What Teachers Discuss and How They Perceive and Feel: Topic Modeling and Sentiment Analysis of a Generative Artificial Intelligence Learning Group on Facebook

• In Event: Teacher Practices and Professional Development with AI

Abstract

Rapid GenAI advancements promise to reshape teaching, daily tasks, and student outcomes. However, prior studies rely mostly on interviews, surveys, or tool-specific experiments, lacking large-scale analysis of teachers’ concerns. This study used topic modeling and sentiment analysis on 96,693 posts from the largest GenAI teacher group on Facebook, identifying four key topics: 1) GenAI for teaching/administrative work, 2) student development, 3) usage and assessment tips, and 4) ethics and policies. Sentiment was generally positive for topics 1 and 3, neutral for 2 and 4. Combined with qualitative analysis, four teacher perspectives emerged, highlighting GenAI’s role in transforming teaching, influencing student skills, requiring new pedagogies, and prompting ethical and policy considerations—offering insights for research and policy.

Authors

• Zicong Song, The University of Hong Kong

• Chun Lai, The University of Hong Kong

• Xianhan Huang, The Education University of Hong Kong

• Chin-Hsi Lin, University of Hong Kong

• Zhong Sun, Capital Normal University