Reflections on “Qualitative Data Analysis”

During the last term I attended the course “Qualitative Data Analysis” of the Psychology Department, which has introduced methods of Qualitative research I did not know before and given me a deeper understanding on how to analyse data. While much of the course has been given as talks, the role, aim and methods of qualitative methods have been discussed throughout. In addition to giving overviews about the topics, the lecturers both gave examples from their own work; explaining how they applied this theory.  The course consisted of four parts, which were: Introduction to qualitative research methods, Data elicitation, Thematic Analysis and Q-Methodology.

In the introduction the lecturer showed an interesting example in which the researcher team compared representations in the media with lay understandings. Going into details how techniques have been combined, I found that inspirational and very useful to consider. I think I am still very ‘one-dimensional’ when planning data collection and hope this is something I can improve on during my PhD.

In the second part “Eliciting data” the lecturer introduced interviews and the Free Association Method as examples. While I had short training sessions about interviewing, this session had a different approach. The lecturer emphaised the use of open questions to avoid asking the participants “Why do you think this?”, but rather work with the participants words and ask them to expand on them. Taking part in an interview shortly after I learned for myself how complicated it is to rationalize certain exclamations and how intimidating it can be. Even though it is such a small thing, it made me question the way in which I would approach an interview and I hope it will support my work in future. Even though useful, the lecturer warned that interviews are ‘time consuming and costly’ and therefore need to be planned carefully and with a strong research question to make the best of the time people offer.

This seminar was the first time I came across the Free Association method and it is one that I consider quite useful as a way to elicit quick, associative responses. Like probes these seem useful to start a conversation about a topic, in a very open way; ‘naturalistic’ as the lecturer called it. She introduced the grip elaboration method, as a way to elicit ‘first thoughts’ which lay latent in people’s thinking. These responses can then be used in further interviews to learn more about the reasoning behind them.

Interestingly the seminar part on “Thematic analysis” fell into the time when I was doing the analysis of my study from the 32C3 congress. As I was struggeling with analysing the data at the beginning, this course gave me new angles with which to approach the data. The point I struggled with the most at the beginning was the question how not to focus on the literature I read before. While I wanted to approach the data deductively, I felt I was guided a lot by the topics I had already identified in the literature research initially. Using an initial coding frame, I was able to divide the data in new ways that made it easier for me to approach it in new ways. I came accross this method in the seminar and discussed the problem of being too close to the data shortly with the lecturer, which both gave me new inputs for working with the data.

Even though I had not been able to attend the labs in which a data analysis using Atlas.ti was undertaken, though this course I do have an initial idea on how to approach this, when it might be useful to use an analitical tool and many sources with which to train myself, should I need it. As for my own analysis the amount of data was quite small, I felt it might be limiting to use a tool and I also felt it would be a useful experience to do it “by hand”. Learning about the arguments for and against using tools, I feel I am now more fluent in arguing why and how I undertook the analysis.

The lecturer put a strong emphasis on quantitative elements with qualitative research, e.g. when highlighting that she always gives the number of codes within a data set when reporting the data. The emphasise differs from the way  Braun and Clarke approach the analysis. It was useful to see different ways in which people interpret the same method. For this analysis I have chosen a less quanitative way, but I can see how this is more interesting with a larger data set, in which relations might become more meaningful.

The section on Q-Methodology was completely new to me as I had never heard of this technique. It differed from the other methods introduced as it was more prescriptive in my opinion. While techniques such as Free Association put a strong emphasise on working with the participants voice, Q-Methodology gives pre-defined statements to work with. Even though these might be generated from the participants themselves, I found the technique less approachable from this point of view. I nonetheless think it might be useful tool to approach ‘wicked questions’ such as the question about autonomy and privacy in my own project and I could imagine using it at a later stage.

Evren though we did not build up our own q-set, we sorted the data and tentively analysed it in the week after. The lecturer had the statistical evaluation prepared and we have been able to work with the data and go into the qualitative analysis. It was an interesting experience to see both sides of the technique.

As I was already thinking about using qualitative methods in my research, the course did not change my mind. But it helped a lot to learn more about different approaches towards qualitative analysis and enriched my knowledge of what tools and techniques are out there. It has supported my first analysis and given me more confidence in approaching analysis.


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