Analyzing Talk Patterns in Video-based Automatic Multimodal Analysis (VAMA)-Supported Collaborative Reflection: How Talk Features Enhance Reflection Depth

Collaborative reflection among teachers has gained significant attention in educational research. With the advancement of technology, various technological tools are being integrated into the process of teacher reflection, including Video-based Automatic Multimodal Analysis (VAMA). Despite the growing adoption of VAMA, there is a scarcity of research focusing on its impact on the depth of reflection and the patterns through which it operates.This study employs VAMA to facilitate collaborative reflection among four groups of pre-service teachers, capturing procedural discourse data and analyzing it through content coding. The findings reveal that the depth of reflection facilitated by VAMA varies across different groups, with distinct discourse characteristics observed between high-performing and low-performing groups.