Writing a Master’s Dissertation: Basic Guidelines for Novice Researchers
by Abla BENBELLAL, PhD student at Algiers 2 University (see the bottom of this page for Abla’s bio) Writing a dissertation is one of the most challenging tasks for the majority of students all over the world let alone novice researchers who have never done research before or written a paper of more than 50 pages. Thus, the aim of this short article is to provide graduate students with some basic guidelines on writing a master’s (MA) dissertation. It explicitly defines and describes the main components of the following sections and chapters in an MA dissertation: the abstract, the introductory section, the literature review chapter, the research design chapter, the results and discussion of the results’ chapter and the general conclusion. Abstract: This is generally the first section examiners read as it provides a short summary of the dissertation’s content. A good abstract consists of the following elements: A short background: here the writer needs to describe the problem under investigation briefly Purpose of the study: it answers the question (WHAT did the researcher do?) by stating the aim of the whole study in one or two sentences. Methods: it answers the question (HOW did the researcher do it?) by briefly stating the research design used, the target population and the research setting (without excessive details) Findings: it answers the question (WHAT did the researcher find?) by briefly stating the major findings of the study (i.e. those results which answer the research question(s) Conclusions: it answers the question (WHAT did the researcher conclude?) by interpreting the results and drawing inferences (i.e. explaining what the results mean Introduction: The general introduction is one of the most important sections in a dissertation as It aims at grabbing readers’ attention and interest to carry on reading your work. Thus, writing the introductory section requires a careful consideration from the writer. This section should include the following major elements: Background to the study: in this section, the writer should establish context for his/her research by reviewing some related studies. To do so, the writer should answer the following questions: How did s/he become aware of the problem? Are there any related theories or concepts that might be unfamiliar to readers and require further explanation? Are there any previous studies that should be shared to provide context on why the current issue emerged? Statement of the problem: In this section, the problem being studied should be described and explained as clearly as possible. The statement of the problem should be clear and concise. It should include all the variables to be considered (if it is a quantitative study) and state the central idea/concept of the research (if it is qualitative). In addition, it should provide information about the research setting and the target population. The research rationale (significance of the study): In the section, the writer should explain why his/her research is important by providing valid argument. Also, s/he should identify the gap in the literature and show how her/his study could fill that gap and contribute to the development of knowledge in the area of interest. Purpose of the study (or purpose statement): In this section, the writer states the overall aim of the study (i.e. what does s/he intend to do?). the following are some common introductory phrases for purpose statements: The current study investigates the relationship between…………… The main purpose of this study is…………………….. The present study is designed to examine…………………. The primary concern of this research is……………………… The purpose of this study is to address the problem of ……….. The purpose of this study is to advance understanding of………….. Research question(s): A good research question(s) should be: Clear: in order to help the researcher direct his/her research Focused and specific: in order to be well covered in the space provided Appropriately complex: that is, it should not be that simple but rather it should be a question that requires research and analysis Definitions of key terms: In this section, the writer defines the most important concepts and terms in his research to avoid ambiguity. Layout of the dissertation: In this section, the writer presents the structure of the dissertation by telling, briefly, the content of each section and chapter in the dissertation. The literature review chapter: This chapter should describe and synthesize the main theories and major studies related to the topic being studied. In this chapter, the writer should: Focus on addressing the key issues and concepts related to his/her topic. Report on the major findings of the studies and provide details about the researchers (who), the methods used (how) and the context (where). Comment critically on the benefits and major flaws of the studies being reviewed. The research design chapter: In this chapter, the writer needs to provide information about the following elements: The research design: the writer should identify and define the research design adopted (qualitative, quantitative or mixed-methods), and provide valid arguments on why a particular type of design is appropriate to reach the objectives of the study. Sampling techniques: the writer should provide a detailed description of the participants who took part in the research and how they were selected (i.e. randomly or non-randomly) Data collection instruments: the writer should describe, in details, the tools research s/he used (i.e. questionnaires, interviews, experiments…etc) how they were used to collect data and how issues of validity and reliability were addressed. Data analysis procedures: the writer should explain the procedures s/he followed to treat and analyze qualitative and quantitative data. The results and discussion chapter: This chapter involves three main sections: Data presentation: the writer presents all the findings of the study. These findings are presented using descriptive summaries (for qualitative data) and tables and figures (for quantitative data). Data discussion: in this section, the writer comments on the results by linking the study’s findings to the previous literature in the field and research question(s) investigated. S/he can also evaluate the results of the study by stating the strengths and weaknesses and assessing their generalizability to others
Publishing a (grounded theory) paper… how hard can it be?
by Catherine Hitch, PhD Researcher at Ulster University (see the bottom of this page for Catherine’s bio) I never really preferred qualitative or quantitative research; I would probably say I was a mixed methods advocate. However, when I came to develop my MSc research project I could see I was heading down the grounded theory path. I took the project design very seriously, despite still being a novice. I wanted to answer a ‘how’ question and look at process, so grounded theory seemed to be the way to go. I wanted to argue that questionnaires have many limitations, and launched into my argument that “…you need to take a qualitative approach to understanding how specific populations cope with specific health conditions, in the absence of a suitable or reliable scale”. So, I designed my study, got ethical approval, started collecting my data and began to analyse the findings. To my glee the findings began to show that this particular niche population did cope in a specific way. Also, some of the findings supported previous research whereas other findings challenged previous research. Some quite firmly supported ideas in research were contradictory to what I had found. This was quite exciting. Whilst my study was small, and it was only for a MSc qualification, it could still add something to the existing body of evidence. I felt it needed publishing, discussing and disseminating. I discussed the research at a national psychology conference, and was advised to discuss it again the following year at a medical conference. I wrote a journalistic article for a medical magazine, which set out my recommendations in terms of its implications. That was also very well received. I presented it at a conference in a poster format, where there would be a large number of attendees from the population I was writing about. The population liked it, and complimented me on how well I had captured their coping style. However, when it came to publishing it in a peer reviewed journal, that was a whole other story. It was like my paper kept being blocked. The first attempt saw the paper get approved by the editor, but was rejected by the reviewers. The main reason was that it should have been a quantitative paper (I spend most of the introduction explaining why a qualitative approach was more appropriate). The second reason was that it didn’t have enough demographic detail in it (it could be argued that this may matter less in qualitative papers, because if I am considering a ‘how’ question then the fact that a female did or did not have a degree may not matter. It may, but it may not). Nevertheless, I took this on board for attempt at publication number two. I made the introduction more robust as to why a qualitative method was appropriate for approaching ‘how’ questions, and added in as much demographic information as I could find. The second attempt was rejected outright, and I must say it was a very polite rejection, which made me feel slightly better. The editor rejected it because the sample size was too small. I had commented in the limitations that the sample was seven, but pointed out that I had seen grounded theory papers with a sample of two. Sadly, the editor didn’t agree that seven was better than two. So now we come to the third attempt. This time the paper came back with a ‘revise and resubmit’, so this time I was delighted. Despite the fact that reviewer one alone had made 85 commented, I was still delighted; it wasn’t a rejection. So, I shut the email and read it again a few days later. Bearing in mind reviewer one admitted they were not ‘qually’, they then ripped the guts out of my paper. Reviewer two clearly does have experience of qualitative papers, but both their comments would turn my paper into something completely different. I feared this difference would lead to the meaning of the paper, and the theory I had produced being lost. Beginning with the introduction, both reviewers wanted more, more, more. I had to explain that that is not the grounded theory way. They also wanted much more in the methods section, so the readers can “…judge critically whether it has been researched correctly…”. Reviewer one wanted me to alter a quote that I had used because “..that is not in line with existing research findings..”. This comment astounded me, because I reasoned that surely researchers would appreciate that everyone is different and have their own way of doing things or thinking about things? Reviewer one also wanted me to add to the discussion a comment which suggested that the author (and publishers) don’t advocate what the participants suggested, if it goes against existing research. I was also advised I needed link my theory to existing theories, which I don’t feel is necessary with grounded theory. I mean, creating a theory is about finding something new, which may compliment or challenge other theories. Isn’t the point of research partly to find new things? So, I am partly expecting the paper to get rejected again, and I will at that point send it off to another (maybe more sociological) journal. I feel that this process highlights that people are judging your paper on its worthiness to be read, by people who don’t understand the process and certainly don’t appreciate its value. Yet, we don’t know who will review the paper; that is down the editor. It’s a tough situation. As I travel through my PhD I am now discovering it is far easier to get a quantitative paper published, and many of my colleagues agree with this. Many still don’t even see the point of qualitative work, despite knowing that you can’t compare apples and oranges in many situations. It continues to be a frustrating situation, that I seriously hope will improve. At least the rejections and resubmissions give me free feedback. I am discovering yes, it’s
Is “online” the new “safe space” for conducting qualitative interviews?
Online research Over the recent years there has been a significant increase in interest in using internet for qualitative enquiry, and a number of new an innovative methods have been adopted and tested, including online ethnographies (Garcia et al., 2009; Kozinets, 2009) or analysing blog (Hookway, 2008) and Facebook (Baker, 2013; Taylor et al., 2014; Wilson et al., 2012) content. Advantages and disadvantages of Skype interviews Conducting interviews through Skype or other VoIP (Voice over Internet Protocol) technologies has also been increasingly discussed (e.g. Bertrand and Bourdeau, 2010; Deakin and Wakefield, 2013; Oates, 2015). Notwithstanding some possible challenges of this method, including potential difficulties in establishing trust and rapport, challenges of discussing difficult and “sensitive” topics, threats to the overall “richness” of interaction, technical problems (e.g. slow internet connection and/or poor video/audio quality) that may disrupt the flow of the conversation, or not being able to pay attention to non-verbal ques (e.g. gestures and body language) and the overall context of the interviewee’s environment, there are also advantages of conducting interviews online. The most commonly discussed advantages are the capacity of this method to enable us to transcend geographical boundaries and connect with participants all over the world, as well as to be more flexible and save us and the participants a lot of time. In some contexts, the fact that the interviewees are not required to be physically present at the interview may also help to reduce stress and anxiety and, as a result, benefit, rather than affect, the overall rapport between the researcher and the interviewee. The new “safe space” It is this aspect of reducing stress that I want to draw your attention to in particular. It is commonly argued in the literature on conducting qualitative interviews that one of the most important things to consider is the location of the interview. It is advised that we select the “location” that is convenient to our interviewees, the one in which they feel comfortable and relaxed. I believe, therefore, that in 2018, when over half (55%) of the world’s population has access to internet (a significant increase from just over 40% in 2015), the question we need to ask ourselves is whether the “location” should still refer to a physical environment. This, I believe, is an important issue to consider particularly when interviewing younger generations (although in 2015 over ¾ of adults in the UK were reported to use internet every day). They spend so much time online that, arguably, this is the “place” where they feel most comfortable. They are quickly becoming experts in social media platforms and they do not seem to mind sharing their views and talking to people either there or through the online games they play. At the same time, they seem to be more reluctant than we used to be when they have to interact with others (especially adults) in person. Regardless of the physical “location” that they choose for the interview, will they really open up and feel comfortable and at ease when they are taken outside their safe “online space” and have a stranger “invade” their personal space? I believe that, as researchers, we really need to reconsider the meaning of terms such as “location” or “interpersonal distance” (e.g. “social”, “personal” or “intimate” distance) in light of the global spread of the internet and the resulting changes in people’s preferences for communication. I urge you, therefore, to become “pioneers” of new and innovative approaches to research, in order to ensure that qualitative research is not stuck in the past, but rather is responsive to the emerging trends and keeps bringing about great changes in people’s lives. Reference list Baker, S. (2013). Conceptualising the use of Facebook in ethnographic research: as tool, as data and as context. Ethnography and Education, 8 (5), 131-45. Bertrand, C., & Bourdeau, L. (2010). Research interviews by Skype: A new data collection method. In J. Esteves (Ed.), 9th European Conference on Research Methods (pp. 70-79). Spain: IE Business School: Reading UK, Academic Publishing. Deakin, H., & Wakefield, K. (2013). Skype interviewing: Reflections of two PhD researchers. Qualitative Research, 14(5), 603-616. Garcia, A.C., Standlee, A. I., Bechkoff, J., & Yan, C. (2009). Ethnographic Approaches to the Internet and Computer-Mediated Communication. Journal of Contemporary Ethnography, 38 (1), 52-84. Hookway, N.. (2008). `Entering the blogosphere’: some strategies for using blogs in social research. Qualitative Research, 8 (1), 91-113 Kozinets, R. V. (2009). Netnography: doing ethnographic research online. London: SAGE. Oates, J. (2015). Use of Skype in interviews: The impact of the medium in a study of mental health nurses. Nurse Researcher, 22(4), 13-17. Taylor, Y., Falconer, E., & Snowdon, R. (2014). Queer youth, Facebook and faith: Facebook methodologies and online identities. New Media & Society, 16 (7), 1138-53. Wilson, R. E., Gosling, S. D., & Graham, L. T. (2012). A Review of Facebook Research in the Social Sciences. Perspectives on Psychological Science, 7 (3), 203-20.
(Guest post) Self-confidence is way overrated
This post was sent by Martin May Martin is a Trainer, Management Consultant, Business Coach and Managing Director, and he’s all about “effective communication skills for people who manage people”, as he puts it. The reason I find his post, and his blog in general, relevant to the content of Qualitative Researcher is that communication skills, self-confidence, self-positioning, etc. is something that is helpful in all aspects of life, regardless of one’s profession. To students, it may obviously be about presenting their work and ideas at the university; for academics and researchers it is, again, about “presenting themselves” in a broad sense – presenting at conferences, networking, trying to convince someone of our ideas, speaking in front of a panel, sitting in a job interview.. In my academic career, I made conscious efforts to work on my self-confidence. I read books, I tried to meditate, I spoke to professional trainers. Let’s see what Martin has to say about self-confidence… ——————————————————————————————————————————————————————- I often experience a lack of self-confidence. Even now, when I’m writing these words, the mixture of hesitation and anxiety flows overwhelmingly through my body. At this moment I feel like I’m losing it, I can’t get my confidence back. And the best part is that I don’t want to. What is confidence? You can trust someone’s judgements, have faith in your own abilities, or be certain about the outcome of a situation. Confidence is a belief that someone or something will turn out the way you think it should. And when this belief is applied to yourself, we call it self-confidence or self-esteem. There’s plenty of tips and tricks, articles and self-help books on how to be more confident. All are devoted to the discovery of the Holy Grail of self-confidence. Some work better than the others but… But there is a catch What if all of us are searching for the wrong thing? What if “how to be more confident” is the wrong question? I’m asking this not because I’m confident these pursuits are wrong but because I know they are wrong. How do I know? First and foremost, confidence, belief and trust all imply that you do not know. Therefore, trying to work around them is a form of a lie! You aren’t honest enough with yourself to admit that. Needless to say, if you want to improve your confidence you will have to become a greater liar. That’s not all When we’re doing well and everything seems to be falling smoothly into its place, our self-esteem grows. People like us and respect our point of view, and therefore, we feel appreciated. We see the proof of our greatness everywhere around us so we tend to be more courageous, thus we take bolder actions. In contrast, when we experience failure, rejection and disappointment our confidence drops. We slowly begin to fold in, we shrink, we hide in our shells like the tortoise when they are scared, or their life is at stake. From a lack of self-confidence, we can dive into illness, anxiety and into depression. All I’m saying is that the confidence has a shadow and it’s a very nasty one. What about self-confidence? Believing in yourself also has interesting implications. There needs to be the person that has confidence and another person in whom that confidence is placed. It looks like the beginning of a split personality disorder. So, are there two of you or is there only one? You need to make up your mind. There is a solution First off, if you’re confident that you are more than one person, please see a specialist. But if you know there is only one person and only you, then confidence is no longer going to work. And that pretty good because there is something far greater: clarity. Clarity is the state when you are free from ambiguity. It means that you can differentiate knowledge from perception, opinions from facts, beliefs from the truth. Put simply, you can effortlessly recognize and see through the bullshit. Lack of clarity is dangerous Let’s assume that you are a good driver to the extent that you could actually teach others how to be confident behind the wheel. You’re taking your usual route home but suddenly a dense fog has obscured your visibility and you can only see a few dozen yards ahead. You know this route like the back of your hand, you’ve got the skills so there’s no need to slow down. You already know how this is going to end, don’t you? We have seen this in sport, business and politics. Confidence without clarity will make you ignore crucial information and will negatively affect your judgements, causing poor decision making. In addition, it will make you gamble more – and this is not the same as taking calculated risks. So why are we chasing self-confidence? Bluntly speaking because we need a substitute. If you can’t get the number one thing you are going for, you go after the second one. As the old proverb goes better a mouse in the pot than no meat at all (or better a bird in the hand than two in the bush), and I completely agree with that. Because it’s better to be full of self-confidence rather than full of self-doubt. Having said that, I’ve decided to live with some doubts. And it’s a conscious decision. If you would like to read more about self-confidence, have a look at this article about the four cornerstones of high self-confidence, published by INLP Center.
Analysing Focus Group data
Focus Groups Focus groups are essentially a “series of discussions to obtain perceptions on a defined area of interest” (Krueger and Casey, 2009: 2). Typically, these seemingly informal discussions occur in a group of no more than 12 individuals (Asbury, 1995; Smithson, 2008), who share some common characteristics (Franz, 2011) and “have a direct experience of the topic” (Acocella, 2012: 1127), and, thus, are treated as ‘experts’ (Stewart and Shamdasani, 1990). These discussions are facilitated by a moderator. Analysing focus group data The analysis of focus group data can be quite complex, and involves both the verbal content of the debate and the non-verbal communication. Still, focus group data are often under-analysed and used, for example, to simply report emerging themes and coding frequency. When preparing this post, I did a quick online search for what people say about focus group analysis and immediately found comments such as the following: “analyzing focus group interviews is not greatly different from analyzing one-person interviews.” “I personally think that the analysis of focus group data is not much different from the analysis of any other kind of interview data. Most people who ask for specific analytic tools in focus groups do so because they don’t have experience with analyzing other kinds of qualitative data, so they think there must be something unique about focus groups.” … Needless to say, they couldn’t be more wrong. Focusing exclusively on individual participants’ accounts (which would be the case if “the analysis of focus group data [was] not much different from the analysis of any other kind of interview data”, as suggested above) would mean that we are overlooking the most unique and valuable aspects of focus group discussion – the group’s views and group dynamics. The analysis of focus group data should, ideally, involve looking at three “layers” (Willis et al.) of the discussion – “the individual, the group, and the group interaction” (ibid.). Importantly, these different layers are not necessarily “steps” – thus, in practice, the analysis of one layer is difficult to separate from another (although I think there are also some guidelines that suggest doing so). When you investigate the “individual” layer, for example, not only do you want to pay attention to all views and opinions expressed by one group member throughout the discussion, but also to how this participant “functioned” within the group (were these views relevant to what was being discussed, were they similar to/conflicting with the group’s views, etc.), to whether these views changed throughout the discussion (were they influenced by the discussion? Did they emerge because of some other participant’s views?), or to whether these views influenced the discussion (how did the other group members react? Were these views supported? Or ignored? Was the participant silenced?). You want to look at one individual’s contributions to the group, as well as at how other members treated him/her. You may also see if this person tried to reinforce his/her opinion more than once and, again, how the group reacted. Similarly, when you focus on the “group” and the “group interaction” layers, it is not possible to ignore the individual roles. When you look at whether the group achieved a “common ground”, or a kind of a shared identity or self-positioning, you need to pay attention to how the individuals constructed this identity together and how each participant responded to the construction of this identity (did he/she contribute to it, and self-positioned him/herself as a group member? Did he/she distance him/herself from the group?). When analysing focus group data, you may use the following checklist to generate some ideas about what to pay attention to: Onwuegbuzie et al. (2009) propose another useful structure for focus group analysis which is centred around a combination of different data analysis techniques – constant comparison method (which may involve comparing themes emerging in different focus groups), content analysis (e.g. coding the content of the discussion and paying attention to coding frequencies), and keywords-in-context and discourse analysis, both of which involve careful examination of the use of words, and language as a whole, throughout the focus group discussion (at both the group and individual levels). I would not even want to try to discuss focus group analysis in much detail in such a short blog post, but I do hope that the above gives you a general idea of what it may involve (and that you will understand that it is definitely NOT the same as individual interview analysis!). Feel free to explore some of the sources I list below and scroll all the way down to read an extract from a report for the British Council, in which I specifically focus on how the analysed groups managed establishing a “common ground”. REFERENCES Acocella, I. (2012). The focus groups in social research: advantages and disadvantages. Quality & Quantity. 46 (4), 1125-1136. Asbury, J.-E. (1995). Overview of Focus Group Research. Qualitative Health Research. 5 (4), 414-420. Franz, N.K. (2011). The unfocused focus group: benefit or bane? Qualitative Report, 16 (5), 1380-1388. Krueger, R., & Casey, M. (2009). Focus groups: A practical guide for applied research. 4th Ed. Thousand Oaks, CA: Sage Publications. Onwuegbuzie, A., Dickinson, W.B., Leech, N.L. & Zoran, A.G. (2009). A Qualitative Framework for Collecting and Analyzing Data in Focus Group Research. International Journal of Qualitative Methods, 8 (3), 1-21. Smithson, J. (2008). Focus groups. In Denzin, N. and Lincoln, Y. (eds.) Handbook of Qualitative Research. 2nd Ed. Thousand Oaks, CA: Sage Publications. Stewart, D.W. & Shamdasani, P.N. (1990). Focus Group. Theory and Practice. Newbury Park: Sage. Willis, K., Green, J., Daly, J., Williamson, L. & Bandyopadhyay, M. (2008). Perils and possibilities: achieving best evidence from focus groups in public health research. Australian and New Zealand Journal of Public Health, 33, 131-6. Extract from my focus group results section in Galloway, Kriukow and Numajiri (2017: 29) “A deeper analysis revealed that the discussed topics and opinions shared by the groups varied in relation to the ways the participants were establishing common ground and positioning the group as a whole, as well as self-positioning themselves within the group (Hydén and Bülow, 2003). For example, in the Hubei focus group, where all the participants majored in English education, they established a collective voice of ‘English majors’ quite effortlessly, and constructed their narratives as a group of ‘experts’ in their field. They spoke of
Tips on how to ‘unlock’ your data analysis
A common problem with analysing qualitative data, which both students and more experienced researchers face, is… simply getting stuck with it. It’s like writer’s block, but in data analysis – you may have all the necessary components in theory, but you are not sure what to do with them. You are not sure what to analyse and how, where to look, what to focus on, etc. Here are some steps that always help me “unlock” my data analysis and dig deeper into the data (the order is random, you may apply some, or all of them, and at various stages of your work): Read through the data, without worrying about coding. Try to get the overall “feel” of it, occasionally recording some thoughts that may occur (e.g. if you see patterns across the data, some similarities/differences, something that you think could turn out to be significant, etc.) Try to sketch a simple model of what you see in the data. You can either do it with a computer software (data analysis software, such as NVivo, or specific software for designing models – I have used https://www.draw.io/) or by hand. I quite often do it on a separate piece of paper, which results in hundreds of pages with weird and difficult to interpret “hieroglyphics” scattered around my house. In the model, try to “theorize” about your data, potential links, relationships and associations between different elements of your project (e.g. the themes you develop, or certain experiences/beliefs described by your participants), possible causal relationships (e.g. this seems to result in that) and other things you notice. This is supposed to be theoretical, so don’t be afraid to make assumptions and jump into conclusions – this is Exactly what you need. As a result, you have a whole bunch of possible relationships, assumptions and “hunches” to investigate and check if they are, in fact, true. Write about your data (you can do it as a free writing exercise) – again, as with the model, write about what you have found, as well as about what you think you may find, write about everything that seems to be relevant in any way. Similar to drawing the model, this may help you “open up” your data, come up with ideas that you may later explore and investigate (and this will be the actual analysis part of your data analysis) Run word frequency queries – to see which words appear most frequently in your data. This sometimes helps to draw your attention to issues that you previously did not pay attention to “Dig deep” into what the content of what the participants said meant to them – go beyond simple factual information that they convey, try to see who said something, how they said it, under what circumstances, when they decided to talk about it (e.g. which interview questions prompted them to give a certain response), see what followed these thoughts, what they chose to speak about (e.g. do they always talk about stressful experiences at school when you ask them about their childhood?), what kind of emotions they seem to experience when discussing particular topics, etc. Conduct a detailed “within-case analysis” – focus on each participant individually, considering some of the points made above, as well as whether one participant changed his/her opinion within the same interview, how he/she reacted to similar questions asked at different stages in the interview, etc. If you have a coding framework, analyse it in detail for one participant at the time. Try to draw a model for each participant. Write a case summary – summarize what a given participant said, what your thoughts and observations based on this are, etc. If you have more than one data set for an individual participant (e.g. an interview transcript, a diary, open-ended questionnaire responses, etc.), treat them as one “case” and explore all these data sets in detail. Conduct a detailed “cross-case analysis” – follow similar steps but this time with the aim of comparing the “cases” (e.g. different participants), looking for similarities and differences, comparing these similarities/differences in relation to (demographic) characteristics of the participants (e.g. did those with more teaching experience express more positive attitudes towards something than those with no experience, did men express similar opinions to women, did students share similar views to their teachers, etc.) If you have a coding framework – create matrices that compare the coding between the participants in relation to the above kind of characteristics (in NVivo, this is called a matrix coding query) Check whether the participants repeat similar points, whether there are re-occurring patterns, when these patterns occur Investigate “negative cases” – these are the cases (e.g. participants) that, for any reason, do not “fit” the rest of cases or your emerging “theory” or explanation (e.g. what one single participant said is completely the opposite to what all, or the vast majority of, the others said). I love investigating negative cases – remember that they don’t “ruin” your theory, or your analysis in general, but rather enrich it and provide a lot of new insights Do you have any other tips for “unlocking” your data? Please share them in the comments!