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.

MM-TBA是一款专为线下课堂场景中教师行为分析打造的综合多模态数据集（multi-modal dataset）。该数据集包含三个子数据集：教师教学行为检测子数据集（Teacher Teaching Action Detection Sub-Dataset）、教师授课评价子数据集（Teacher Lecture Evaluation Sub-Dataset）以及教学设计子数据集（Teaching Design Sub-Dataset）。教师教学行为检测子数据集包含教师教学行为的视觉特征文件与行为分类标注文件；教师授课评价子数据集涵盖教师授课文本与对应评价报告；教学设计子数据集收录原始教学设计方案及其配套标注文件。本数据集的构建旨在推动教师行为与认知科学领域的科学研究，为教育科学提供全新研究工具，并助力智能教育技术的发展。