Grounded theory methods were used to analyze transcribed interviews over time (2019-2022) due to the Covid-19 shutdown. As utilized by grounded theory methodologists, we applied an iterative approach to our qualitative study design, moving back and forth between collecting and analyzing the data (Charmaz, 2014; Thornberg et al., 2013). This dataset includes the coded quotes from the interviews, organized by the three primary themes: I. Teachers and Teaching; II. Improving Opportunities to Learn for School-based STEM Education; and Theme III: Realizing Equity in School-based STEM Education.
After transcribing the audio-recorded interviews, we completed data analyses of the transcripts over five phases.
- Phase 1: For the first set of interviews, we carried out line-by-line coding grounded in the data (Saldaña, 2017). This resulted in codes that were discussed/agreed upon across the research team;
- Phase 2: After all interviews were completed, the research team met via Zoom to synchronously code 3-4 transcripts before completing the remaining transcripts independently. Constant comparison of those codes, memo writing, and memo sorting led to our first set of themes: STEM is viewed as important for a) providing future opportunities and b) understanding daily life, c) the instructional approaches used to teach STEM are important, and d) teachers matter).
- Phase 3: Additional interviews conducted over the next year were transcribed and open coded by the research team following the same procedures in phases one and two. We then merged the initial and additional interview data codes, with team members checking each other’s codes and reaching consensus agreement for all codes across coded transcripts. Using constant comparison methods (Charmaz, 2014), we proceeded to construct focused codes and families from the merged dataset, resulting in seven themes: a) Teachers and teaching, b) What constitutes STEM and STEM experiences, c) Relevance to real life –in and out of school disconnects, d) STEM courses lead to greater opportunities/college preparation, e) Equity and equal opportunity for all – Student agency for course selection, f) Extrinsic motivation, and g) Intrinsic motivation.
- Phase 4: Two of the research team then reviewed the coded transcripts a third time, comparing data with codes and across codes (phase four), leading to fewer but more focused and comprehensive codes (Thornberg et al., 2013) with five overarching themes: I) Teachers/teaching, II) STEM learning experiences, III) Relevance to real life – In and out of school disconnects, IV) STEM courses lead to greater opportunities, and V) Equity and equal opportunities for all – Student agency.
- Phase 5: For this final phase of analysis, three of the research team reviewed the overall coded transcripts again, discussing and merging codes to finalize and come to agreement on categories and codes for three themes: I) Teachers/Teaching, II) Improving Opportunities to Learn for School-based STEM Education, III) Realizing Equity in School-based STEM Education.
The research team discussed and resolved all differences before moving from one phase of analysis to the next, resulting in an inter-rater reliability rate of 100%.