Given the exploratory nature of this mixed-methods multiple case study, my data analysis plan incorporated three primary analytic strategies designed to facilitate the integration of findings across data sources.
Phase 1—Survey analysis: Descriptive statistics and data visualization
Considering the smaller sample size in this dissertation, I optimized the quality and robustness of findings by relying on a variety of descriptive (e.g., Loeb et al., 2017) and small-N (e.g., Smith & Little, 2018) analytic techniques. I used measures of central tendency and variation to describe teacher candidates’ endorsement of perceptual frameworks and enactment of practices for equity on pre- and post-surveys. Additionally, using empirical growth plots (for an overview of this method, see Singer & Willett, 2003), I visualized weekly diary data on teacher candidates’ transformative teacher education experiences (i.e., course activities, fieldwork experiences around race) as well as knowledge of and motivation to implement equitable teaching practice over time. Through this data visualization, I was able to note patterns of change in teacher candidate’s affective/motivational course experiences as well as knowledge of and motivation to implement equitable teaching practices in relation to transformative activities. These strategies allowed me to understand both how teacher candidates’ perceptual frameworks changed between pre- and post-
surveys—perhaps as a result of transformative activities—as well as how teacher candidates’ weekly development of knowledge and motivation to implement equitable teaching practices varied over time and across transformative activities.
Phase 2—Interview analysis: Data reduction
To better understand the characteristics, experiences, and outcomes of transformative teacher education activities, I used a two-cycle coding process. First, a graduate student who served as a second coder for consensus in this analysis and I generated a list of potential codes while reading interview transcripts and reviewing prior literature. The resulting first-cycle coding scheme employed descriptive coding techniques (for a review of these techniques, see Saldaña, 2013) to reduce the data into excerpts most relevant to our constructs of interest (i.e., biographical factors, transformative activities, perceptual frameworks, and learning about racial equity in teacher practice). First-cycle coding was done in NVivo (version 12; NVivo, n.d.) and yielded a total of 74 accounts of transformative activities that explicitly addressed race or equity. In terms of equity-explicit transformative activities, we included both activities that explicitly addressed racial equity as well as those that explicitly addressed equity with regards to other oppressed identities (e.g., gender, sexual orientation, religion, income/socioeconomic status). On average there were 15 race/equity-explicit transformative activities per participant, with a range of nine to 18 activities per participant). Because some participants were enrolled in the same classes and were placed in the same district for student teaching, there were instances in which multiple participants shared their perspective on the same transformative activity. See Appendix Table 1 in Appendix D for the first-cycle coding scheme.
In the second cycle of coding, I reviewed only excerpts coded as transformative activities and used a causation coding strategy (for a review of this strategy, see Saldaña, 2013) to generate attributional chains representing teacher candidates’ meaning making of their experiences with transformative activities. I did this by re-reading the transformative activity excerpts and identifying the antecedents and mediators to which teacher candidates attributed their responses (i.e., local interpretations) and shifts in their perceptual frameworks or understanding of equitable practices (i.e., generalized interpretations). On average there were two attributional chains for each transformative activity with a range from one to 12 attributional chains. To facilitate future steps in analysis, interpretations of each attributional chain were written to capture the process by which teacher candidates used transformative activities to challenge their perceptual frameworks and learn about racial equity in teacher practice. See Appendix Table 6 in Appendix E for an example of the causation coding strategy.
Once all coding was complete, I wrote a memo (for a review of memoing, see Saldaña, 2013) for each case compiling the attributional chains from the second round of qualitative analysis and reflecting on how the emergent findings aligned with or departed from existing theory.
An expert in qualitative research was consulted just before and after each of the three stages of qualitative data analysis (i.e., first-cycle descriptive coding, second-cycle causation coding, case memoing). The expert provided suggestions on the wording of first-cycle codes (e.g., changing “biographical influences” to “biographical factors”) and the process of reducing data. For most codes, we decided to first code at the highest level and then review excerpts to identify and apply lower-level codes in subsequent rounds. However, lower level codes for perceptual frameworks were applied in the first round of coding because they were clearly defined and largely determined by prior literature. The expert also advised creating a validation check to confirm through evidence
in participants’ language that activities identified as transformative by coders were, in fact transformative for teacher candidates. To do this, the second coder and I generated lists of words, phrases, and sentence structures that indicated “transformation.” Examples included transition words (e.g., before/after) and verbs (e.g., change, shape, improve), as well as sentence structures (e.g., then… but now…). See Appendix F for the full details of the transformative teacher education activity validation tool. Out of the 74 race/equity-explicit transformative activity excerpts, 58 excerpts (about 78%) had one or more transformative activity validation words/phrases. On average there were four words/phrases from the validation list per race/equity- explicit transformative activity excerpt. The expert also provided guidance on how to format the causation coding analysis (i.e., in an excel table) and recommended focusing on connections to theory in the case memos.
Phase 3—Meta-inferences of survey and interview findings: Comprehensive case summaries
Once quantitative and qualitative analyses were completed separately, I aimed to generate a deeper understanding of transformative teacher education activities by integrating findings from each method using the following a thread approach (for a review of this approach, see O’Cathain et al., 2010). Specifically, I expanded on the qualitative case memos by inserting quantitative findings from the weekly diary surveys that matched the activities described in each interview. I used information about course and placement activities from course syllabi and weekly diaries to link qualitative and quantitative patterns that occurred across the semester. Positioning quantitative and qualitative findings side by side (see Fetters et al., 2013 for a review of this strategy) in the case memos helped me evaluate confirming, disconfirming, and complimentary evidence across
analytic approaches for each research question (for a review of this type of mixed-methods analysis, see Creswell & Plano-Clark, 2018). Finally, using Stake's (2006) multiple case study analysis worksheets, I drew meta-inferences across data sources both within and across cases. Such meta-inferences are a powerful way to improve the quality and insightfulness of conclusions from an empirical study (Creswell & Plano-Clark, 2018). As final validity checks, the second coder for qualitative analyses read and recommended revisions to the findings section based on their understanding of the data. In addition, I met with and had each teacher candidate review sections of the findings chapter focused on them to confirm or revise my interpretations. All teacher candidates felt they were accurately represented and did not request any substantive revisions of the findings.