ClassInSight: Designing Conversation Support Tools to Visualize Classroom Discussion for Personalized Teacher Professional Development

要旨

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.

著者
Tricia J.. Ngoon
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
S Sushil
University of California San Diego, La Jolla, California, United States
Angela E.B.. Stewart
University of Pittsburgh, Pittsburgh, Pennsylvania, United States
Ung-Sang Lee
University of Nevada Las Vegas, Las Vegas, Nevada, United States
Saranya Venkatraman
Pennsylvania State University, State College, Pennsylvania, United States
Neil Thawani
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Prasenjit Mitra
The Pennsylvania State University, University Park, Pennsylvania, United States
Sherice Clarke
University of California San Diego, San Diego, California, United States
John Zimmerman
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Amy Ogan
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
論文URL

doi.org/10.1145/3613904.3642487

動画

会議: CHI 2024

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2024.acm.org/)

セッション: Learning and Teaching Technologies B

319
5 件の発表
2024-05-15 18:00:00
2024-05-15 19:20:00