dissertation surveys

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!

Sign up now

Free unlimited surveys, questions and responses.

Dissertation & Thesis Survey Design 101

5 Common Mistakes To Avoid (+ Examples)

By: David Phair (PhD) & Kerryn Warren (PhD) | April 2022

Surveys are a powerful way to collect data for your dissertation, thesis or research project. Done right, a good survey allows you to collect large swathes of useful data with (relatively) little effort. However, if not designed well, you can run into serious issues.

Over the years, we’ve encountered numerous common mistakes students make when it comes to survey design. In this post, we’ll unpack five of these costly mistakes.

Overview: 5 Survey Design Mistakes

• Having poor overall survey structure and flow
• Using poorly constructed questions and/or statements
• Implementing inappropriate response types
• Using unreliable and/or invalid scales  and measures
• Designing without consideration for analysis techniques

Mistake #1: Having poor structure and flow

One of the most common issues we see is poor overall survey structure and flow . If a survey is designed badly, it will discourage participants from completing it. As a result, few participants will take the time to respond to the survey, which can lead to a small sample size and poor or even unusable results . Let’s look at a few best practices to ensure good overall structure and flow.

1. Make sure your survey is aligned with your study’s “golden thread”.

The first step might seem obvious, but it’s important to develop survey questions that are tightly aligned with your research question(s), aims and objectives – in other words, “your golden thread”. Your survey serves to generate the data that will answer these key ideas in your thesis; if it doesn’t do that, you’ve got a serious problem. To put it simply, it’s critically important to design your survey questions with the golden thread of your study front of mind at all times.

2. Order your questions in an intuitive, logical way.

The types of questions you ask and when you ask them are vital aspects when designing an effective survey. To avoid losing respondents, you need to order your questions clearly and logically.

In general, it’s a good idea to ask exclusion questions upfront . For example, if your research is focused on an aspect of women’s lives, your first question should be one to determine the gender of the respondent (and filter out unsuitable respondents). Once that’s out of the way, the exclusion questions can be followed by questions related to the key constructs or ideas and/or the dependent and independent variables in your study.

Lastly, the demographics-related questions are usually positioned at the end of the survey. These are questions related to the characteristics of your respondents (e.g., age, race, occupation). It’s a good idea to position these questions at the end of your survey because respondents can get caught up in these identity-related questions as they move through the rest of your survey. Placing them at the end of your survey helps ensure that the questions related to the core constructs of your study will have the respondents’ full attention.

3. Design for user experience and ease of use.

This might seem obvious, but it’s essential to carefully consider your respondents’ “journey” when designing your survey. In other words, you need to keep user experience and engagement front of mind when designing your survey.

One way of creating a good user experience is to have a clear introduction or cover page upfront. On this intro page, it’s good to communicate the estimated time required to complete the survey (generally, 15 to 20 minutes is reasonable). Also, make u se of headings and short explainers to help respondents understand the context of each question or section in your survey. It’s also helpful if you provide a progress indicator to indicate how far they are in completing the survey.

Naturally, readability is important to a successful survey. So, keep the survey content as concise as possible, as people tend to drop out of long surveys. A general rule of thumb is to make use of plain, easy-to-understand language . Related to this, always carefully edit and proofread your survey before launching it. Typos, grammar and formatting issues will heavily detract from the credibility of your work and will likely increase respondent dropout.

In cases where you have no choice but to use a technical term or industry jargon, be sure to explain the meaning (define the term) first. You don’t want respondents to be distracted or confused by the technical aspects of your survey. In addition to this, create a logical flow by grouping related topics together and moving from general to more specific questions.

You should also think about what devices respondents will use to access your survey. Because many people use their phones to complete your survey, making it mobile-friendly means more people will be able to respond, which is hugely beneficial. By hosting your survey on a trusted provider (e.g., SurveyMonkey or Qualtrix), the mobile aspect should be taken care of, but always test your survey on a few devices.  Aside from making the data collection easier, using a well-established survey platform will also make processing your survey data easier.

4.  Prioritise ethics and data privacy.

The last (and very important) point to consider when designing your survey is the ethical requirements. Your survey design must adhere to all ethics policies and data protection laws of your country. If you (or your respondents) are in Europe for instance, you’ll need to comply with GDPR. It’s also essential to highlight to your respondents that all data collected will be handled and stored securely , to minimise any concerns about the confidentiality and safety of their data.

Mistake #2: Using poorly constructed questions

Another common survey design issue we encounter is poorly constructed questions and statements. There are a few ways in which questions can be poorly constructed. These usually fall into four broad categories: 

• Loaded questions
• Leading questions
• Double-barreled questions
• Vague questions 

Let’s look at each of these. 

A loaded question assumes something about the respondent without having any data to support that assumption. For example, if the question asks, “Where is your favourite place to eat steak?”, it assumes that the respondent eats steak. Clearly, this is problematic for respondents that are vegetarians or vegans, or people that simply don’t like steak. 

A leading question pushes the respondent to answer in a certain way. For example, a question such as, “How would you rate the excellent service at our restaurant?” is trying to influence the way that the respondent thinks about the service at the restaurant. This can be annoying to the respondent (at best) or lead them to respond in a way they wouldn’t have, had the question been more objective.

Need a helping hand?

A double-barreled question is a question that contains two (or more) variables within it. It essentially tries to ask two questions at the same time. An example of this is

“ Do you enjoy eating peanut butter and cheese on bread?”

As you can see, this question makes it unclear whether you are being asked about whether they like eating the two together on bread, or whether they like eating one at a time. This is problematic, as there are multiple ways to interpret this question, which means that the resultant data will be unusable. 

A vague question , as the name suggests, is one where it is unclear what is being asked or one that is very open-ended . Of course, sometimes you do indeed want open questions, as they can provide richer information from respondents. However, if you ask a vague question, you’ll likely get a vague answer. So, you need to be careful. Consider the following fairly vague question:

“What was your experience at this restaurant?”. 

A respondent could answer this question by just saying “good” or “bad” – or nothing at all. This isn’t particularly helpful. Alternatively, someone might respond extensively about something unrelated to the question. If you want to ask open-ended questions, interviewing may be a better (or additional) data method to consider, so give some thought to what you’re trying to achieve. Only use open-ended questions in a survey if they’re central to your research aims . 

To make sure that your questions don’t fall into one of these problematic categories, it’s important to keep your golden thread (i.e., your research aims, objectives and research questions ) in mind and consider the type of data you want to generate. Also, it’s always a good idea to make use of a pilot study to test your survey questions and responses to see whether any questions are problematic and whether the data generated is useful.

Mistake #3: Using inappropriate response types

When designing your survey, it’s essential to choose the best-suited response type/format for each question. In other words, you need to consider how the respondents will input their responses into your survey. Broadly speaking, there are three response types .

The first response type is categorical.  

These are questions where the respondent will choose one of the pre-determined options that you provide, for example: yes/no, gender, ethnicity, etc.

For categorical responses, there will be a limited number of choices and respondents will only be able to pick one. This is useful for basic demographic data where all potential responses can be easily grouped into categories. 

The second response type is scales . 

Scales offer respondents the opportunity to express their opinion on a spectrum . For example, you could design a 3-point scale with the options of agree, neutral and disagree. Scales are useful when you’re trying to assess the extent to which respondents agree with specific statements or claims. This data can then be statistically analysed in powerful ways. 

Scales can, however, be problematic if they have too many or too few points . For example, if you only have “strongly agree”, “neutral” and “strongly disagree”, your respondent might resort to selecting “neutral” because they don’t feel strongly about the subject. Conversely, if there are too many points on the scale, your respondents might take too much time to complete the survey and become frustrated in the process of agonising over what exactly they feel. 

The third response type is the free form text box (open-ended response). 

We mentioned open-ended questions earlier and looked at some of the ways in which they can be problematic. But, because free-form responses are useful for understanding nuances and finer details, this response type does have its benefits. For example, some respondents might have a problem with how the other questions in your survey are presented or asked, and therefore an open-ended response option gives them an opportunity to respond in a way that reflects their true feelings. 

As you can see, it’s important to carefully consider which response types you use, as each one has its own purpose, pros and cons . Make sure that each response option is appropriate for the type of question and generates data that you will be able to analyse in a meaningful way.

It’s also good to keep in mind that you as the researcher will need to process all the data generated by the survey. Therefore, you need to consider how you will analyse the data from each response type. Use the response type that makes sense for the specific question and keep the analysis aspect in mind when choosing your response types.

Mistake #4: Using poorly design scales/measures

We’ve spoken about the design of the survey as a whole, but it’s also important to think carefully about the design of individual measures/scales. Theoretical constructs are typically measured using Likert scales. To measure these constructs effectively, you’ll need to ensure that your scales produce valid and reliable data.

Validity refers to whether the scale measures what you’re trying to measure . This might sound like a no-brainer, but oftentimes people can interpret questions or statements in diverse ways. Therefore, it’s important to think of whether the interpretations of the responses to each measure are sound relative to the original construct you are measuring and the existing literature relating to it.

Reliability, on the other hand, is related to whether multiple scales measuring the same construct get the same response (on average, of course). In other words, if you have three scales measuring employee satisfaction, they should correlate, as they all measure the same construct. A good survey should make use of multiple scales to measure any given construct, and these should “move” together – in other words, be “reliable”.

If you’re designing a survey, you’ll need to demonstrate the validity and reliability of your measures. This can be done in several ways, using both statistical and non-statistical techniques. We won’t get into detail about those here, but it’s important to remember that validity and reliability are central to making sure that your survey is measuring what it is meant to measure.

Importantly, when thinking about the scales for your survey, you don’t need to reinvent the wheel. There are pre-developed and tested scales available for most areas of research, and it’s preferable to use a “tried and tested” scale, rather than developing one from scratch. If there isn’t already something that fits your research, you can often modify existing scales to suit your specific needs.

Mistake #5: Not designing with analysis in mind

Naturally, you’ll want to use the data gathered from your survey as effectively as possible. Therefore, it’s always a good idea to start with the end (i.e., the analysis phase) in mind when designing your survey. The analysis methods that you’ll be able to use in your study will be dictated by the design of the survey, as it will produce certain types of data. Therefore, it’s essential that you design your survey in a way that will allow you to undertake the analyses you need to achieve your research aims. 

Importantly, you should have a clear idea of what statistical methods you plan to use before you start designing your survey. Be clear about which specific descriptive and inferential tests you plan to do (and why). Make sure that you understand the assumptions of all the statistical tests you’ll be using and the type of data (i.e., nominal, ordinal, interval, or ratio ) that each test requires. Only once you have that level of clarity can you get started designing your survey. 

Finally, and as we’ve emphasized before, it’s essential that you keep your study’s golden thread front of mind during the design process. If your analysis methods don’t aid you in answering your research questions, they’ll be largely useless. So, keep the big picture and the end goal front of mind from the outset.

Recap: Survey Design Mistakes

In this post we’ve discussed some important aspects of survey design and five common mistakes to avoid while designing your own survey. To recap, these include:

If you have any questions about these survey design mistakes, drop a comment below. Alternatively, if you’re interested in getting  1-on-1 help with your research , check out our dissertation coaching service or book a free initial consultation with a friendly coach.

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 ...

You Might Also Like:

Thank you much for this article. I really appreciate it.

Please do you handle someone’s project write up or you can guide someone through out the project write up?

Very useful and understandable for a user like me. I thank you very much !!

Submit a Comment Cancel reply

Your email address will not be published. Required fields are marked *

Save my name, email, and website in this browser for the next time I comment.

• Print Friendly

Quantitative Research

Qualitative research.

• Free plan, no time limit
• Set up in minutes
• No credit card required

7+ Reasons to Use Surveys in Your Dissertation

Writing a dissertation is a serious milestone. Your degree depends on it, so it takes a lot of effort and time to figure out what direction to choose. Everything starts with the topic: you read background literature, consult with your supervisor and seek approval before you start writing the first draft. After that, you need to decide how you will collect the data that is supposed to contribute to the research field.

This is where it gets complicated. If you have never tried conducting primary research (i.e. working with human subjects), it can seem quite scary. Analyzing articles may sound like the safest and the coolest option. Yet, there might not be enough information for you to claim that your research is somehow novel.

To make sure it is, you might need to conduct primary research, and the survey method is the most widespread tool to do that. The number of advantages surveys present is huge. However, there are various perks depending on what approach you pursue. So, let’s go through all of them before you decide to pay for essay and order a dissertation that will go on and on about analyzing literature and nothing else except it.

In the quantitative primary research, students have to calculate the data received from typical a, b, c, d questionnaires. The latter provides precise answers and helps prove or reject the formulated hypothesis. For the research to be legit, there are several stages to go through like:

• Discarding irrelevant or subjective questions/answers included in questionnaires.
• Setting criteria for credible answers.
• Composing an explanation of how you will manage ethical concerns (for participants and university committee).

However, all this is done to prevent issues in the future. Provided you have taken care of all the points above, you will get to enjoy the following benefits.

Data Collection Is Less Tedious

There are numerous services, like Survey Monkey, that the best write my essay services use. It can help you distribute your questionnaire among potential participants. These platforms simplify the data collection process. You don’t have to arrange calls or convince someone that they can safely share the information. Just upload the consent letter each participant has to sign and let the platform guide them further.

Data Analysis Is Fast

In quantitative analysis, all you have to take care of is mainly data entry. It requires focus and accuracy, but the rest can be done with the help of software. Whether it’s ordinary Excel or something like SPSS, you don’t have to reread loads of text. Just make sure you download the collected data from the platform correctly, remove irrelevant fields, and feed the rest to your computer.

Numbers Rule

Numbers don’t lie (unless you miscalculated them, of course). They give a clear answer: it’s either ‘yes’ or ‘no’. Moreover, they leave more room for creating good visuals and making your paper less boring. Just make sure you explain the numbers properly and compare the results between various graphs and charts.

No Room For Subjectivity

A quantitative dissertation is mostly a technical paper. It’s not about creativity and your ability to impress like in admission essays students usually delegate to admission essay writing services to avoid babbling about things they deem senseless. It’s about following particular procedures. And there is also a less abstract analysis.

Qualitative-oriented surveys are about conducting full-fledged personal interviews, working with focus groups, or distributing open-ended questionnaires requiring short but unique answers. Let’s talk about what makes this approach worth trying!

First-Hand Experience

The ability to gain a unique perspective is what distinguishes interviews from other surveys. Close-ended questions may be too rigid and make participants omit a lot of information that might help the research. In an interview, you may also correct some of your questions, and add more details to them, thus improving the outcomes.

More Diverse and Honest Answers

When participants are limited by only several options, they might choose something they cannot fully relate to. So, there is no guarantee that the results will be authentic. Meanwhile, with open-ended questions, participants share a lot of details.

Sure, some of them may be less relevant to your topic, but the researcher gains a deeper understanding of the issues lying beneath the topic. Of course, all of it is guaranteed only if the researcher provides anonymity and a safe space for the interviewees to share their thoughts freely.

No Need For Complex Software

In contrast to quantitative analysis, here, you won’t have to use formulae and learn how to perform complex tests. You might not even need Excel, except for storing some data about your participants. However, no calculations will be needed, which is also a relief for those who are not used to working with such kind of data.

Both types of research have also other advantages:

• With surveys, you have more chances to fill the literature gap you’ve discovered.
• Primary research may not be quite easy, but it’s highly valued at the doctoral level of education.
• You receive a lot of new information and stay away from retelling literature that has been published before.
• Primary research is less boring.

However, there is a must-remember thing: not every supervisor or university committee approves of surveys and primary research in general. It depends on numerous aspects like topic and subject, the conditions of research, your approach to handling human subjects, etc.

It means that the methodology you are going to use should be approved by your professor first. Otherwise, you may have to discard some parts of your draft and lose time gathering data you won’t be able to use. So, take care and good luck!

7+ Reasons to Use Surveys in Your Dissertation FAQ

What are the benefits of using surveys in a dissertation, surveys can provide a large amount of data in a short amount of time, they are cost-effective and can allow for anonymity, they can reach a wide audience, and they can be used to obtain feedback from the participants., how can i ensure that my survey results are accurate, make sure to ask questions that are clear and concise and that there are no bias in the questions. make sure to have a good sample size and to have a response rate that is high enough to provide accurate results., how can i analyze the survey results, depending on the type of survey, there are various analysis techniques that can be used. these include descriptive statistics, inferential statistics, correlation analysis, and regression analysis., what are the limitations of surveys, surveys can be subject to sampling errors, response bias, and interviewer effects. they may also not be able to capture the full range of opinions and attitudes of the population., like what you see share with a friend..

Sarath Shyamson

Sarath Shyamson is the customer success person at BlockSurvey and also heads the outreach. He enjoys volunteering for the church choir and loves spending time with his two year old son.

Related articles

A/b testing calculator for statistical significance.

Anounymous Feedback: A How to guide

A Beginner's Guide to Non-Profit Marketing: Learn the Tips, Best practices and 7 best Marketing Strategies for your NPO

4 Major Benefits of Incorporating Online Survey Tools Into the Classroom

7 best demographic questions to enhance the quality of your survey

Best Practices for Ensuring Customer Data Security in Feedback Platforms

Confidential survey vs Anonymous survey - How to decide on that

Conjoint analysis: Definition and How it can be used in your surveys

Cross-Tabulation Analysis: How to use it in your surveys?

What is Data Masking- Why it is essential to maintain the anonymity of a survey

The Art of Effective Survey Questions Design: Everything You Need to Know to Survey Students the Right Way

Focus group survey Vs Online survey: How to choose the best method for your Market Research

How Employee Satisfaction Affects Company's Financial Performance

How to create an anonymous survey

How to identify if the survey is anonymous or not

A Simple and Easy guide to understand: When and How to use Surveys in Psychology

How to write a survey introduction that motivates respondents to fill it out

Survey and Question Design: How to Make a Perfect Statistical Survey

Matrix Questions: Definition and How to use it in survey

Maxdiff analysis: Definition, Example and How to use it

How to Maximize Data Collection Efficiency with Web 3.0 Surveys?

Empowering Prevention: Leveraging Online Surveys to Combat School Shootings

Optimizing Survey Results: Advanced Editing And Reporting Techniques

Enhancing Student Engagement and Learning with Online Surveys

Student survey questions that will provide valuable feedback

Preparing Students for the Future: The Role of Technology in Education

When It’s Best To Use Surveys For A Dissertation & How To Ensure Anonymity?

Which Pricing Strategy Should You Choose for Your Product? A Van Westendorp Analysis

Why Are Surveys Important for Financial Companies?

Want to create Anonymous survey in Facebook??- Know why you can't

• Utility Menu

Harvard University Program on Survey Research

• How to Frame and Explain the Survey Data Used in a Thesis

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.

This handout, based on an annual workshop offered by the Program on Survey Research at Harvard, is geared toward undergraduate honors thesis writers using survey data.

PSR Resources

• Managing and Manipulating Survey Data: A Beginners Guide
• Finding and Hiring Survey Contractors
• Overview of Cognitive Testing and Questionnaire Evaluation
• Questionnaire Design Tip Sheet
• Sampling, Coverage, and Nonresponse Tip Sheet
• Introduction to Surveys for Honors Thesis Writers
• PSR Introduction to the Survey Process
• Related Centers/Programs at Harvard
• General Survey Reference
• Institutional Review Boards
• Select Funding Opportunities
• Survey Analysis Software
• Professional Standards
• Professional Organizations
• Major Public Polls
• Survey Data Collections
• Major Longitudinal Surveys
• Other Links

• About About dataSpring Get to know your Asian panel insights provider. Meet the Team We aspire to be visionary, passionate, and relentless drivers of dataSpring values. Careers See our current openings and let’s build great things together! Visit Us Check out our offices in key cities across Asia.
• Products dataSpring Panels Asian Sample We’re ready to serve your research needs with our expansive coverage in Asia. Panel Sources Our secure data comes from proprietary panels, API integration, and third-party partners. Panel Quality Our industry-leading Quality Check System ensures data validity and valuable insights. Operations Enjoy convenient 24/7 support from our highly-capable Springers who speak your language. Get Our Panel Book Solutions Products Complete your requirements with our reliable platforms. Services We provided solutions for every stage of your projects. Mobile Platform Draw in-the-moment insights from Asian mobile consumers with our all-in-one platform. Check our mobile capabilities
• Resources Get started Understanding Online Research Panels Mobile Research Essentials Downloadable Media Newsletter Press Releases Resources Blogs Read more on topics about online research solutions to get you started. Eye On Asia Check out the latest trends in Asia and learn valuable local insights. dS Insights Relevant and beneficial market research content, updated regularly. Eye On Asia Podcast Listen to the latest market research news and trends in Asia in dataSpring's monthly podcast. リソース ブログ マーケティングリサーチやアジア諸国の情報について Eye On Asia アジアの最新トレンドをチェックして、現地の貴重な情報を知ることができます。 最新のインサイト情報 アジア地域のパネルについては、毎月実施される自主調査より詳しい情報をご確認いただけます。 Eye On Asia Podcast Eye On Asia Podcastにて、最新のアジアのマーケティングリサーチに関するニュースやトレンドを聞くことができます。
• Ask dataSpring
• About dataSpring
• Meet the Team
• Asian Sample
• Panel Sources
• Panel Quality
• Mobile Platform
• Understanding Online Research Panels
• Mobile Research Essentials
• Eye On Asia
• dS Insights
• Eye On Asia Podcast
• Downloadable Media
• Press Releases
• オンラインパネルについて
• モバイルリサーチの必要性について
• Ask dataSpring Contact Us

Relevant and beneficial market research content, updated regularly.

7 Ways To Get Respondents for Your Dissertation Survey

Not getting enough people for your study? Here are tried and tested ways to get respondents for your dissertation survey.

Conducting a survey may probably be the most important part of writing your dissertation, since this is where you can get hard data to support your study. It might be the most challenging part as well, especially when you need to get as many respondents as possible to support your results.

You may have everything down pat, from the objectives to the survey design, but without your respondents, your dissertation survey won’t be as useful as you thought it might be. Here are some tips in order for you to gather enough respondents for your dissertation survey:

We wish you the best of luck in completing your dissertation survey! We hope that you’ll be able to gather enough respondents who will complete your study. If you need assistance in getting an Asian online research panel for your survey, or if you'd like to try our survey demo, feel free to contact us or try our free IR check . If you’d like to know more about online research panels, check out our special page about them .

Don't forget to share this post!

Related articles.

Let's take a quick look at some studies to check if mobile research surveys in Asia do work. Technology has fast-tracked the development of surveys as market research tools, transitioning from traditi...

A properly designed and optimized mobile research survey will deliver powerful insights from your Asian respondents.

Contact us anytime 24/7! One of our Springers will be in touch with you within 24-48 hours to follow up on your request.

• Tokyo +81 3-5294-5970
• Shanghai +86 21-5238-7703
• Seoul +82 2-778-6051
• Manila +63 2-8899-3862
• Singapore +65 8333-5956
• Los Angeles +1 718-404-9260
• London +44 7724-025-169

© 2024 dataSpring Inc. Know today, Power tomorrow INTAGE GROUP

• Important Features

Survey Panels

• Additional Tools

1. SurveyKing

2. alchemer, 3. surveymonkey, 4. qualtrics, 5. questionpro, 6. sawtooth, 7. conjointly, 8. typeform, 9. google forms.

• Employee Feedback
• Creating the Survey
• Identity Protection
• Research Tools

Need a research survey tool? Features include MaxDiff, conjoint, and more!

These nine survey tools are perfect for academic research because they offer unique question types, solid reporting options, and support staff to help make your project a success. This article includes a detailed review of each of these nine survey tools. In addition to these survey tools, we include information about other research tools and survey panels.

Below is a quick summary of these nine survey tools. We list the lowest price to upgrade, which usually has the featured s needed for research projects. We also include a summary of the unique features of each tool. Most survey software has a monthly subscription; we denote when a tool requires annual pricing is required.

Important Features of Research Survey Software

Academic research surveys often require advanced question types to capture the necessary data. Many of the tools we mention in this article include these questions. However, some projects also require specialized features or the ability to purchase a panel. To help guide your decision in choosing the best piece of software for your project, we’ll summarize some of the most critical aspects.

Research Questions

Standard multiple-choice questions can only get you so far. Here are some question types you should be aware of:

• MaxDiff – measure the relative importance of an attribute. It goes beyond a standard ranking or rating by forcing respondents to pick the least and most valued items from a list. Rankings and other types only can you what is liked, not what is disliked. A statistical model will give you the probability of a user selecting an item as the most important. Latent class analysis can help you identify groups of respondents who value different attributes.
• Conjoint – Similar to MaxDiff in terms of finding importance, respondents evaluate a complete product (multiple attributes combined). This simulates real word purchasing decisions. A statistical model is also used to compute the importance of each item.
• Van Westendorp – Asks respondents to evaluate four price points. This shapes price curves and gives you a range of acceptable prices.
• Gabor Granger – Asks users whether or not they would purchase an item at specific price points. Price points are shown in random order to simulate real-world buying conditions. The results include a demand curve, giving you the revenue-maximizing price.
• Likert Scale – Measure attitudes and opinions related to a topic. It’s essential to use a mobile-ready Likert scale tool to increase response rates; many tools use a matrix for Likert scales, which could be more user-friendly.
• Semantic differential scale – a multirow rating scale that contains grammatically opposite adjectives at each end. It is used similarly to a Likert scale but is much easier for respondents to evaluate.
• Image heat map – Respondents click on places they like on an image. The results include a heat map showing the density of clicks. This is useful for product packaging.
• Net Promoter Score – Respondents choose a rating from 0-10. Many companies use this industry-standard question to benchmark their brand perception. This question type is necessary if your academic project measures brand reputation.

Anonymous Survey Links

Many academic surveys can deal with sensitive subjects or target sensitive groups. For this reason, assuring anonymity for respondents is crucial. Choosing a platform with an anonymous link is essential to increase trust with respondents and increase your response rates.

Data Segmentation

Comparing two groups within your survey data is essential for many research projects. This is called cross tabulation . For example, consider a survey where you ask for gender along with product satisfaction. You may notice that males are not satisfied with the product while females are.

You can take this further and compute the statistical significance between the groups. In other words, make the differences that exist between two data sets due to random chance or not. Your comparison is statistically significant if it’s not due to random chance.

Some lower-end survey tools may not offer any segmentation features. If this is the case, you need to download your survey data into a spreadsheet and create pivots of set-up custom formulas.

Skip Logic and Piping

If your academic project has questions that only a specific subset of respondents need to answer, then some logic will help streamline your survey.

Skip logic will take you to a new page based on answers to previous questions. Display logic will show a question to a user based on previous questions; perfect for follow-up.

Answer piping will allow you to carry forward answers from one question into another. So, for example, ask someone which brand names they have heard of, then pipe those answers into a ranking question.

Data Cleaning

Making sure your responses are high quality is a big part of any survey research project. For example, if people speed through the survey or mark all the first answers for questions, those would be low-quality responses and should be removed from your data set. Some tools highlight these low-quality responses, which can be a helpful feature.

For platforms that do not offer a data cleaning feature, it’s generally possible to export the data to Excel, create formulas for time spent, answer straight-lining, then remove the needed data. You can also include a  trap question  to help filter out low-quality responses.

Great Support

Many academic projects require statistical analysis or additional options for the survey. Using a tool with a support staff that can explain a statistical model’s intricacies, help build custom models, or adds features on request will ensure your project is a success. With SurveyKing, custom-built features are billed at $50 per hour, making custom projects feasible for small budgets.

Asking classmates to take your survey, posting it on social media, or distributing QR code surveys around campus is a great way to collect responses for your project. But if you need more responses with those methods, purchasing additional answers might be required.

A panel provider will enable you to target a specific demographic, job role, or hobby type. When setting up a survey with a penal provider, you always want to include screening questions (on the first page) to ensure they meet your criteria, as panel filters may not be 100% accurate. Generally, panel responses start around $2.50 per completed response.  Cint  is one of the largest panel providers and works well with any survey platform.

Additional Research Tools

Before deep diving into the survey software list, here are some additional tools and resources that might assist in your project. These can help shape your survey by conducting preliminary research or using it as a substitute if conducting a study is not feasible.

• Hotjar  – They offer simple surveys and many tools to help capture feedback and data points from a website. A feedback widget customized for websites in addition to a heat map tool to show where users click the most or to identify rage clicks. A tool like this could be helpful if your academic projects revolve around launching or optimizing a website.
• Think with Google  – Used to help marketers understand their audience. The site contains links to Google Trends to search for the popularity of key terms over time. They also have a tool that helps you identify your audience based on popular YouTube channels. Finally, they have a “Grow My Store Tool” that recommends tips for improving an online store.
• Google Scholar  – A specific search engine used for scholarly literature. This can help locate research papers related to the survey you are creating.
• MIT Theses  – Contains over 58,000 theses and dissertations from all MIT departments. The database is organized by department and lets you search for keywords.

SurveyKing is the best tool for academic research surveys because of a wide variety of question types like MaxDiff, excellent reporting features, a solid support staff, and a low cost of $19 per month.

The survey builder is straightforward to use. Question types include MaxDiff, conjoint, Gabor Granger, Van Westendorp, a mobile optimized Likert scale, and semantic differential.

The MaxDiff question also includes anchored MaxDiff and collecting open-ended feedback for the feature most valued by a respondent. In addition, cluster analysis is available to help similar group data together; some respondents might value specific attributes, while other groups value others.

The reporting section is also a standout feature. It is easy to create filters and segment reports. In addition, the Excel export is well formatted easily for question types like ranking and Likert Scale, making it easy to upload into SPSS. The reporting section also gives the probability for MaxDiff, one of the few tools to offer that.

The anonymous link on SurveyKing is a valuable feature. A snippet at the top of each anonymous survey is where users can click to understand whether their identities are protected.

The software also offers a Net Promoter Score module which can come in handy for projects that deep dive into brand reputation.

Some downsides to SurveyKing include no answer piping, no image heat maps, no continuous sum question, and no premade data cleaning feature.

As a platform with lots of advanced question types and a reasonable cost, Alchemer is an excellent tool for academic research. Question types include MaxDiff, conjoint, semantic differential, image heat map, text highlighter, continuous sum, cascading dropdowns, rankings, and card grouping.

Reporting on Alchemer is a standout feature. Not only can you create filters and segment reports, but you can also create those filters and segments using advanced criteria. So if you ask a question about gender and hobby, you can make advanced criteria that match a specific gender and hobby.

In addition, their reporting section also can do chi-square tests to calculate the significant difference between the two groups. Finally, they also have a section where you can create and run your R scripts. This can be useful for various academic research projects as you can create custom statistical models in the software without needing to export your data.

Alchemer is less user-friendly than some other tools. The platform is a little clunky; things like MaxDiff require respondents to hit the submit button to get to the next set. Radio buttons need respondents to click inside of them instead of the area around them.

The pricing is reasonable for a student; $249 a month for access to the research questions. However, if you can organize your project quickly, you may only need one month of access.

As the most recognized brand for online surveys, SurveyMonkey is a reliable option for academic research. While the platform does not have any research questions, it offers all the standard question types and a clean user interface to build your surveys.

One advanced question type they do have is the image heat map. Their parent company  Momentive  does offer things like MaxDiff and conjoint studies, but you would need to contact sales to get a quote, meaning this could be out of budget for students.

The reporting on SurveyMonkey is good. You can easily create filters and segments. You can also save that criterion to create a view. The views enable you to toggle between rules quickly.

One of the main downsides to SurveyMonkey is the cost. For the image heat map and to create advanced branching rules, you need to upgrade to their Premier plan, which costs $1,428 annually. To get statistical significance, you would need their Primer plan, which is $468 annually.

As the survey tool known for experience management, Qualtrics has some nice features for research projects. For example, they offer both MaxDiff and conjoint in addition to tools like drill-down, continuous sun, image heat map, and a text highlighter.

Reporting on the tool offers the ability to create filters and segments. For segments, it’s called a report breakout, and it appears there is no ability to create a breakout with advanced criteria. However, filers do allow you for advanced criteria.

There is a custom report builder option to create custom PDF reports. You can add as many elements as needed and customize the information displayed, whether a chart type or a data table.

Overall, Qualtrics could be more user-friendly and may require training. The survey builder and reporting screens could be more cohesive. For example, to add more answer options, you need to click the “plus” symbol on the left-hand side of the question instead of just hitting enter or clicking a button right below the current answer choice. In addition, the reporting section will display things like mean and standard deviation for simple multiple-choice questions before showing simple response counts.

One drawback to Qualtrics is the pricing. For example, you would need to pay $1,440 for an annual plan to use the research questions. But many universities have a licensing agreement with Qualtrics so students can use the platform. When you sign up for a new account, you can select academic use, enter your Edu email, and they will check if your university has a license agreement.

A survey platform with all the needed research questions, including Gabor Granger and Van Westendorp, QuestionPro is a quality research tool.

The reporting on QuestionPro is comprehensive. They offer segment reports with statistical significance using a t-test. In addition, they offer TURF analysis to show answer combinations with the highest reach.

For conjoint, offer a market simulation tool that can forecast new product market share based on your data. That tool can also calculate how much  premium  consumers will pay for a brand name.

QuestionPro is a little easier to use than Qualtrics. The UI is cleaner but still clumsy. You must navigate to a different section in the builder for things like quotas instead of just having it near skip logic rules. The distribution page has the link at the top but an email body below. The reporting has a lot of different pages to click through for each option. Small things like this mean there is a learning curve to use the platform efficiently.

The biggest downside of QuestionPro is the price. All of their research questions, even Net Promoter Score, would require a custom quote under the research plan. There another plan with upgraded feature types is $1,188 annually.

When it comes to advanced research projects, Sawtooth is a great resource. While their survey builder is a little limited in question types, they offer different forms of MaxDiff and conjoint. They also provide consulting services, which could help if your academic project is highly specialized.

For MaxDiff, they offer a bandit  version, which can be used for MaxDiff studies with over 50 attributes. Each set of detailed attributes that are most relevant to the user. This can save panel costs because you can build a suitable statistical model with 300 bandit responses compared with 500 or 1000 standard MaxDiff responses.

Their MaxDiff feature also comes with a TURF analysis option that can show you the possible market research of various attributes.

For conjoint, they offer adaptive choice-based conjoint and menu-based conjoint. Adaptive choice tailors the product cards toward each respondent based on early responses or screening questions. Menu-based conjoint is for more complex projects, allowing respondents to build their products based on various attributes and prices.

Sawtooth has a high price point and may be out of the research for many academic projects. The lowest plan is $4,500 annually. If you need advanced tools like bandit MaxDiff or adaptive conjoint, you must pay $11,990 annually. They do have a package just for MaxDiff starting at $2,420.

Conjointly is a platform geared towards research projects, namely market research. Not only do they have the standard research questions, but they also have a bunch of unique ones: claims testing, Kano Model testing, and monadic testing. There are also question types like feature placement matrix, which combines MaxDiff and Gabor Granger into a single question.

You can either use your respondents or select from a survey panel. The survey panel option comes with predefined audiences, which makes scouring respondents a breeze.

One unique feature is that they monitor in real-time speeders and other criteria for low-quality respondents. If a respondent is speeding through the survey, a warning message is displayed asking them to repeat questions before being disqualified. If a question has a lot of information to digest, the system automatically pauses, forcing the respondent to thoroughly read the question before answering.

The pricing is a little steep at $1,795 annually. Response panels for USA residents appear to start around $4 per completed response. The survey builder and reporting section could be cleaner, with different options in many places. It may take time to get up to speed.

While Typeform doesn’t have any research questions, it is a very well-designed and easy-to-use tool that can assist with your academic survey. For example, it could gather preliminary data for a MaxDiff study.

Typeform offers a lot of integrations with other applications. For example, if your project requires exporting data to a spreadsheet, then Google Sheets or Excel integration might be helpful. Likewise, if your research project is part of a class project, then the Slack or Microsoft Teams integration might help to notify other team members when you get responses.

One unique feature of Typeform is the calculator feature. Add, subtract, and multiply numbers to the @score or @price variable. These variables can be recalled to show scores or used in a payment form.

The reporting in Typeform is basic. There is no option to create a filter or a segment report. Any data analysis would need to be done in Google Sheets or Excel.

For $29 a month, you can get 100 responses, or $59 a month, you can collect 1,000 responses each month.

One of the widely used survey tools, Google Forms , is a decent platform for an academic research survey. Unfortunately, the software doesn’t offer any research questions. Still, the few questions it has, like multiple choice, rantings, and open-ended feedback, are enough to collect essential feedback for simple projects or preliminary data for more complex studies.

Skip logic is straightforward to set up on Google Forms. For example, you can select what section to skip based on question answers or choose what to skip once a section is complete. Of course, you can’t create complex rules, but these simple rules can cover many bases.

Overall the user interface is elegant and straightforward. The form design is also elegant, meaning the respondent experience is excellent. Unlike other survey tools, which can have a clunky interface, there is no worry about that with Google Forms; respondents can quickly navigate your form and submit answers.

The spreadsheet export is very well formatted and can be easily imported into SPSS for advanced analysis. However, the export has the submission date and time but has yet to have the time started, so calculating speeders is impossible.

ABOUT THE AUTOR

Allen is the founder of SurveyKing. A former CPA and government auditor, he understands how important quality data is in decision making. He continues to help SurveyKing accomplish their main goal: providing organizations around the world with low-cost high-quality feedback tools.

Ready To Start?

Create your own survey now. Get started for free and collect actionable data.

Business Process Improvement Consulting: Expert Solutions

Definition: A business process improvement consultant will help design and implement strategies to increase the efficiency of workflows across your o...

8 Excel Consulting Services to Use in 2024 + VBA Support

These 6 Excel consulting firms offer support, training, and VBA development to help you automate tasks and increase efficiency when using Microsoft Ex...

9 Great SurveyMonkey Alternatives to Use in 2024

Discover alternatives to the most popular online survey tool, SurveyMonkey. Gain an understanding of where SurveyMonkey lacks in features and get intr...

7 Great Qualtrics Alternatives to Use in 2024

These seven alternatives to Qualtrics offer either more features, a lower cost, or a cleaner user interface. These alternative platforms also include ...

Union Negotiation Consulting: Planning Labor Agreements

A labor union negotiation consulting engagement involves quantifying member needs, proposing contract language, and developing communication strategie...

Creating a Transactional Survey: Examples + Template

Definition: A transactional survey captures customer feedback after a specific interaction, referred to as a touchpoint. This survey type provides dir...

Hire an Excel Expert: Automation + VBA Development

An Excel expert will help you to complete your projects within Microsoft Excel. A good Excel expert should be proficient in advanced formulas such as ...

Creating an Anonymous Employee Survey + Template, Sample Questions

Definition: An anonymous employee survey is a convenient way to collect honest feedback in the workplace. The survey can either measure employee satis...

Improving Fleet Performance Through Driver Feedback Surveys

In the US, the trucking industry generated $875.5 billion in gross freight revenues, accounting for 80.8% of the country’s freight invoice in 20...

13 College Study Tips to Use in 2023

These 15 college study tips will help you succeed in your academic career.

Maximizing the Value of Skills Assessment Tools Using Surveys

When you apply for a job, it’s only natural that you’ll aim to present the best possible version of yourself. You’ll focus on your best skills a...

Creating UX Surveys: 6 Tips and Examples

UX surveys are used to help create a great user experience. A good UX survey will incorporate a variety of question types to help understand what user...

5 Web Consultants to Use in 2023: Design + Development

Definition: A web consultant can update an existing website design, create a custom website, help increase traffic, recommend layout changes, and even...

Creating a Targeted Survey: Panels to Reach Your Audience

Definition: A targeted survey is used to research a specific audience, frequently utilizing a survey panel provider. A paneling service generally has ...

8 Typeform Alternatives to Use in 2023

These seven alternatives to Typeform offer a lower cost or additional features. In addition, these alternative platforms include question types that T...

6 Ecommerce Skills For Professionals + Students

Ecommerce has occupied its leading niche in the world, allowing us to draw certain conclusions. For example, it is not surprising that more specialize...

Ecommerce Analytics Explained + Tools to Use

Definition: Ecommerce analytics is the practice of continuously monitoring your business performance by gathering and examining data that affects your...

Planning a Survey: 6 Step Guide + Best Practices

Planning a survey involves six steps: Set objectives, define the target audience, select the distribution method, organize external data, draft the su...

4 Survey Consulting Services to Use in 2023

Definition: These 4 survey consulting services offer planning, design, development, and support to help complete your survey project. Whether it’s f...

Excel Automation Explained: VBA Code + Sample Workbooks

Definition: Excel automation will streamline repetitive tasks such as updating data, formatting cells, sending emails, and even uploading files to Sha...

Hire a Financial Modeling Consultant: Forecasts + Valuations

Definition: A financial modeling consultant will provide expertise in planning budgets, generating forecasts, creating valuations, and providing equit...

Excel Programming Services: Development, Macros, VBA

Definition: An excel programmer can be hired to organize workbooks, create custom formulas, automate repetitive tasks using VBA, and can consult on h...

Market Research Surveys: Sample Questions + Template

Definition: Market research surveys are a tool used to collect information about a target market. These surveys allow businesses to understand market ...

What do Americans Value Most in the Coming Election? A Comprehensive and Interactive 2020 Voter Poll

SurveyKing set out on a mission in the fall of 2020, to poll American's and help identify, with quantifiable data, what issues american are most focus...

Get Started Now

We have you covered on anything from customer surveys, employee surveys, to market research. Get started and create your first survey for free.

Surveys for dissertation

We are starting a series of articles created for students who are looking for an online survey and questionnaire tool for their dissertations.

While planning your survey you can select from multiple research techniques. Each one can be the subject of a separate article. In this article, we will focus on CAWI (Computer-Assisted Web Interview).

Thanks to Internet and survey tools development (like SurveyLab) CAWI is gaining popularity not only among students but also among big organizations and corporations.

The most important advantages of CAWI are low cost of the research, a clear process that is easy to control, and short time needed to create a survey and collect responses.

How to start – research goal

Before you start work on your questionnaire design, define the goal you want to accomplish. It may occur that survey research is not the best way to do it.

It is always good to write your goal on a blank sheet of paper. It will help you to clarify your thoughts.

Target group

Define your target group. It means estimate how many responses you need to be able to start data analysis and what is your respondent profile (e.g. people living in big cities – over 200k citizens, that are active tourists – spend at least one weekend outside the city).

Questionnaire

Now you can start work on your questionnaire. This phase is very important as questionnaire quality will impact survey results and report quality. There are a few rules you should follow :

• Remember that your respondents won’t be able to ask you additional questions and you won’t be able to provide additional explanations. Therefore your questionnaire should be clear and easy to understand.
• Your questionnaire and questions quality will impact report and survey results.
• Use easy-to-understand language, and avoid technical jargon, slang, or abbreviations.
• Don’t try to add every question to your survey. Ask yourself if you need each question that has been added.
• Your questionnaire should be logical, which means questions should be grouped by subjects.
• Don’t forget about statistical and demographic questions. It will help you to analyze your database using such criteria as gender, age, city, occupation, …
• Test your questionnaire, send it to your friends, and test if the survey is clear and easy to complete.

Project start

Select the best date to start data collection. For example, December, 24 won’t be the best idea to start data collection. Make sure that selected date is best for your target group.

Response analysis

SurveyLab was designed to make hard work for you. The system will automatically collect responses, aggregate them, and present them in a single report.

When selecting a survey tool make sure it will be able to export data in the format you need it. SurveyLab allows you to download survey results in CSV, Excel, or SPSS format.

Try SurveyLab for free Best survey tool with great features

14 days trial | view complete list of features

Qualitative study design: Surveys & questionnaires

• Qualitative study design
• Phenomenology
• Grounded theory
• Ethnography
• Narrative inquiry
• Action research
• Case Studies
• Field research
• Focus groups
• Observation
• Surveys & questionnaires
• Study Designs Home

Surveys & questionnaires

Qualitative surveys use open-ended questions to produce long-form written/typed answers. Questions will aim to reveal opinions, experiences, narratives or accounts. Often a useful precursor to interviews or focus groups as they help identify initial themes or issues to then explore further in the research. Surveys can be used iteratively, being changed and modified over the course of the research to elicit new information. 

Structured Interviews may follow a similar form of open questioning.  

Qualitative surveys frequently include quantitative questions to establish elements such as age, nationality etc. 

Qualitative surveys aim to elicit a detailed response to an open-ended topic question in the participant’s own words.  Like quantitative surveys, there are three main methods for using qualitative surveys including face to face surveys, phone surveys, and online surveys. Each method of surveying has strengths and limitations.

Face to face surveys  

• Researcher asks participants one or more open-ended questions about a topic, typically while in view of the participant’s facial expressions and other behaviours while answering. Being able to view the respondent’s reactions enables the researcher to ask follow-up questions to elicit a more detailed response, and to follow up on any facial or behavioural cues that seem at odds with what the participants is explicitly saying.
• Face to face qualitative survey responses are likely to be audio recorded and transcribed into text to ensure all detail is captured; however, some surveys may include both quantitative and qualitative questions using a structured or semi-structured format of questioning, and in this case the researcher may simply write down key points from the participant’s response.

Telephone surveys

• Similar to the face to face method, but without researcher being able to see participant’s facial or behavioural responses to questions asked. This means the researcher may miss key cues that would help them ask further questions to clarify or extend participant responses to their questions, and instead relies on vocal cues.

Online surveys

• Open-ended questions are presented to participants in written format via email or within an online survey tool, often alongside quantitative survey questions on the same topic.
• Researchers may provide some contextualising information or key definitions to help ‘frame’ how participants view the qualitative survey questions, since they can’t directly ask the researcher about it in real time. 
• Participants are requested to responses to questions in text ‘in some detail’ to explain their perspective or experience to researchers; this can result in diversity of responses (brief to detailed).
• Researchers can not always probe or clarify participant responses to online qualitative survey questions which can result in data from these responses being cryptic or vague to the researcher.
• Online surveys can collect a greater number of responses in a set period of time compared to face to face and phone survey approaches, so while data may be less detailed, there is more of it overall to compensate.

Qualitative surveys can help a study early on, in finding out the issues/needs/experiences to be explored further in an interview or focus group. 

Surveys can be amended and re-run based on responses providing an evolving and responsive method of research. 

Online surveys will receive typed responses reducing translation by the researcher 

Online surveys can be delivered broadly across a wide population with asynchronous delivery/response. 

Limitations

Hand-written notes will need to be transcribed (time-consuming) for digital study and kept physically for reference. 

Distance (or online) communication can be open to misinterpretations that cannot be corrected at the time. 

Questions can be leading/misleading, eliciting answers that are not core to the research subject. Researchers must aim to write a neutral question which does not give away the researchers expectations. 

Even with transcribed/digital responses analysis can be long and detailed, though not as much as in an interview. 

Surveys may be left incomplete if performed online or taken by research assistants not well trained in giving the survey/structured interview. 

Narrow sampling may skew the results of the survey. 

Example questions

Here are some example survey questions which are open ended and require a long form written response:

• Tell us why you became a doctor? 
• What do you expect from this health service? 
• How do you explain the low levels of financial investment in mental health services? (WHO, 2007) 

Example studies

• Davey, L. , Clarke, V. and Jenkinson, E. (2019), Living with alopecia areata: an online qualitative survey study. British Journal of Dermatology, 180 1377-1389. Retrieved from https://onlinelibrary-wiley-com.ezproxy-f.deakin.edu.au/doi/10.1111%2Fbjd.17463    
• Richardson, J. (2004). What Patients Expect From Complementary Therapy: A Qualitative Study. American Journal of Public Health, 94(6), 1049–1053. Retrieved from http://ezproxy.deakin.edu.au/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=s3h&AN=13270563&site=eds-live&scope=site  
• Saraceno, B., van Ommeren, M., Batniji, R., Cohen, A., Gureje, O., Mahoney, J., ... & Underhill, C. (2007). Barriers to improvement of mental health services in low-income and middle-income countries. The Lancet, 370(9593), 1164-1174. Retrieved from https://www-sciencedirect-com.ezproxy-f.deakin.edu.au/science/article/pii/S014067360761263X?via%3Dihub  

Below has more detail of the Lancet article including actual survey questions at: 

• World Health Organization. (2007.) Expert opinion on barriers and facilitating factors for the implementation of existing mental health knowledge in mental health services. Geneva: World Health Organization. https://apps.who.int/iris/handle/10665/44808
• Green, J. 1961-author., & Thorogood, N. (2018). Qualitative methods for health research. SAGE. Retrieved from http://ezproxy.deakin.edu.au/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=cat00097a&AN=deakin.b4151167&authtype=sso&custid=deakin&site=eds-live&scope=site   
• JANSEN, H. The Logic of Qualitative Survey Research and its Position in the Field of Social Research Methods. Forum Qualitative Sozialforschung, 11(2), Retrieved from http://www.qualitative-research.net/index.php/fqs/article/view/1450/2946  
• Neilsen Norman Group, (2019). 28 Tips for Creating Great Qualitative Surveys. Retrieved from https://www.nngroup.com/articles/qualitative-surveys/   
• << Previous: Documents
• Next: Interviews >>
• Last Updated: Apr 8, 2024 11:12 AM
• URL: https://deakin.libguides.com/qualitative-study-designs

Masters Compare - Find your perfect masters course.

• Studying a Postgraduate degree

Your postgraduate student guide to using a research questionnaire for your dissertation

Share this article.

• Facebook Sharer
• Twitter Sharer
• LinkedIn Sharer

Explore other topics

• Funding a Postgraduate course
• Living as a Postgraduate student
• Popular masters degree subjects
• Student Wellbeing
• Finding a PhD or Masters Course

Think Postgrad

Frequently asked questions.

There are a few key steps in creating a dissertation for use in your thesis. Firstly, you should think about the topic you are studying and who you need to respond to your questionnaire. You then need to think about how you can deliver the questions, this can be in the form of in-person interviews or emails. You can begin to formulate your questions and format.

Visit the Studying for a PhD section for more information and advice.

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 can be used with relatively small-scale research projects, and research questionnaires can be designed and delivered quite quickly and cheaply. It is not surprising, therefore, that when it comes to conducting research for a master’s dissertation, questionnaire surveys feature prominently as the research method of choice.

Occasionally such thesis surveys will be sent out by post, and sometimes the questionnaires will be distributed by hand. But the popularity of questionnaire surveys in the context of master’s dissertations is principally due to the benefits of using online web-based questionnaires. There are two main aspects to this.

First, the software for producing and delivering web questionnaires, with their 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 which, given the time and resource constraints faced when producing a dissertation, makes online surveys all the more enticing. (And, for the more adventurous students, there are also developing possibilities for the use of social media such as Facebook and SMS texts 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 as the basis for advanced, master’s level academic enquiry. Which means it is not good enough to simply rely on getting 100 or so people to complete your questionnaire. Students are expected to be aware of the pros and cons of questionnaire surveys and to be able to justify the value of the data they 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 not only 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 the 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

• Advertisers
• Cookie Policy
• Terms and Conditions

Sorry! You need to sign up

Sign up to Postgraduate Studentships

Sign up to compare masters

Opportunity added!

Thanks for making your selection. Click below to view your list.

Course Added

Thanks for making your selection. Click below to view your comparisons.

Think Postgrad Ltd 2008-2024 Website By Parachute

Collecting Dissertation Data

Once you have successfully defended your dissertation proposal and have had your study approved by your university’s institutional review board, you are ready to start collecting data for your study. There are many data collection methods, but how you ultimately choose to collect data will depend on the design of your study. Below are some common methods of collecting dissertation data and the types of projects for which these methods are most appropriate.

Online Data Collection

Online data collection has become very popular. Compared to paper-and-pencil surveys, online data collection is much cheaper and less time consuming and allows researchers to recruit participants from a larger geographic area. There are many websites for data collection, such as Survey Monkey and Psych Data, which make the process of collecting data very easy. Given its nature, online dissertation data collection is really only appropriate for quantitative research projects.

Paper-and-Pencil Surveys

Like the name implies, paper-and-pencil surveys are hard copies of your questionnaires that are handed out to participants to complete and return. One advantage of using paper-and-pencil surveys is that participants are more likely to complete paper-and-pencil surveys if surveys are handed to participants and if participants are given time and space to complete the surveys (n.b., you can make use of all the undergraduate classes in which you and your fellow grad students are GAs). The drawback of paper-and-pencil surveys is that you will have to enter the data by hand, which you would not have to do for dissertation data collected online. However, you can always recruit eager undergraduates who want to get into grad school to help you enter the data. As with online data collection, paper-and-pencil surveys are only appropriate for quantitative research projects.

Interviews/Focus Groups

If your project is qualitative in nature, you will likely need to conduct interviews or focus groups to collect the dissertation data you need. Once you have conducted your interviews or focus groups, you will need to go back and transcribe them verbatim, which is also a rather time-consuming process. Again, you can enlist undergraduates to help you transcribe your interviews.

Click here to cancel reply.

You must be logged in to post a comment.

Copyright © 2024 PhDStudent.com. All rights reserved. Designed by Divergent Web Solutions, LLC .

Have a language expert improve your writing

Run a free plagiarism check in 10 minutes, automatically generate references for free.

• Knowledge Base
• Dissertation

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

A dissertation or thesis is a long piece of academic writing based on original research, submitted as part of an undergraduate or postgraduate degree.

The structure of a dissertation depends on your field, but it is usually divided into at least four or five chapters (including an introduction and conclusion chapter).

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

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

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

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

Instantly correct all language mistakes in your text

Be assured that you'll submit flawless writing. Upload your document to correct all your mistakes.

Table of contents

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

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

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

Prevent plagiarism, run a free check.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Is this article helpful?

Other students also liked.

• What Is a Dissertation? | 5 Essential Questions to Get Started
• What is a Literature Review? | Guide, Template, & Examples
• How to Write a Dissertation Proposal | A Step-by-Step Guide

More interesting articles

• Checklist: Writing a dissertation
• Dissertation & Thesis Outline | Example & Free Templates
• Dissertation binding and printing
• Dissertation Table of Contents in Word | Instructions & Examples
• Dissertation title page
• Example Theoretical Framework of a Dissertation or Thesis
• Figure & Table Lists | Word Instructions, Template & Examples
• How to Choose a Dissertation Topic | 8 Steps to Follow
• How to Write a Discussion Section | Tips & Examples
• How to Write a Results Section | Tips & Examples
• How to Write a Thesis or Dissertation Conclusion
• How to Write a Thesis or Dissertation Introduction
• How to Write an Abstract | Steps & Examples
• How to Write Recommendations in Research | Examples & Tips
• List of Abbreviations | Example, Template & Best Practices
• Operationalisation | A Guide with Examples, Pros & Cons
• Prize-Winning Thesis and Dissertation Examples
• Relevance of Your Dissertation Topic | Criteria & Tips
• Research Paper Appendix | Example & Templates
• Thesis & Dissertation Acknowledgements | Tips & Examples
• Thesis & Dissertation Database Examples
• What is a Dissertation Preface? | Definition & Examples
• What is a Glossary? | Definition, Templates, & Examples
• What Is a Research Methodology? | Steps & Tips
• What is a Theoretical Framework? | A Step-by-Step Guide
• What Is a Thesis? | Ultimate Guide & Examples