Classroom teacher behavior analysis: The TBU dataset and performance evaluation

Abstract

Classroom videos are objective records of teaching behaviors, which provide evidence for teachers’ teaching reflection and evaluation. The intelligent identification, tracking and description of teacher teaching behavior based on classroom videos have become a research hotspot in the field of intelligent education to understand the teaching process of teachers. Although the recent attempts propose several promising directions for the analysis of teaching behavior, the existing public datasets are still insufficient to meet the need for these potential solutions due to lack of varied classroom environment, fine-grained teaching scene behavior data. To address this, we analyzed the influencing factors of teacher behavior and related video datasets, and constructed a diverse, scenario-specific, and multi-task dataset named TBU for Teacher Behavior Understanding. The TBU contains 37,026 high-quality teaching behavior clips, 9422 annotated teaching behavior clips with precise time boundaries, and 6098 teacher teaching behavior description clips annotated with multi-level atomic action labels of fine-grained behavior, spatial location, and interactive objects in four education stages. We performed a comprehensive statistical analysis of TBU and summarized the behavioral characteristics of teachers at different educational stages. Additionally, we systematically investigated representative methods for three video understanding tasks on TBU: behavior recognition, behavior detection, and behavior description, providing a benchmark for the research towards a more comprehensive understanding of teaching video data. Considering the specificity of classroom scenarios and the needs of teaching behavior analysis, we put forward new requirements for the existing baseline methods. We believe that TBU can facilitate in-depth research on classroom teacher teaching video analysis. TBU is available at: https://github.com/cai-KU/TBU.