ClassInSight: Designing Conversation Support Tools to Visualize Classroom Discussion for Personalized Teacher Professional Development
Proceedings of the CHI Conference on Human Factors in Computing Systems(2024)
摘要
Teaching is one of many professions for which personalized feedback and
reflection can help improve dialogue and discussion between the professional
and those they serve. However, professional development (PD) is often
impersonal as human observation is labor-intensive. Data-driven PD tools in
teaching are of growing interest, but open questions about how professionals
engage with their data in practice remain. In this paper, we present
ClassInSight, a tool that visualizes three levels of teachers' discussion data
and structures reflection. Through 22 reflection sessions and interviews with 5
high school science teachers, we found themes related to dissonance,
contextualization, and sustainability in how teachers engaged with their data
in the tool and in how their professional vision, the use of professional
expertise to interpret events, shifted over time. We discuss guidelines for
these conversational support tools to support personalized PD in professions
beyond teaching where conversation and interaction are important.
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