Abstract:

The Monash Virtual School (MVS) is an innovative program that offers free online STEM education to K-12 students, with a particular emphasis on reaching disadvantaged and underrepresented young women. While numerous studies have delved into the impact of online STEM opportunities for students (for example, see: Chung & Shamir, 2021; Cox, Margulieux, & Darling-Aduana, 2022), our research takes a distinctive turn. Instead of focusing solely on the students, we shift our attention to the educators of tomorrow, exploring the transformation of their knowledge, skills, values, identities, and epistemologies.

Central to our exploration is the concept of epistemic frames (Shaffer, 2006). These frames are pivotal for the development, delivery, and refinement of interactive, team-taught lessons such as those offered by MVS. To delve deeper into this, we employed Quantitative Ethnography (QE), a groundbreaking integrated methodology that marries both quantitative and qualitative methods. This approach allows for a nuanced exploration of the relationships between learners—in our case, the pre-service teachers—and their contexts. Our primary tool in this endeavour was Epistemic Network Analysis (ENA), which proved deep insights in understanding the capacity-building process of these educators.

Our research journey began with an aim to discern the relative strengths of connections within individual pre-service teachers’ epistemic frames. We then sought to ground these findings by examining the collaborative capacities of pairs of pre-service teachers. Data for our study was collected through individual, semi-structured interviews conducted both before and after teaching experiences. These interviews were then analysed using the ENA webtool, version 1.7.0 (Marquart, et al., 2021).

While our initial analyses provided insights into the statistically significant evolutions in pre-service teachers’ epistemic frames, we felt a deeper exploration was necessary to truly understand the reasons behind these changes. This led us to conduct additional interviews throughout the academic year. These unveiled five pivotal situated learning processes: induction, transferability, interdependence, synchronicity, and negotiability. Each of these processes played a crucial role in explaining the shifts observed in pre-service teachers’ epistemic frames.

Our research critically underscores the limitations of tools like ENA and emphasises the vital need for closing the interpretive loop in QE, while also spotlighting the imperative of equipping future educators and championing integrated research methodologies.

References:
[1] Chung, C. J., & Shamir, L. (2021). Introducing machine learning with scratch and robots as a pilot program for K-12 computer science education. International Journal of Learning and Teaching, 7(3).
[2] Cox, B., Margulieux, L., & Darling-Aduana, J. (2022). Georgia online education option for broadening participation in K-12 computer science. Policy Futures in Education
[3] Marquart, C. L., Hinojosa, C., Swiecki, Z., Eagan, B., & Shaffer, D. W. (2021). Epistemic network analysis (Version 1.7.0) [Software]. Available from http://app.epistemicnetwork.org
[4] Shaffer, D. W. (2006). Epistemic frames for epistemic games. Computers & Education, 46(3), 223-234.

Keywords:

Virtual school, pre-service teachers, Quantitative Ethnography, Epistemic Network Analysis.