, follow these best practices:

Use the consent form.

The consent form is a must when distributing a research questionnaire. A respondent has to know how you’ll use their answers and that the survey is anonymous.

Avoid leading and double-barreled questions

Leading and double-barreled questions will produce inconclusive results—and you don’t want that. A question such as: “Do you like to watch TV and play video games?” is double-barreled because it has two variables.

On the other hand, leading questions such as “On a scale from 1-10 how would you rate the amazing experience with our customer support?” influence respondents to answer in a certain way, which produces biased results.

Use easy and straightforward language and questions

Don’t use terms and professional jargon that respondents won’t understand. Take into consideration their educational level and demographic traits and use easy-to-understand language when writing questions.

Mix close-ended and open-ended questions

Too many open-ended questions will annoy respondents. Also, analyzing the responses is harder. Use more close-ended questions for the best results and only a few open-ended ones.

Strategically use different types of responses

Likert scale, multiple-choice, and ranking are all types of responses you can use to collect data. But some response types suit some questions better. Make sure to strategically fit questions with response types.

Ensure that data privacy is a priority

Make sure to use an online survey tool that has SSL encryption and secure data processing. You don’t want to risk all your hard work going to waste because of poorly managed data security. Ensure that you only collect data that’s relevant to your dissertation survey and leave out any questions (such as name) that can identify the respondents.

Create dissertation questionnaires with SurveyPlanet

Overall, survey methodology is a great way to find research participants for your research study. You have all the tools required for creating a survey for a dissertation with SurveyPlanet—you only need to sign up . With powerful features like question branching, custom formatting, multiple languages, image choice questions, and easy export you will find everything needed to create, distribute, and analyze a dissertation survey.

Happy data gathering!

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Free unlimited surveys, questions and responses.

Think of yourself as a member of a jury, listening to a lawyer who is presenting an opening argument. You'll want to know very soon whether the lawyer believes the accused to be guilty or not guilty, and how the lawyer plans to convince you. Readers of academic essays are like jury members: before they have read too far, they want to know what the essay argues as well as how the writer plans to make the argument. After reading your thesis statement, the reader should think, "This essay is going to try to convince me of something. I'm not convinced yet, but I'm interested to see how I might be."

An effective thesis cannot be answered with a simple "yes" or "no." A thesis is not a topic; nor is it a fact; nor is it an opinion. "Reasons for the fall of communism" is a topic. "Communism collapsed in Eastern Europe" is a fact known by educated people. "The fall of communism is the best thing that ever happened in Europe" is an opinion. (Superlatives like "the best" almost always lead to trouble. It's impossible to weigh every "thing" that ever happened in Europe. And what about the fall of Hitler? Couldn't that be "the best thing"?)

A good thesis has two parts. It should tell what you plan to argue, and it should "telegraph" how you plan to argue—that is, what particular support for your claim is going where in your essay.

Steps in Constructing a Thesis

First, analyze your primary sources.  Look for tension, interest, ambiguity, controversy, and/or complication. Does the author contradict himself or herself? Is a point made and later reversed? What are the deeper implications of the author's argument? Figuring out the why to one or more of these questions, or to related questions, will put you on the path to developing a working thesis. (Without the why, you probably have only come up with an observation—that there are, for instance, many different metaphors in such-and-such a poem—which is not a thesis.)

Once you have a working thesis, write it down.  There is nothing as frustrating as hitting on a great idea for a thesis, then forgetting it when you lose concentration. And by writing down your thesis you will be forced to think of it clearly, logically, and concisely. You probably will not be able to write out a final-draft version of your thesis the first time you try, but you'll get yourself on the right track by writing down what you have.

Keep your thesis prominent in your introduction.  A good, standard place for your thesis statement is at the end of an introductory paragraph, especially in shorter (5-15 page) essays. Readers are used to finding theses there, so they automatically pay more attention when they read the last sentence of your introduction. Although this is not required in all academic essays, it is a good rule of thumb.

Anticipate the counterarguments.  Once you have a working thesis, you should think about what might be said against it. This will help you to refine your thesis, and it will also make you think of the arguments that you'll need to refute later on in your essay. (Every argument has a counterargument. If yours doesn't, then it's not an argument—it may be a fact, or an opinion, but it is not an argument.)

This statement is on its way to being a thesis. However, it is too easy to imagine possible counterarguments. For example, a political observer might believe that Dukakis lost because he suffered from a "soft-on-crime" image. If you complicate your thesis by anticipating the counterargument, you'll strengthen your argument, as shown in the sentence below.

Some Caveats and Some Examples

A thesis is never a question.  Readers of academic essays expect to have questions discussed, explored, or even answered. A question ("Why did communism collapse in Eastern Europe?") is not an argument, and without an argument, a thesis is dead in the water.

A thesis is never a list.  "For political, economic, social and cultural reasons, communism collapsed in Eastern Europe" does a good job of "telegraphing" the reader what to expect in the essay—a section about political reasons, a section about economic reasons, a section about social reasons, and a section about cultural reasons. However, political, economic, social and cultural reasons are pretty much the only possible reasons why communism could collapse. This sentence lacks tension and doesn't advance an argument. Everyone knows that politics, economics, and culture are important.

A thesis should never be vague, combative or confrontational.  An ineffective thesis would be, "Communism collapsed in Eastern Europe because communism is evil." This is hard to argue (evil from whose perspective? what does evil mean?) and it is likely to mark you as moralistic and judgmental rather than rational and thorough. It also may spark a defensive reaction from readers sympathetic to communism. If readers strongly disagree with you right off the bat, they may stop reading.

An effective thesis has a definable, arguable claim.  "While cultural forces contributed to the collapse of communism in Eastern Europe, the disintegration of economies played the key role in driving its decline" is an effective thesis sentence that "telegraphs," so that the reader expects the essay to have a section about cultural forces and another about the disintegration of economies. This thesis makes a definite, arguable claim: that the disintegration of economies played a more important role than cultural forces in defeating communism in Eastern Europe. The reader would react to this statement by thinking, "Perhaps what the author says is true, but I am not convinced. I want to read further to see how the author argues this claim."

A thesis should be as clear and specific as possible.  Avoid overused, general terms and abstractions. For example, "Communism collapsed in Eastern Europe because of the ruling elite's inability to address the economic concerns of the people" is more powerful than "Communism collapsed due to societal discontent."

Copyright 1999, Maxine Rodburg and The Tutors of the Writing Center at Harvard University

Dissertation Questionnaire

A dissertation is a document usually a requirement for a doctoral degree especially in the field of philosophy. This long essay discusses a particular subject matter uses questionnaires   and other sources of data and is used to validate its content. The  questionnaire’s importance is evident in the processes of data gathering as it can make the dissertation factual, effective and usable.

Having a well-curated and formatted document to follow when making a dissertation can be very beneficial to an individual who is currently immersed in the data gathering stage of the specific research study. We have gathered downloadable samples and templates of questionnaires so it will be easier for you to curate your own.

Dissertation Timeline Gantt Chart Template

Size: 55 KB

Dissertation Research Gantt Chart Template

Size: 43 KB

Dissertation Project Gantt Chart Template

Size: 41 KB

Dissertation Plan Gantt Chart Template

Size: 51 KB

Dissertation Research Questionnaire

Size: 18 KB

Dissertation Proposal Questionnaire

Size: 131 KB

Sample Dissertation Questionnaire

Size: 10 KB

What Is a Dissertation Questionnaire?

A dissertation questionnaire can be defined as follows:

• It is a document used in the processes of data gathering.
• Questionnaires in PDF used for a dissertation contain questions that can help assess the current condition of the community which is the subject of study within the dissertation.
• It specifies the questions that are needed to be answered to assure that there is a basis in terms of the results that will be presented in a dissertation.

How to Write a Dissertation Questionnaire

Writing an efficient and comprehensive dissertation questionnaire can greatly affect the entire dissertation. You can make one by following these steps:

• Be specific with the kind of dissertation that you are creating and align the purposes of the dissertation questionnaire that you need to make to your study.
• List down the information needed from the community who will provide the answers to your questions.
• Open a software where you can create a questionnaire template. You may also download  survey questionnaire examples   and templates to have a faster time in formatting the document.
• The purpose of the dissertation questionnaire.
• The guidelines and instructions in answering the dissertation questions.
• The name of the person to who will use the questionnaire results to his/her dissertation.
• The institution to whom the dissertation will be passed.
• List down the questions based on your needs.

Undergraduate Dissertation Questionnaire

Size: 12 KB

Project Management Dissertation

Size: 54 KB

Guidelines for Writing a Dissertation Questionnaire

There are no strict rules in writing a dissertation questionnaire. However, there are some tips that can help you to create a dissertation questionnaire that is relevant to the study that you are currently doing. Some guidelines:

• Make sure that you are well aware of the data that is needed in your dissertation so you can properly curate questions that can supply your information needs.
• It will be best to use a dissertation questionnaire format that is organized, easy to understand, and properly structured. This will help the people who will answer the dissertation questionnaire quickly know how they can provide the items that you would like to know.
• Always make sure that your instructions in answering the questions are precise and directly stated.
• You may look at  questionnaires in Word   for comparisons. Doing this will help you assess whether there are still areas of improvement that you may tap with the content and format of the dissertation questionnaire that you have created.

Keeping this guidelines in mind and implementing them accordingly will allow you to create a dissertation questionnaire that is beneficial to the processes that you need to have an outstanding dissertation.

Questionnaire Generator

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Dissertations & projects: Research questions

• Research questions
• The process of reviewing
• Project management
• Literature-based projects

Jump to content on these pages:

“The central question that you ask or hypothesis you frame drives your research: it defines your purpose.” Bryan Greetham, How to Write Your Undergraduate Dissertation

This page gives some help and guidance in developing a realistic research question. It also considers the role of sub-questions and how these can influence your methodological choices. 

Choosing your research topic

You may have been provided with a list of potential topics or even specific questions to choose from. It is more common for you to have to come up with your own ideas and then refine them with the help of your tutor. This is a crucial decision as you will be immersing yourself in it for a long time.

Some students struggle to find a topic that is sufficiently significant and yet researchable within the limitations of an undergraduate project. You may feel overwhelmed by the freedom to choose your own topic but you could get ideas by considering the following:

Choose a topic that you find interesting . This may seem obvious but a lot of students go for what they think will be easy over what they think will be interesting - and regret it when they realise nothing is particularly easy and they are bored by the work. Think back over your lectures or talks from visiting speakers - was there anything you really enjoyed? Was there anything that left you with questions?

Choose something distinct . Whilst at undergraduate level you do not have to find something completely unique, if you find something a bit different you have more opportunity to come to some interesting conclusions. Have you some unique experiences that you can bring: personal biography, placements, study abroad etc?

Don't make your topic too wide . If your topic is too wide, it will be harder to develop research questions that you can actually answer in the context of a small research project.

Don't make your work too narrow . If your topic is too narrow, you will not be able to expand on the ideas sufficiently and make useful conclusions. You may also struggle to find enough literature to support it.

Scope out the field before deciding your topic . This is especially important if you have a few different options and are not sure which to pick. Spend a little time researching each one to get a feel for the amount of literature that exists and any particular avenues that could be worth exploring.

Think about your future . Some topics may fit better than others with your future plans, be they for further study or employment. Becoming more expert in something that you may have to be interviewed about is never a bad thing!

Once you have an idea (or even a few), speak to your tutor. They will advise on whether it is the right sort of topic for a dissertation or independent study. They have a lot of experience and will know if it is too much to take on, has enough material to build on etc.

Developing a research question or hypothesis

Research question vs hypothesis.

First, it may be useful to explain the difference between a research question and a hypothesis. A research question is simply a question that your research will address and hopefully answer (or give an explanation of why you couldn't answer it). A hypothesis is a statement that suggests how you expect something to function or behave (and which you would test to see if it actually happens or not).

Research question examples

• How significant is league table position when students choose their university?
• What impact can a diagnosis of depression have on physical health?

Note that these are open questions - i.e. they cannot be answered with a simple 'yes' or 'no'. This is the best form of question.

Hypotheses examples

• Students primarily choose their university based on league table position.
• A diagnosis of depression can impact physical health.

Note that these are things that you can test to see if they are true or false. This makes them more definite then research questions - but you can still answer them more fully than 'no they don't' or 'yes it does'. For example, in the above examples you would look to see how relevant other factors were when choosing universities and in what ways physical health may be impacted.

For more examples of the same topic formulated as hypotheses, research questions and paper titles see those given at the bottom of this document from Oakland University: Formulation of Research Hypothesis

Which do you need?

Generally, research questions are more common in the humanities, social sciences and business, whereas hypotheses are more common in the sciences. This is not a hard rule though, talk things through with your supervisor to see which they are expecting or which they think fits best with your topic.

What makes a good research question or hypothesis?

Unless you are undertaking a systematic review as your research method, you will develop your research question  as a result of reviewing the literature on your broader topic. After all, it is only by seeing what research has already been done (or not) that you can justify the need for your question or your approach to answering it. At the end of that process, you should be able to come up with a question or hypothesis that is:

• Clear (easily understandable)
• Focused (specific not vague or huge)
• Answerable (the data is available and analysable in the time frame)
• Relevant (to your area of study)
• Significant (it is worth answering)

You can try a few out, using a table like this (yours would all be in the same discipline):

A similar, though different table is available from the University of California: What makes a good research topic?   The completed table has some supervisor comments which may also be helpful.

Ultimately, your final research question will be mutually agreed between yourself and your supervisor - but you should always bring your own ideas to the conversation.

The role of sub-questions

Your main research question will probably still be too big to answer easily. This is where sub-questions come in. They are specific, narrower questions that you can answer directly from your data.

So, looking at the question " How much do online users know and care about how their self-images can be used by Apple, Google, Microsoft and Facebook? " from the table above, the sub-questions could be:

• What rights do the terms and conditions of signing up for Apple, Google, Microsoft and Facebook accounts give those companies regarding the use of self-images?
• What proportion of users read the terms and conditions when creating accounts with these companies?
• How aware are users of the rights they are giving away regarding their self-images when creating accounts with these companies?
• How comfortable are users with giving away these rights?

Together, the answers to your sub-questions should enable you to answer the overarching research question.

How do you answer your sub-questions?

Depending on the type of dissertation/project your are undertaking, some (or all) the questions may be answered with information collected from the literature and some (or none) may be answered by analysing data directly collected as part of your primary empirical research .

In the above example, the first question would be answered by documentary analysis of the relevant terms and conditions, the second by a mixture of reviewing the literature and analysing survey responses from participants and the last two also by analysing survey responses. Different projects will require different approaches.

Some sub-questions could be answered by reviewing the literature and others from empirical study.

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For example, the following research question is too broad.

Does social media affect mental health in college students?

A more focused research question could be:

Does social media play a role in the number of eating disorder diagnoses in college-aged women?

Need some guidance? Contact your subject librarian for a research consultation or reach out to [email protected] .

Start the brainstorming process:

• Begin by identifying a broad topic of research interest (the more you're personally interested in it, the better!). Write it down to clarify your focus.
• Narrow down your scope  by considering specific areas within this topic that you want to explore.
• Identify key themes and elements  related to these specific areas. These will be the building blocks of your investigation.
• Finally,  integrate these key areas and elements  into a well-crafted research question.

One way to brainstorm is to use a flowchart.

The scope of a topic  encompasses the boundaries and constraints you set for your research. The more precise your research question, the smoother the research process becomes.

Feeling stuck? Here are some ways you can narrow down your topic:

• geographic location
• time period
• discipline/field of study
• age group, etc.

You:  I need to conduct a literature review about social media, mental health, and college students. What are some example research questions within this topic?

ChatGPT: 

• How does the frequency and nature of social media use impact the mental health of college students?
• What role do specific social media platforms play in influencing the mental well-being of college students?
• How do online social interactions on platforms like Facebook, Instagram, or Twitter relate to the mental health outcomes of college students?
• Are there differences in the association between social media use and mental health outcomes based on demographic factors such as gender, age, or academic major among college students?
• What strategies do college students employ to cope with negative mental health effects associated with social media use?
• How does the perception of social support through online platforms affect the mental health of college students?
• To what extent does the comparison of oneself to others on social media contribute to mental health challenges among college students?
• What interventions or educational programs are effective in promoting positive mental health behaviors in the context of social media use for college students?
• How do social media literacy and awareness programs impact the mental health attitudes and behaviors of college students?
• What is the relationship between the use of social media for academic and social purposes and the mental health outcomes of college students?

Generative AI tools : ChatGPT , Google Gemini (formerly Bard) , Claude , Microsoft Copilot

For more information on how to incorporate AI tools into your research, check out the section on AI Tools .

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Trapped in dissertation revisions?

Qualitative research questions, published by steve tippins on may 17, 2024 may 17, 2024.

Last Updated on: 17th May 2024, 05:05 am

If you’re writing a proposal for a qualitative dissertation, you will need to create qualitative research questions. Getting these right the first time means you’ll save time revising and going back and forth with your committee. So, how do you do that? The key is alignment. 

By the time you write your qualitative research questions, you should have already written your Problem Statement and Purpose Statement. Your qualitative research questions should be based on your Problem Statement and Purpose Statement. 

If your research questions start heading in a different direction from your problem statement, purpose, and title, then your committee will say you’re not in alignment. This means that your research questions will not allow you to address the problem you’ve identified.

Examples of Qualitative Research Questions

Some examples of a qualitative research question include:

“What are the perceptions of teachers in central Arkansas about the use of a high-quality math curriculum?”

“What are the lived experiences of first responders who have worked through a traumatic event?”

“What are the perceptions of hourly employees about policies related to sick time?”

“What do employees in the private security industry report as their perceptions of increased overtime work?”

“What do doctoral students perceive to be the optimal level of support from their committees?”

The research questions will be supported by interview questions. These are the questions you will actually ask study participants. They will provide many rich responses that will then allow you to develop codes and ultimately themes, which will then be used to answer the qualitative research questions.

How to Write a Qualitative Research Question

If you’re doing a qualitative study, you’ll  want to make sure that your problem statement says that you’re looking for something like “perceptions” or “lived experiences” as opposed to “significance” or “relationships.” That’s because in qualitative research, we don’t deal with significance or relationships. We don’t involve enough people to be able to use statistical tests that generate reliable and significant results.

However, what we can do in qualitative research is understand people’s perceptions, lived experiences, and the approaches they take to address problems.

With qualitative research questions, we do not have null and alternative hypotheses as we do in quantitative research. We just have research questions.  Null and alternative hypotheses are part of quantitative testing, and we aren’t testing in qualitative research.

Keep Your Research Questions Specific

In the design of the qualitative research question, if you stick to the problem statement and purpose, you will not find yourself with questions that, while interesting, will not allow you to address the problem statement.

For example, let’s say the Problem Statement is, “Hourly employee’s perceptions of transformational leadership in the food and beverage industry in Northern Illinois is unknown.”

A too-broad research question is, “What are employees perceptions of their leaders?” Here you’ll find out about their leaders, but you won’t find out about transformational leadership. You might also find out about leaders in other industries or other locations.

A better research question would be: “What are employee perceptions of leaders who use transformational leadership style in the food and beverage industry in Northern Illinois?”

Over 50% of doctoral candidates don’t finish their dissertations.

Avoid Leading Questions

You want to make sure that your research questions and interview questions are as objective as possible and not designed to get a specific answer. For example, if an interview question was, “how much do you like the new healthcare plan?” you’ve pretty much defined the field as they like it. You’re assuming they like it. You’ve come up with a biased question. And biased questions give you biased answers and your results end up having little validity.

This gets to the notion of “just answering the question” as opposed to “I know that I want to prove a specific idea or concept when doing my research.” Your job is to answer the question. You add a little more information to the pile of knowledge so that we overall start to understand things.

For example, in 1930, we proved that Pluto was a planet. Then in 2007, we determined that Pluto was no longer a planet. And now, we’re reconsidering it. The word “proof” is difficult in any research. Rather than trying to prove something, we simply add a little more knowledge to the field. Then over time, it becomes the preponderance of evidence that leads us to support a certain position, until there’s evidence contrary.

So in the creation of knowledge in the scientific method, if you come up with a new theory, it has to do everything the old theory did and more, if it’s going to take its place. 

Qualitative Research Questions: Summary

Qualitative research questions work best when they are designed in concert with your problem statement and purpose, are specific, are not leading, and lead to the ability to address the problem as stated in the research.

Steve Tippins

Steve Tippins, PhD, has thrived in academia for over thirty years. He continues to love teaching in addition to coaching recent PhD graduates as well as students writing their dissertations. Learn more about his dissertation coaching and career coaching services. Book a Free Consultation with Steve Tippins

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50 Best Finance Dissertation Topics For Research Students

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Finance Dissertation Made Easier!

Embarking on your dissertation adventure? Look no further! Choosing the right finance dissertation topics is like laying the foundation for your research journey in Finance, and we're here to light up your path. In this blog, we're diving deep into why dissertation topics in finance matter so much. We've got some golden writing tips to share with you! We're also unveiling the secret recipe for structuring a stellar finance dissertation and exploring intriguing topics across various finance sub-fields. Whether you're captivated by cryptocurrency, risk management strategies, or exploring the wonders of Internet banking, microfinance, retail and commercial banking - our buffet of Finance dissertation topics will surely set your research spirit on fire!

What is a Finance Dissertation?

Finance dissertations are academic papers that delve into specific finance topics chosen by students, covering areas such as stock markets, banking, risk management, and healthcare finance. These dissertations require extensive research to create a compelling report and contribute to the student's confidence and satisfaction in the field of Finance. Now, let's understand why these dissertations are so important and why choosing the right Finance dissertation topics is crucial!

Why Are Finance Dissertation Topics Important?

Choosing the dissertation topics for Finance students is essential as it will influence the course of your research. It determines the direction and scope of your study. You must make sure that the Finance dissertation topics you choose are relevant to your field of interest, or you may end up finding it more challenging to write. Here are a few reasons why finance thesis topics are important:

1. Relevance

Opting for relevant finance thesis topics ensures that your research contributes to the existing body of knowledge and addresses contemporary issues in the field of Finance. Choosing a dissertation topic in Finance that is relevant to the industry can make a meaningful impact and advance understanding in your chosen area.

2. Personal Interest

Selecting Finance dissertation topics that align with your interests and career goals is vital. When genuinely passionate about your research area, you are more likely to stay motivated during the dissertation process. Your interest will drive you to explore the subject thoroughly and produce high-quality work.

3. Future Opportunities

Well-chosen Finance dissertation topics can open doors to various future opportunities. It can enhance your employability by showcasing your expertise in a specific finance area. It may lead to potential research collaborations and invitations to conferences in your field of interest.

4. Academic Supervision

Your choice of topics for dissertation in Finance also influences the availability of academic supervisors with expertise in your chosen area. Selecting a well-defined research area increases the likelihood of finding a supervisor to guide you effectively throughout the dissertation. Their knowledge and guidance will greatly contribute to the success of your research.

Writing Tips for Finance Dissertation

A lot of planning, formatting, and structuring goes into writing a dissertation. It starts with deciding on topics for a dissertation in Finance and conducting tons of research, deciding on methods, and so on. However, you can navigate the process more effectively with proper planning and organisation. Below are some tips to assist you along the way, and here is a blog on the 10 tips on writing a dissertation that can give you more information, should you need it!

1. Select a Manageable Topic

Choosing Finance research topics within the given timeframe and resources is important. Select a research area that interests you and aligns with your career goals. It will help you stay inspired throughout the dissertation process.

2. Conduct a Thorough Literature Review

A comprehensive literature review forms the backbone of your research. After choosing the Finance dissertation topics, dive deep into academic papers, books, and industry reports, gaining a solid understanding of your chosen area to identify research gaps and establish the significance of your study.

3. Define Clear Research Objectives

Clearly define your dissertation's research questions and objectives. It will provide a clear direction for your research and guide your data collection, analysis, and overall structure. Ensure your objectives are specific, measurable, achievable, relevant, and time-bound (SMART).

4. Collect and Analyse Data

Depending on your research methodology and your Finance dissertation topics, collect and analyze relevant data to support your findings. It may involve conducting surveys, interviews, experiments, and analyzing existing datasets. Choose appropriate statistical techniques and qualitative methods to derive meaningful insights from your data.

5. Structure and Organization

Pay attention to the structure and organization of your dissertation. Follow a logical progression of chapters and sections, ensuring that each chapter contributes to the overall coherence of your study. Use headings, subheadings, and clear signposts to guide the reader through your work.

6. Proofread and Edit

Once you have completed the writing process, take the time to proofread and edit your dissertation carefully. Check for clarity, coherence, and proper grammar. Ensure that your arguments are well-supported, and eliminate any inconsistencies or repetitions. Pay attention to formatting, citation styles, and consistency in referencing throughout your dissertation.

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Finance Dissertation Topics

Now that you know what a finance dissertation is and why they are important, it's time to have a look at some of the best Finance dissertation topics. For your convenience, we have segregated these topics into categories, including cryptocurrency, risk management, internet banking, and so many more. So, let's dive right in and explore the best Finance dissertation topics:

Dissertation topics in Finance related to Cryptocurrency

1. The Impact of Regulatory Frameworks on the Volatility and Liquidity of Cryptocurrencies.

2. Exploring the Factors Influencing Cryptocurrency Adoption: A Comparative Study.

3. Assessing the Efficiency and Market Integration of Cryptocurrency Exchanges.

4. An Analysis of the Relationship between Cryptocurrency Prices and Macroeconomic Factors.

5. The Role of Initial Coin Offerings (ICOs) in Financing Startups: Opportunities and Challenges.

Dissertation topics in Finance related to Risk Management

1. The Effectiveness of Different Risk Management Strategies in Mitigating Financial Risks in Banking Institutions.

2. The Role of Derivatives in Hedging Financial Risks: A Comparative Study.

3. Analyzing the Impact of Risk Management Practices on Firm Performance: A Case Study of a Specific Industry.

4. The Use of Stress Testing in Evaluating Systemic Risk: Lessons from the Global Financial Crisis.

5. Assessing the Relationship between Corporate Governance and Risk Management in Financial Institutions.

Dissertation topics in Finance related to Internet Banking

1. Customer Adoption of Internet Banking: An Empirical Study on Factors Influencing Usage.

Enhancing Security in Internet Banking: Exploring Biometric Authentication Technologies.

2. The Impact of Mobile Banking Applications on Customer Engagement and Satisfaction.

3. Evaluating the Efficiency and Effectiveness of Internet Banking Services in Emerging Markets.

4. The Role of Social Media in Shaping Customer Perception and Adoption of Internet Banking.

Dissertation topics in Finance related to Microfinance

1. The Impact of Microfinance on Poverty Alleviation: A Comparative Study of Different Models.

2. Exploring the Role of Microfinance in Empowering Women Entrepreneurs.

3. Assessing the Financial Sustainability of Microfinance Institutions in Developing Countries.

4. The Effectiveness of Microfinance in Promoting Rural Development: Evidence from a Specific Region.

5. Analyzing the Relationship between Microfinance and Entrepreneurial Success: A Longitudinal Study.

Dissertation topics in Finance related to Retail and Commercial Banking

1. The Impact of Digital Transformation on Retail and Commercial Banking: A Case Study of a Specific Bank.

2. Customer Satisfaction and Loyalty in Retail Banking: An Analysis of Service Quality Dimensions.

3. Analyzing the Relationship between Bank Branch Expansion and Financial Performance.

4. The Role of Fintech Startups in Disrupting Retail and Commercial Banking: Opportunities and Challenges.

5. Assessing the Impact of Mergers and Acquisitions on the Performance of Retail and Commercial Banks.

Dissertation topics in Finance related to Alternative Investment

1. The Performance and Risk Characteristics of Hedge Funds: A Comparative Analysis.

2. Exploring the Role of Private Equity in Financing and Growing Small and Medium-Sized Enterprises.

3. Analyzing the Relationship between Real Estate Investments and Portfolio Diversification.

4. The Potential of Impact Investing: Evaluating the Social and Financial Returns.

5. Assessing the Risk-Return Tradeoff in Cryptocurrency Investments: A Comparative Study.

Dissertation topics in Finance related to International Affairs

1. The Impact of Exchange Rate Volatility on International Trade: A Case Study of a Specific Industry.

2. Analyzing the Effectiveness of Capital Controls in Managing Financial Crises: Comparative Study of Different Countries.

3. The Role of International Financial Institutions in Promoting Economic Development in Developing Countries.

4. Evaluating the Implications of Trade Wars on Global Financial Markets.

5. Assessing the Role of Central Banks in Managing Financial Stability in a Globalized Economy.

Dissertation topics in Finance related to Sustainable Finance

1. The impact of sustainable investing on financial performance.

2. The role of green bonds in financing climate change mitigation and adaptation.

3. The development of carbon markets.

4. The use of environmental, social, and governance (ESG) factors in investment decision-making.

5. The challenges and opportunities of sustainable Finance in emerging markets.

Dissertation topics in Finance related to Investment Banking

1. The valuation of distressed assets.

2. The pricing of derivatives.

3. The risk management of financial institutions.

4. The regulation of investment banks.

5. The impact of technology on the investment banking industry.

Dissertation topics in Finance related to Actuarial Science

1. The development of new actuarial models for pricing insurance products.

2. The use of big data in actuarial analysis.

3. The impact of climate change on insurance risk.

4. The design of pension plans that are sustainable in the long term.

5. The use of actuarial science to manage risk in other industries, such as healthcare and Finance.

Tips To Find Good Finance Dissertation Topics 

Embarking on a financial dissertation journey requires careful consideration of various factors. Your choice of topic in finance research topics is pivotal, as it sets the stage for the entire research process. Finding a good financial dissertation topic is essential to blend your interests with the current trends in the financial landscape. We suggest the following tips that can help you pick the perfect dissertation topic:

1. Identify your interests and strengths 

2. Check for current relevance

3. Feedback from your superiors

4. Finalise the research methods

5. Gather the data

6. Work on the outline of your dissertation

7. Make a draft and proofread it

In this blog, we have discussed the importance of finance thesis topics and provided valuable writing tips and tips for finding the right topic, too. We have also presented a list of topics within various subfields of Finance. With this, we hope you have great ideas for finance dissertations. Good luck with your finance research journey!

Frequently Asked Questions

How do i research for my dissertation project topics in finance, what is the best topic for dissertation topics for mba finance, what is the hardest finance topic, how do i choose the right topic for my dissertation in finance, where can i find a dissertation topic in finance.

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AI-assisted writing is quietly booming in academic journals. Here’s why that’s OK

Lecturer in Bioethics, Monash University & Honorary fellow, Melbourne Law School, Monash University

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Julian Koplin does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

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If you search Google Scholar for the phrase “ as an AI language model ”, you’ll find plenty of AI research literature and also some rather suspicious results. For example, one paper on agricultural technology says:

As an AI language model, I don’t have direct access to current research articles or studies. However, I can provide you with an overview of some recent trends and advancements …

Obvious gaffes like this aren’t the only signs that researchers are increasingly turning to generative AI tools when writing up their research. A recent study examined the frequency of certain words in academic writing (such as “commendable”, “meticulously” and “intricate”), and found they became far more common after the launch of ChatGPT – so much so that 1% of all journal articles published in 2023 may have contained AI-generated text.

(Why do AI models overuse these words? There is speculation it’s because they are more common in English as spoken in Nigeria, where key elements of model training often occur.)

The aforementioned study also looks at preliminary data from 2024, which indicates that AI writing assistance is only becoming more common. Is this a crisis for modern scholarship, or a boon for academic productivity?

Who should take credit for AI writing?

Many people are worried by the use of AI in academic papers. Indeed, the practice has been described as “ contaminating ” scholarly literature.

Some argue that using AI output amounts to plagiarism. If your ideas are copy-pasted from ChatGPT, it is questionable whether you really deserve credit for them.

But there are important differences between “plagiarising” text authored by humans and text authored by AI. Those who plagiarise humans’ work receive credit for ideas that ought to have gone to the original author.

By contrast, it is debatable whether AI systems like ChatGPT can have ideas, let alone deserve credit for them. An AI tool is more like your phone’s autocomplete function than a human researcher.

The question of bias

Another worry is that AI outputs might be biased in ways that could seep into the scholarly record. Infamously, older language models tended to portray people who are female, black and/or gay in distinctly unflattering ways, compared with people who are male, white and/or straight.

This kind of bias is less pronounced in the current version of ChatGPT.

However, other studies have found a different kind of bias in ChatGPT and other large language models : a tendency to reflect a left-liberal political ideology.

Any such bias could subtly distort scholarly writing produced using these tools.

The hallucination problem

The most serious worry relates to a well-known limitation of generative AI systems: that they often make serious mistakes.

For example, when I asked ChatGPT-4 to generate an ASCII image of a mushroom, it provided me with the following output.

It then confidently told me I could use this image of a “mushroom” for my own purposes.

These kinds of overconfident mistakes have been referred to as “ AI hallucinations ” and “ AI bullshit ”. While it is easy to spot that the above ASCII image looks nothing like a mushroom (and quite a bit like a snail), it may be much harder to identify any mistakes ChatGPT makes when surveying scientific literature or describing the state of a philosophical debate.

Unlike (most) humans, AI systems are fundamentally unconcerned with the truth of what they say. If used carelessly, their hallucinations could corrupt the scholarly record.

Should AI-produced text be banned?

One response to the rise of text generators has been to ban them outright. For example, Science – one of the world’s most influential academic journals – disallows any use of AI-generated text .

I see two problems with this approach.

The first problem is a practical one: current tools for detecting AI-generated text are highly unreliable. This includes the detector created by ChatGPT’s own developers, which was taken offline after it was found to have only a 26% accuracy rate (and a 9% false positive rate ). Humans also make mistakes when assessing whether something was written by AI.

It is also possible to circumvent AI text detectors. Online communities are actively exploring how to prompt ChatGPT in ways that allow the user to evade detection. Human users can also superficially rewrite AI outputs, effectively scrubbing away the traces of AI (like its overuse of the words “commendable”, “meticulously” and “intricate”).

The second problem is that banning generative AI outright prevents us from realising these technologies’ benefits. Used well, generative AI can boost academic productivity by streamlining the writing process. In this way, it could help further human knowledge. Ideally, we should try to reap these benefits while avoiding the problems.

The problem is poor quality control, not AI

The most serious problem with AI is the risk of introducing unnoticed errors, leading to sloppy scholarship. Instead of banning AI, we should try to ensure that mistaken, implausible or biased claims cannot make it onto the academic record.

After all, humans can also produce writing with serious errors, and mechanisms such as peer review often fail to prevent its publication.

We need to get better at ensuring academic papers are free from serious mistakes, regardless of whether these mistakes are caused by careless use of AI or sloppy human scholarship. Not only is this more achievable than policing AI usage, it will improve the standards of academic research as a whole.

This would be (as ChatGPT might say) a commendable and meticulously intricate solution.

• Artificial intelligence (AI)
• Academic journals
• Academic publishing
• Hallucinations
• Scholarly publishing
• Academic writing
• Large language models
• Generative AI

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• Knowledge Base
• Dissertation
• How to Write a Discussion Section | Tips & Examples

How to Write a Discussion Section | Tips & Examples

Published on 21 August 2022 by Shona McCombes . Revised on 25 October 2022.

The discussion section is where you delve into the meaning, importance, and relevance of your results .

It should focus on explaining and evaluating what you found, showing how it relates to your literature review , and making an argument in support of your overall conclusion . It should not be a second results section .

There are different ways to write this section, but you can focus your writing around these key elements:

• Summary: A brief recap of your key results
• Interpretations: What do your results mean?
• Implications: Why do your results matter?
• Limitations: What can’t your results tell us?
• Recommendations: Avenues for further studies or analyses

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Table of contents

What not to include in your discussion section, step 1: summarise your key findings, step 2: give your interpretations, step 3: discuss the implications, step 4: acknowledge the limitations, step 5: share your recommendations, discussion section example.

There are a few common mistakes to avoid when writing the discussion section of your paper.

• Don’t introduce new results: You should only discuss the data that you have already reported in your results section .
• Don’t make inflated claims: Avoid overinterpretation and speculation that isn’t directly supported by your data.
• Don’t undermine your research: The discussion of limitations should aim to strengthen your credibility, not emphasise weaknesses or failures.

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Start this section by reiterating your research problem  and concisely summarising your major findings. Don’t just repeat all the data you have already reported – aim for a clear statement of the overall result that directly answers your main  research question . This should be no more than one paragraph.

Many students struggle with the differences between a discussion section and a results section . The crux of the matter is that your results sections should present your results, and your discussion section should subjectively evaluate them. Try not to blend elements of these two sections, in order to keep your paper sharp.

• The results indicate that …
• The study demonstrates a correlation between …
• This analysis supports the theory that …
• The data suggest  that …

The meaning of your results may seem obvious to you, but it’s important to spell out their significance for your reader, showing exactly how they answer your research question.

The form of your interpretations will depend on the type of research, but some typical approaches to interpreting the data include:

• Identifying correlations , patterns, and relationships among the data
• Discussing whether the results met your expectations or supported your hypotheses
• Contextualising your findings within previous research and theory
• Explaining unexpected results and evaluating their significance
• Considering possible alternative explanations and making an argument for your position

You can organise your discussion around key themes, hypotheses, or research questions, following the same structure as your results section. Alternatively, you can also begin by highlighting the most significant or unexpected results.

• In line with the hypothesis …
• Contrary to the hypothesised association …
• The results contradict the claims of Smith (2007) that …
• The results might suggest that x . However, based on the findings of similar studies, a more plausible explanation is x .

As well as giving your own interpretations, make sure to relate your results back to the scholarly work that you surveyed in the literature review . The discussion should show how your findings fit with existing knowledge, what new insights they contribute, and what consequences they have for theory or practice.

Ask yourself these questions:

• Do your results support or challenge existing theories? If they support existing theories, what new information do they contribute? If they challenge existing theories, why do you think that is?
• Are there any practical implications?

Your overall aim is to show the reader exactly what your research has contributed, and why they should care.

• These results build on existing evidence of …
• The results do not fit with the theory that …
• The experiment provides a new insight into the relationship between …
• These results should be taken into account when considering how to …
• The data contribute a clearer understanding of …
• While previous research has focused on  x , these results demonstrate that y .

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Even the best research has its limitations. Acknowledging these is important to demonstrate your credibility. Limitations aren’t about listing your errors, but about providing an accurate picture of what can and cannot be concluded from your study.

Limitations might be due to your overall research design, specific methodological choices , or unanticipated obstacles that emerged during your research process.

Here are a few common possibilities:

• If your sample size was small or limited to a specific group of people, explain how generalisability is limited.
• If you encountered problems when gathering or analysing data, explain how these influenced the results.
• If there are potential confounding variables that you were unable to control, acknowledge the effect these may have had.

After noting the limitations, you can reiterate why the results are nonetheless valid for the purpose of answering your research question.

• The generalisability of the results is limited by …
• The reliability of these data is impacted by …
• Due to the lack of data on x , the results cannot confirm …
• The methodological choices were constrained by …
• It is beyond the scope of this study to …

Based on the discussion of your results, you can make recommendations for practical implementation or further research. Sometimes, the recommendations are saved for the conclusion .

Suggestions for further research can lead directly from the limitations. Don’t just state that more studies should be done – give concrete ideas for how future work can build on areas that your own research was unable to address.

• Further research is needed to establish …
• Future studies should take into account …
• Avenues for future research include …

Cite this Scribbr article

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McCombes, S. (2022, October 25). How to Write a Discussion Section | Tips & Examples. Scribbr. Retrieved 14 May 2024, from https://www.scribbr.co.uk/thesis-dissertation/discussion/

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