Confronted with an overwhelming amount of data? Thematic Analysis provides a remedy.
Qualitative data analysis may look very intimidating for novice researchers at the first glance; a notebook full of field notes, hours of conversations with many different people, and hundreds of images or documents to go through. How come it is manageable for researchers to analyze such a large amount of data and create two or three bullet points that answer research questions? Thematic Analysis is one way to make this happen. It is a systematic approach to identifying, organizing, and offering insights into patterns of meanings, in other words, themes across qualitative data (Braun & Clarke, 2012). In this blog post I will guide you through the steps of a Thematic Analysis and how you can use MAXQDA for it.
What is a Thematic Analysis?
Thematic Analysis has become one of the most commonly used analytical approaches for social sciences over the last few years. Braun et al. (2019) suggest that it has a shared history with Content Analysis and has started to appear in health and social sciences studies as a qualitative data analysis approach by the 1980s. A quick search on Google Scholar with the key term “Thematic analysis” (in-between quotation marks) brings more than 370.000 results. A key article alone, Using Thematic Analysis in Psychology authored by Braun and Clarke (2006), was cited more than 126.000 times by May 2022. These easily accessible data indicate the popularity of this approach. This popularity may be related to the modularity and flexibility it affords to researchers who analyze qualitative data. However, it is also a very systematic process that needs to be recursive. To add, Thematic Analyses require researchers to get immersed in their data set immensely. To systematize this process, Braun and Clarke (2006, 2012) proposed a six-phase procedure of Thematic Analysis to guide qualitative researchers.
The Research Project
In this blog post, I will share a recent publication of mine as an example of how I used MAXQDA to advance the six-phase Thematic Analytic approach. In this qualitative study, I intended to explain the online professional development experiences of English as a foreign language (EFL) during a massive open online course (MOOC) on teaching languages online. This study was entitled “How massive open online courses constitute digital learning spaces for EFL teachers: A netnographic case study”; and as the name suggests, I employed ethnographic methods to investigate the online experiences of two EFL teachers, as qualitative cases. A comparative case study with two participants as cases might feel that it will not yield so much data but, on the contrary, one typical characteristic of ethnographic studies is that it requires the researcher to get immersed in the culture investigated over an extended period of time.
The Research Data
To add, the multimodal nature of qualitative data provides a wide range of possibilities for qualitative researchers to collect data; accordingly, I drew on digital learner diaries (that included case participants’ reflections throughout the online learning experience), semi-structured interviews, and screenshots illustrating participants’ online forum posts and similar contributions in the online course. Intending to investigate the participants’ experiences in an explanatory way without a reconceptualized theoretical or conceptual framework in mind, I used inductive coding and Thematic Analysis. Throughout this tentative process, several features of MAXQDA informed each phase of my Thematic Analysis.
The Six Phases of Thematic Analysis
Figure 2: Document System of my research on MAXQDA 2022
First, MAXQDA’s Document System allowed me to experiment with grouping my data in various ways. As my study was a comparative case study reporting on the experiences of two case participants (Teacher 1 and Teacher 2, see Figure 2), I have decided to group data by participants.
Transcribing the Data
Secondly, I have uploaded different data types such as audio files and images. As I collected audio diaries from two different sources who had used different devices to record their diary entries, I had to deal with two different data formats. With MAXQDA, I was able to upload and play audio files in these two data formats without any difficulty. Last, I have used the transcribe audio file feature. Creating timestamps while transcribing data enabled me to go back to particular parts of the audio files and listen again and again, which is crucial for me while familiarizing myself with the dataset.
Phase 2: Generate initial codes
Coding in Thematic Analysis
Once the Document System takes some shape, qualitative coding starts. According to Braun and Clarke (2012), codes are “the building blocks of analysis” (p. 61) and help researchers make sense of their data in light of the tentative research questions. According to Kuckartz and Rädiker (2019), researchers select part of the data and assign it a code, which can be done in two generic ways, the concept-driven, deductive approach and the data-driven, inductive approach. In Thematic Analysis, coding can be conducted in both ways, and the coded segments may cooccur and interconnect.
Looking out for emerging codes
Feeling immersed in my data, I started to generate my initial codes. With no pre-conceptualized theoretical framework that particularly shapes my analytical lens, I relied on data-driven, inductive coding and looked for emerging codes and code groups. I have completed coding through my entire dataset. In my initial code generation process, I have used two features of MAXQDA extensively: open coding and Memos. Open coding with MAXQDA was very a very intuitive experience, and Memos helped me to trace back my original rationalizations when I created a new code for previous coded segments. These Memos helped me if I can reuse previously created codes across 22 files that I compiled in my Document System.
Phase 3: Search for themes
Looking out for emerging themes
After feeling saturated with coding and recoding all data sources included in the Thematic Analysis, I moved from codes to themes. According to Braun and Clarke (2006), themes are “patterned response or meaning within the data set” that somehow relates to the research questions (p. 82). Searching for themes is a very active process in which the qualitative researchers actively construct themes rather than discover them even though the name of the phase is “searching” for themes. Braun and Clarke (2012) liken researchers searching for themes to sculptors making choices that will profoundly influence the end-product of sculpturing instead of archeologists digging for some fossils (i.e. themes) that are embedded in the data regardless of the dirt to be removed around them. That resonated with me as a qualitative data analyst in my research because my entire analytical lens was data-driven and my research questions aimed to understand rather than explore. In tandem with this, I needed to be an active meaning-maker rather than a passive observer; I needed to communicate with my data and make sense of it while constructing themes.
Discovering patterns through visualizations
MAXQDA offered me a lot of choices to be a more active analyst while communicating with my data at a conceptual level. Personally, it is easier for me to synthesize information when I have visual input; accordingly, charts, images, and data visualization help me to see a relationship between codes and emerging themes as well as documents and participants. Similarly, summative workflows and pipelines help me situate myself in the long process that is required for most qualitative data analysis approaches including the thematic analysis. To this end, I have benefitted greatly from three particular features of MAXQDA: Code Maps, MAXMaps, and Questions, Themes & Theories (QTT).
Gaining a holistic view
Figure 3: Screenshots from my QTT worksheet
In figure 3, I illustrated two screenshots from my QTT worksheet that I used in my data analysis. First of all, MAXQDA allows researchers to generate Code Maps that analyze the relationship of codes as they co-occur or occur within certain proximity across data documents. I always start with Code Maps because they take little effort to create and it helps me to take a meta-position after the long and repetitive process of immersion and coding; taking one step back and having a more holistic view of my codes and their relations with each other. However, as I explained earlier, this is one way to start the process and it should not be the last one because Thematic Analysis requires researchers to be actively involved in the meaning-making process.
Using the QTT for Thematic Analysis
This brings me to another very important visualization tool of MAXQDA: MAXMaps. MAXMaps afforded me a space for stimulated brainstorming over my codes and initial themes. In this space, I could retrieve codes and documents as icons, create and signify relations between them with links and arrows, and create code models. Last, with the latest version of MAXQDA, I could create a QTT worksheet that enabled me to import related codes and themes, coded segments, and all the visual materials that I created into one worksheet. On this worksheet, I could return constantly to my research questions and memos when I strived to move from my questions to themes, and even beyond them, my theories later.
Phase 4: Review potential themes
In this phase, the themes constructed in the previous phase are reviewed and cross-checked against the entire code system, coded segments, and documents. The themes, data, and research questions need to be relevant and in alignment. While doing so, researchers can combine some emerging themes to reach overarching themes whereas some emerging themes might get singled out and found irrelevant even though they might seem very interesting.
Guiding questions for a Thematic Analysis
I benefitted from some key questions suggested by Braun and Clarke (2012, p. 65) to review the potential themes and construct overarching themes by combining multiple emerging themes. I adapted those guiding questions to my research context as follows:
These guiding questions were useful for me but still, I needed to adopt smart ways to deal with them.
Detecting central themes with MAXQDA’s Visual Tools
MAXQDA afforded other Visual Tools that guided me even further. I utilized Code and Document Matrices to review and decide whether my initial themes are strong ones and whether I can construct relevant overarching themes out of them.
First, I used the Code Relations Browser to further understand the relationships between codes. One implication that I drew from this matrix, for instance, is the strong relationship between my case participants’ feeling of engagement and the MOOC platform’s facilitation. This led me to go back to my coded segments and to decide if I can construct a theme out of this relationship and if there is any other code that can be linked to this relationship (e.g., flow).
Figure 4: Code Relations Browser
Similar to the Code Relations Browser and Matrix, the Document Comparison Chart also helped me to review my initial codes by using the guiding questions of Braun and Clarke. After applying colors to the codes in my code system (see my code system on the left part of Figure 4), it can be seen that all audio-diary entries include pink blocks which indicate that the case participants revealed some kind of learning experience (e.g., new understanding, engagement, reflection, flow, or multimodal learning). Likewise, my interview data also implied participants’ reflections of their existing or developing digital literacies (red segments).
Figure 5: Document Comparison Chart
Phase 5: Define and name themes
This is also another phase of a Thematic Analysis that is closely related to the previous one. While reviewing the emerging themes and constructing the overarching themes, researchers conducting a Thematic Analysis need to make sure that these overarching themes are not repetitive, or they do not overlap (otherwise, they may need to be combined). It is also suggested by Braun and Clarke (2012) that researchers should only define and name themes when they have singular foci and address research questions.
Staying in focus with the QTT
In this phase, QTT helped me to keep my research questions constantly in mind (see Figure 3), and I reached four overarching themes: (1) the self-regulatory impact of the MOOC, (2) the provision of an online learning experience, which demystified online teaching, (3) preparing the pre-service EFL teachers for a teaching career, and (4) limitations due to the massiveness and non-situatedness in MOOC designs.
Defining themes through codes
MAXQDA’s Code System supports this process in many ways. I have specifically used the possibility of coloring the themes. Similarly, highlighters and code favorites can also help the process. Another easy thing to do is the ability to drag and drop codes across the entire Code System and create code nodes to group sub-codes. This allowed me to create code families, which helped me while defining and naming my themes.
Phase 6: Produce the report
Even though the final phase of the Thematic Analysis might seem like a happy ending for I had the overarching themes and relevant coded segments, it was actually a very tricky one. As with all qualitative research approaches, Thematic Analysis is also a very recursive process, and unlike quantitative research, it does not have a phase-gate process where the phases are initiated only when the previous phase is concluded. On the contrary, thematic analytic reporting required me to go back even to the very first phase of the data analysis because I simply needed to refamiliarize myself with the data to construct the overarching themes.
Figure 6: Integration of insights page of my QTT worksheet
Bringing everything together
This process of going back and forth really made me feel immersed in my data. This is important to report a Thematic Analysis because a thematic analytic report should include a “compelling story” [for the reader] about [my] data based on [my] analysis” (Braun & Clarke, 2012, p. 69). On the last page of my QTT worksheet (See Figure 6), I brought all my overarching themes together with my research questions and integrated them into insights, drew conclusions, and developed hypotheses. Another feature I used extensively was to retrieve coded segments to the important segments tab and linked them with overarching themes. This also helped me it was time to write down the findings and discussion sections of my research paper.
Qualitative data analysis and more specifically Thematic Analysis might look like a daunting task in which researchers need to spend a lot of time making sense of the data and synthesizing hypotheses out of them. Unlike quantitative data analysis software, which makes me feel detached from my data due to its point-and-click interface, qualitative data analysis software affords ways to really get immersed in the data set, which is paradigmatically crucial for successful (and meaningful) qualitative research.
Figure 7: The continuous cycle of Thematic Analysis (adapted from Braun & Clarke, 2006, 2012)
Creating a recursive cycle of meaning-making with MAXQDA
Thematic Analysis is an approach that requires researchers’ extensive immersion in their data. MAXQDA’s many features helped me a lot to feel immersed. With those features, I could feel like “the sculptor” (Braun & Clarke, 2012), who made choices and decisions along the way of creating something out of a block of stone. This made it possible for me as a researcher to have a voice of my own in the data analysis process. This process made the recent conversation around the Thematic Analysis that reconceptualizes the six-phase approach as a reflexive process (see Braun et al., 2019; Braun & Clarke, 2019, 2020). Another useful affordance of MAXQDA in my Thematic Analysis was that I was able to go back and forward the phases Thematic Analysis. With this affordance, my Thematic Analysis felt like a real recursive process as in Figure 7, instead of a more phase-gate process only listing the phases of Thematic Analysis in linear order as in Figure 1. This way, I was able to see how these phases communicate with one another, creating a continuous and recursive cycle of meaning-making.
NOTE: This post is based on my research experience as a user of MAXQDA. The abovementioned research project has been reported and is currently in press to be published in the June 2022 issue of The Journal of Teaching English with Technology.
- Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101. https://doi.org/10.1191/1478088706qp063oa
- Braun, V., & Clarke, V. (2012). Thematic analysis. In H. Cooper (Ed.), APA handbook of research methods in psychology Vol 2: Research designs (Vol. 2, pp. 57–71). American Psychological Association. https://doi.org/10.1037/13620-004
- Braun, V., & Clarke, V. (2019). Reflecting on reflexive thematic analysis. Qualitative Research in Sport, Exercise and Health, 11(4), 589–597. https://doi.org/10.1080/2159676X.2019.1628806
- Braun, V., & Clarke, V. (2020). One size fits all? What counts as quality practice in (reflexive) thematic analysis? Qualitative Research in Psychology, 00(00), 1–25. https://doi.org/10.1080/14780887.2020.1769238
- Braun, V., Clarke, V., Hayfield, N., & Terry, G. (2019). Thematic analysis. In P. Liamputtong (Ed.), Handbook of research methods in health social sciences (pp. 843–860). Springer. https://doi.org/10.1007/978-981-10-5251-4_103
- Kuckartz, U., & Rädiker, S. (2019). Analyzing Qualitative Data with MAXQDA. Text, Audio, and Video. Springer. https://doi.org/10.1007/978-3-030-15671-8
About the Author