The need to expand computer science learning for all students has led to an increase in professional development (PD) opportunities for teachers. The Covid-19 pandemic, however, necessitated changes in well-established PD programs and a shift to
virtual delivery. In this work, we describe our transition to a virtual PD institute, including the topics and design principles
guiding the institute. We also examine how participation in the virtual PD institute infuenced teacher outcomes. Data were
collected from two cohorts of teachers. Data sources included surveys (N=30), lesson plans (N=22), and interviews (N=17)
from a purposeful sample of participants. Findings gleaned from quantitative and qualitative analysis suggest an increase
in teachers’ knowledge and self-efcacy while highlighting the afordances of virtual PD most valued by teachers. Findings
have implications for research and practice.
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Investigating relationships of sentiments, emotions, and performance in professional development K-12 CS teachers
Background and Context: Professional development (PD) programs for K-12 computer science teachers use surveys to measure teachers’ knowledge and attitudes while recognizing daily sentiment and emotion changes can be crucial for providing timely teacher support. Objective: We investigate approaches to compute sentiment and emotion scores automatically and identify associations between the scores and teachers’ performance. Method: We compute the scores from teachers’ assignments using a machine-assisted tool and measure score changes with standard deviation and linear regression slopes. Further, we compare the scores to teachers’ performance and post-PD qualitative survey results. Findings: We find significant associations between teachers’ sentiment and emotion scores and their performance across demographics. Additionally, we find significant associations that are not captured by post-PD qualitative surveys. Implications: The sentiment and emotion scores can viably reflect teachers’ performance and enrich our understanding of teachers’ learning behaviors. Further, the sentiment and emotion scores can complement conventional surveys with additional insights related to teachers’ learning performance.
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- Award ID(s):
- 1837476
- PAR ID:
- 10545539
- Publisher / Repository:
- Taylor & Francis
- Date Published:
- Journal Name:
- Computer Science Education
- ISSN:
- 0899-3408
- Page Range / eLocation ID:
- 1-32
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1080/08993408.2023.2298162
