In the first of our pre-reading posts, Barry Ryan introduces his topic: thematic analysis. After the abstract, Barry has some prompts on how different readers might engage with the pre-reading on his topic. Register for MICER18 here.
Quite often non-numerical (i.e. qualitative) data is collected as part of (chemical) education research projects. Such data could, for example, be derived from interviews, discussion groups or free-text responses in surveys. This rich data set holds the potential to enlighten the underpinning research question; however, how to unpick and rationalize this complex data mixture can be challenging. One methodological approach to address this challenge is to execute a rigorous content analysis of the data. Content analysis is defined as “a strict and systematic set of procedures for the rigorous analysis, examination and verification of the contents of written data” (Cohen, p475). By extension, thematic content analysis is connected by themes.
Qualitative data can generally be explored in one of two ways; applying pre-conceived delimiters or categories (referred to as deductive analysis) or allowing the categories to emerge during the data interrogation process (referred to as inductive analysis). Deductive analysis can lead to converging conclusions; whereas an inductive approach allows the analysis to diverge and to capture unexpected outcomes and findings. As a researcher approaches their data with little or no pre-conceptions of the findings the data will unlock, inductive analysis can be more demanding, time-consuming and requires a rigorous technique to ensure validity. Thematic content analysis is a common inductive analysis approach.
Thematic content analysis has been summarised by Ezzy (2002, p83) as the Four Cs: coding, categorizing, comparing and concluding. Interweaved into the Four Cs is the understanding that the collection and interrogation of a data set should be valid. This is to minimise inherent human bias and errors in data collection and interpretation from projecting into the findings generated. Here, key points such as data triangulation, data saturation, constant comparison and auditability should be considered when researching alone. If collaborative qualitative research is carried out, then additional fail-safes, such as inter-rater reliability, may also be incorporated. Applying a framework to an inductive thematic content analysis approach is recommended for those new (and maybe not so new!) to this methodological approach. One of the more user-friendly frameworks is Braun and Clarkes Model (2006) schematically depicted in Fig 1. This systematic framework will be the basis of the interactive MICER workshop; however, alternative models will also be explored along with software assisted techniques.
The workshop will be underpinned by a previously published (Ryan, 2016) investigative case study that employed thematic content analysis as the primary tool of data interrogation. Through collaboratively engaging with this workshop, participants will be able to:
- Identify appropriate data types for content thematic analysis (Recollection)
- Apply Braun and Clarkes’ (2006) model to code and theme sample qualitative data; with and without an existing set of codes (Application)
- Interpret codes and construct valid themes from sample qualitative data (Analysis)
- A set of guidelines to ensure data validity and discuss how they relate to best practice (Creation)
- Relate their current qualitative data interrogation practice to existing best practice (Evaluation)
The seminal paper for the thematic analysis session is Braun and Clarke (2006) (Accessible here). Although complete reading of the paper is recommended; it is lengthy (25 pages!), so a more targeted approach can be taken ahead of the workshop. This targeted reading is divided based on prior experience with completing thematic analysis:
If you are new to thematic analysis it may be useful to review the summative table (Table Three) detailing the advantages of thematic analysis and consider why you would use thematic analysis in your PedEd Research.
see Table Three: Advantages of thematic analysis (pg. 96)
If you have completed some thematic analyses, it may be useful to consider your approach and reflect on the structured Braun and Clarke model; summarised in Table One and explored in more detail in Table Two.
see Table One: Phases of Thematic Analysis (pg. 87)
see Table Two: A 15-point checklist of criteria for good thematic analysis (pg. 96)
I am a research active applied biochemist who enjoys blurring the academic lines between teaching, learning and research. As an active practitioner I am engaged in the development and execution of high quality, often technology enhanced, learning experiences and I am enthusiastic about sharing my research informed pedagogy with the MICER community. Participation at MICER will allow me to positively influence, and give back to, my community of practice and the wider evidence-based teaching community more generally.
As a novice educator, I felt ill-equipped to support my students learning and, at the time, I did not have a suitable community to support my development. To overcome this embarked on a long journey of self-development. To deepen my understanding of best practice in education and educational research, I have completed three postgraduate qualifications (Postgraduate Diploma in Higher Education, MSc in Applied eLearning and MA in Higher Education). Furthermore, I have successfully completed several substantial and rigorous educational research projects; as part of accredited higher qualifications and as standalone research projects, as lead and principal investigator. As a research active educator, my expertise and impact have been recognised within my own discipline by institution level awards (DIT Presidential Teaching Award; 2012 and 2013) and outside my discipline at national level (Jenifer Burke Innovation in Teaching Award, 2014). I have also been accredited as a Senior Fellow of the HEA (2016).
My workshop at MICER will focus on a methodological instrument (content thematic analysis); however, my broader pedagogic research interests lie in areas such as the first year chemistry experience for non-chemistry majors, embedding industry relevance and graduate attributes into early year undergraduate programmes, empowering the graduate teaching assistant, diversifying and enabling the final year dissertation student and exploring technology facilitated learning in labs and lectures.