Feature Extraction with SHAP Value Analysis for Student Performance Evaluation in Remote Collaboration

Abstract

In recent years, group discussions are becoming an important part of corporate recruitment examinations in Japan. Developing a remote teaching support system for group discussion will help reduce the burden of teachers. As a part of our project, this study aims to support teachers who need effective teaching method in remote group discussions by analyzing the video images. In this study, we used the features obtained from the videos. Students performances in group discussion were assessed automatically by classification, and important features were selected for teaching from the SHapley Additive exPlanations(SHAP) values.