Research on the Design of Performance Evaluation System for Physical Education Major Based on Multimedia Information Processing Technology

Abstract

The Massive Open Online Course (MOOC) platform, despite its reach and potential, faces significant challenges related to learner diversity, including variations in student backgrounds, work experiences, and learning environments. By integrating the principles of ant colony clustering algorithms with MOOC platform dynamics, our study devises a strategy for grouping students based on shared characteristics, thereby fostering a tailored learning environment. A streamlined MOOC platform design framework is outlined, accompanied by a detailed blueprint for a peer-evaluation information system, aimed at accurately gauging students' academic progress within their disciplines. This platform enables students to effortlessly access and engage with courses aligned with their interests, while the reciprocal assessment mechanism heightens understanding of course materials and alleviates pressure on educators. Our research contributes a pragmatic solution to the challenge of student assignment clustering within MOOCs, enhancing both individual learning outcomes and the broader instructional quality.