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Formulating Research Questions: Some Basics, Techniques and Practical Examples


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Did you know that that the research questions are amongst the last things to be written up in your thesis? Oh, yes, and they are also the first thing to be written up, just for a different purpose. Your initial research questions are aimed at providing you with some direction so to allow you to embark on your research.

And as much as good research questions can guide you well through your research, as much can faulty research questions misguide you, and as has been discussed in this webinar. And for those at doubt, whether or not they are well or misguided, the webinar slides feature a number of URL to external supportive sources so for you to evaluate. And to those that would want to get some individual perspective on this matter, feel free to contact us and ask!
The full slide deck is available via the at the Peers4Progress class room, which provides you with a meeting place to support ongoing discussions, and collect and share resources.

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Formulating Research Questions: Some Basics, Techniques and Practical Examples

  1. 1. Formulating Research Questions Dr Andreas Meiszner (PhD) Some Basics, Techniques and Practical Examples Summary
  2. 2. Did you know? … that the research questions are amongst the last things to be written up in your thesis. © DoctorateHUB Slide 2
  3. 3. Now you know! Having said that, it is also the starting point of your research. And it is subject to constant change as your research evolves. Up until the very end point in your journey this will be the basis of a constant question- answer matching process. And comparing your findings against the literature, so to asses what questions can be answered and what still remains unknown. So be prepared for that arduous task. © DoctorateHUB Slide 3
  4. 4. …and not to forget… While perhaps obvious, let us flag it up: The things that you answer belong INTO your thesis. It is not like: ”understood that, not any longer a problem, so let’s take it out of the thesis”. Contrary, ”understood that” should be shown in the analysis chapter of your thesis on how findings and literature answer the respective research questions. © DoctorateHUB Slide 4
  5. 5. So what is the question then? © DoctorateHUB Source: Slide 5 What is the question is indeed the real question!
  6. 6. And what is the purpose of the question? © DoctorateHUB Source: Slide 6 What do we want to explore?
  7. 7. Why do we ask this question? © DoctorateHUB Source: Executive Summary “This guide to using qualitative research methodology is designed to help you think about all the steps you need to take to ensure that you produce a good quality piece of work. The guide starts by telling you what qualitative methodology is and when to use it in the field (understand people’s belief system, perspectives, experiences). It also flags the most important ethical issues that you will encounter (consent and confidentiality). The second part of the guide tackles how you can concretely develop qualitative research designs; starting from clearly defining your research question (one of the most important steps in your research!), to how to develop a research protocol; and finally giving you tips on the sampling methods which are available and how to use them. The third part details how you can actually obtain the data - what methods can you use to get the information you want? The three main methods (individual interviews, group interviews and observational methods) are explained, and the steps to build these different methods are outlined (How to do a topic guide? How to ask questions? How to develop interview skills and manage expectations? How to run group discussions? Etc.). Finally, the fourth chapter looks into how, once you have collected all the data, you can manage it and analyse it. For the management of data, a few practical issues are addressed, such as confidentiality and security, translation and recording. The analysis section will give you clues as to how to use thematic or narrative analysis, what validation strategies you need to think of, what good practice guidelines you should follow, and whether or not to use a computer software. Case studies will be developed throughout the year and put on the open repository.” A Guide to Using Qualitative Research Methodology Slide 7
  8. 8. And what is the intention of the question? © DoctorateHUB Source: Common mistakes in Research Question Framing (adapted from Leek and Penga, 2015) REAL QUESTION TYPE PERCEIVED QUESTION TYPE PHRASE DESCRIBING ERROR Inferential (to reach conclusions that extend beyond the immediate data alone) Causal “Correlation does not imply causation” Exploratory Inferential “Data dredging” (only consider those data that support your argument) Exploratory Predictive “Overfiting” Descriptive Inferential “n of 1 analysis” (e.g. a single case study) “Confusion between data analytic question types is central to the ongoing replication crisis, misconstrued press releases describing scientific results, and the controversial claim that most published research findings are false (13, 14). The solution is to ensure that data analytic education is a key component of research training. The most important step in that direction is to know the question.“ What is the question? Mistaking the type of question being considered is the most common error in data analysis By Jeffery T. Leek and Roger D. Penga (2015) Slide 8
  9. 9. And how do we know that the question is wrong? © DoctorateHUB Source: “Perhaps the most widely known example of that failure occurs when scientists mistake correlation for causation, or, as Leek and Peng describe it, inferential questions for causal ones. Inferential questions ask whether two variables are somehow related, while causal questions ask if deliberately changing one actually affects the other. As an example, some researchers report a connection between mobile phones and brain cancer, but those studies simply asked cancer patients and healthy people about their past cell phone use. Sure, it's possible that cell phones cause brain cancer, but maybe a cancer diagnosis leads people to report spending more time on their portable phones than they actually did. A simpler example is the strange correlation between sports and elections. One rule of thumb: If the Washington football team wins their last home game of the season, the incumbent party stays in the White House. That rule has predicted 17 of the last 19 presidential elections, but that doesn't mean their wins or losses influenced who moved into the White House. Maybe it's the other way around, or maybe it's a coincidence. Answering the inferential question—is there a correlation?—says nothing about the causal question.” Slide 9
  10. 10. Some say, it’s the attitude of questioning © DoctorateHUB Source: “It takes courage and confidence to question published authors, especially when you are just beginning to study a subject; however, that is what is required. No research is perfect, even the best work will be limited and have weaknesses, and will raise more questions than it answers. So try to develop a questioning attitude and check each author’s work. Such questioning is judged to be fair dealing, and is expected and encouraged. Approach critical evaluation as a brainstorming exercise to assess whether the conclusion is true." Slide 10
  11. 11. So then, what is the purpose of the question? © DoctorateHUB • What are the questions that this research has answered? • How do the questions relate to each other? • Are there overarching themes and patterns that could be derived from such questions? t1t0 • What is happening here? • Why is this not working? • Why is A happening once I do B? Once data becomes available • What is the data telling me about my initial questions? • What is the data telling me about the problem that I might have not considered at the start? Initial Questions Emergent Questions Slide 11
  12. 12. Type of questions © DoctorateHUB Source: Slide 12
  13. 13. Criteria of research questions are…  Focused – one issue only; usually one central question and associated sub-questions.  Specific – no vague words or avoiding of naming.  Complex – not a simple question asking for yes/no answers.  Analytical – geared towards exploration of a problem, not the achievement of a solution.  Un-biased – open ended without suggesting a solution. It is like a roadmap for the reader that illuminates your story or contribution. © DoctorateHUB Source: Slide 13
  14. 14. And the questions are derived from a PROBLEM © DoctorateHUB Source: • Sharpen your reading lens and read the guides with a problem view, not a solution view. • In this example the problem is related to decision making, not the outcome expectation (to know what decision to make so to increase sales to a million dollars). • A problem is a problem is a problem (see also /26/post-webinar-the-research-problem-and- the-solution-bias/) Slide 14
  15. 15. How questions Evolve over time (1/3) © DoctorateHUB Source: Slide 15
  16. 16. How questions Evolve over time (2/3) © DoctorateHUB Source: Slide 16
  17. 17. How questions Evolve over time (3/3) © DoctorateHUB Source: Slide 17
  18. 18. Guidelines to evaluate the question  Is the research question of interest to the researcher and organization? Is the possible answer of interest?  Is it a problem that is urgent? And if it is, how would this urgency impact my open ended research?  Is the research question researchable within the time frame and resources at hand?  What methods have earlier studies applied, and is it feasible to adopt these?  Will the research produce data that can be measured, supported or contradicted?  Is the question actionable? Does it allows to act upon it. © DoctorateHUB Adapted from : Slide 18
  19. 19. The underlying complexity of question framing  There is a clear relationship between Problem (Statement), Research Question, and Outcome (Expectation).  Research Questions need to be derived from the research problem, which is only fully understood at the end of the research.  However, at the beginning of the research students frequently have an Outcome (Expectation), but no real understanding about what the actual problem is.  That Outcome (Expectation) frequently is geared towards a random solution that the researcher is advocating for.  As a result of this there is a tendency for asking questions with a bias towards random solutions, but not the problem. © DoctorateHUB Slide 19
  20. 20. The question framing / coding relation © DoctorateHUB Source: t1t0 Once data becomes available Emergent Questions Slide 20
  21. 21. Question Framing Techniques Steps to developing a research question: 1. Choose an interesting general topic. 2. Do some preliminary research on your general topic. 3. Consider your audience. Keep your audience in mind when narrowing your topic and developing your question. 4. Start asking questions. Start asking yourself open-ended “how” and “why” questions about your general topic. 5. Evaluate your question. After you’ve put a question or even a couple of questions down on paper, evaluate these questions to determine whether they would be effective research questions or whether they need more revising and refining. © DoctorateHUB <- Not only keep them in mind, engage with them. <- Engage the stakeholders and discuss the problem and let questions emerge from there. Adapted from: <- Try to also involve them in the evaluations of the problem / question match. Slide 21
  22. 22. Example Research Questions and (potential) weaknesses to understand Source: © DoctorateHUB Slide 22 The practical examples are omitted in this summary. The full slide deck is also available at the Peers4Progress class room, which provides you with a meeting place to support ongoing discussions, and collect and share resources. PLEASE NOTE: to access Peers4Progress, you will need to LOG-IN to the training space and then self-enroll at the Peers4Progress board. For newcomers to the training space: you can create an account free of charge – follow this link to create your account
  23. 23. © DoctorateHUB Be welcome to look into the following available formats: • Advanced Training Courses on Issue Identification, Problematizing and Research Question Framing Schedule your preferred start date at: • Research Execution and Thesis Crafting Workshops – to be delivered in Liverpool, UK, or other locations upon request. Schedule your preferred start date at: Do you want to train further on how to identify issues, problematize, or frame research questions? Slide 23
  24. 24. © DoctorateHUB Did you know that we provide you with the option to ”schedule your date” for webinars, advanced courses, workshops and residencies? Finally, you are invited to have it ”your way” Slide 24
  25. 25. Slide 25