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Reflections on and Framework for AI-Enabled Evaluation in Physical Education

Author(s)

Chuyang Wu, Aoen Wen*

Affiliation(s)

Guangzhou College of Applied Science and Technology, Zhaoqing, Guangdong, China *Corresponding Author

Abstract

Amidst the ongoing digital transformation and the imperative for high-quality education, artificial intelligence (AI) technology presents unprecedented opportunities to overcome the inherent limitations of traditional physical education evaluation. This study employs a systematic review and logical analysis to examine the significance, current challenges, and strategic responses associated with AI integration in physical education evaluation. It argues that AI enables a fundamental shift from static, one-dimensional, and outcome-focused evaluations to dynamic, multi-faceted, and development-oriented approaches. This transition enhances evaluation accuracy, facilitates personalized feedback, optimizes instructional decision-making, and promotes collaborative engagement among diverse stakeholders. However, practical application reveals several challenges: technologically, issues such as fragmented data silos, opaque algorithms, and insufficient adaptability to complex educational environments persist; within the educational domain, risks include overreliance on technology, diminishing educator expertise, and the erosion of the evaluative process's humanistic qualities; ethically and governance-wise, concerns center on privacy and security risks, algorithmic bias, and the lack of robust accountability mechanisms. To address these challenges, the study proposes an integrated pathway that synergizes technology, education, and ethics by advancing data standardization and explainable AI, establishing a human-AI collaborative evaluation model, and strengthening data security alongside algorithmic governance. This framework aims to cultivate a scientific, equitable, and human-centered evaluation system for physical education.

Keywords

Artificial Intelligence; Physical Education; Human-AI Collaboration; Paradigm Shift

References

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