A Multi-Modal Dataset for Teacher Behavior Analysis in Offline Classrooms

MM-TBA is a comprehensive multi-modal dataset designed for analyzing teacher behavior in offline classroom settings. MM-TBA consists of three sub-datasets: the Teacher Teaching Action Detection Sub-Dataset, the Teacher Lecture Evaluation Sub-Dataset, and the Teaching Design Sub-Dataset. The Teacher Teaching Action Detection Sub-Dataset includes visual feature files of teachers' teaching actions and action classification annotation files. The Teacher Lecture Evaluation Sub-Dataset comprises the text of teachers' lectures and corresponding evaluation reports. The Teaching Design Sub-Dataset contains the original teaching designs and their respective annotation files. The aim of introducing MM-TBA is to promote scientific research in teacher behavior and cognitive science, provide new research tools for educational science, and foster the development of intelligent education technology.