Teacher professional development (PD) is a key factor in enabling teachers to develop mindsets and skills that positively impact students. It is also a key step in building capacity for computer science (CS) education in K-12 schools. Successful CS PD meets primary learning goals and enable teachers to grow their self-efficacy, asset and equity mindset, and interest in teaching CS. As part of a larger study, we conducted a secondary analysis of CS PD evaluation instruments (). We found that instruments across providers were highly dissimilar with limited data collected for measures related to teacher learning, which has implications for future K-12 CS education. Likewise, the instruments were limited in being connected to student learning and academic growth. As a way to enable PD providers to construct measures that align with known impacting factors, we offer recommendations for collecting demographic data and measuring program satisfaction, content knowledge, pedagogical content knowledge, growth and equity mindset, and self-efficacy. We also highlight questions for PD providers to consider when constructing their evaluation, including reflecting community values, the goals of the PD, and how the data collected will be used to continually improve CS programs.
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What keeps teachers engaged during professional development? The role of interest development.
Interest influences adults’ and young learners’ learning in formal and informal contexts. Although interest and interest development frameworks have been used in research on student-learning, they are not used in teacher-focused research, especially as “outcomes” of teacher professional development (PD) activities. In this study, we used interest development as the outcome of PD in computer science (CS) and investigated the factors that influenced teachers’ (n = 5) interest development toward CS using various data sources and analysis methods. We found that interest development is (a) varied, (b) influenced by self-relation, knowledge, and affect, (c) associated with reengagement with PD activities, and (d) it can be captured using computational text analysis methods and online log data.
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- Award ID(s):
- 2027948
- PAR ID:
- 10437000
- Editor(s):
- Giersch, Jason
- Date Published:
- Journal Name:
- Education sciences
- Volume:
- 13
- Issue:
- 2
- ISSN:
- 2227-7102
- Page Range / eLocation ID:
- 188
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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