A Study on the Normalized Teaching Model Integrating Intelligent Technologies: A Case of University Physical Education Courses

Abstract

This study focuses on the application of digital intelligent technologies in public university physical education (PE) courses, aiming to explore the internal logic through which these technologies enhance instructional quality and promote students’ physical development. By combining theoretical analysis with empirical investigation, the paper examines the integration of technologies such as virtual reality (VR), big data, and artificial intelligence (AI) with sports education. Taking Fujian Normal University’s “1+3+4” full-cycle course model—which includes pre-class online course selection, in-class smart monitoring and VR-assisted instruction, and post-class data-driven reviews—and Peking University’s digitalized teaching resources (e.g., hybrid teaching models and academic research databases) as representative cases, this study identifies the practical pathways through which technology can innovate instructional models, optimize educational resources, and stimulate student engagement. The findings indicate that intelligent technologies significantly contribute to immersive learning environments (e.g., VR-based sports simulations), precise motion analytics (e.g., real-time heart rate and movement tracking via wearable devices), and personalized instruction. Specifically, the integration of these technologies has led to a 28% increase in student skill assessment pass rates, a 40% rise in independent exercise frequency, and a 50% improvement in exercise outcomes. Additionally, gamified teaching approaches have boosted classroom participation by 35%. However, challenges remain, including high costs of smart device procurement and maintenance (a single VR set costing around 20,000 RMB) and risks of data privacy breaches (e.g., a reported leak of movement data from 2,000 students at one university). To address these issues, the study proposes targeted countermeasures: implementing regular “Technology Application Workshops” (requiring instructors to complete 20 training hours annually), introducing elective courses such as “Introduction to Digital PE” to enhance digital literacy, employing AES encryption and multi-level access controls (instructors can only access data for their own classes), and establishing a “Sports Data Security Management Protocol” with clear accountability mechanisms. Future research should focus on AI-based sports injury prediction, the integration of VR and IoT in building “metaverse PE classrooms,” and the design of personalized learning schemes based on EEG monitoring. It also recommends advancing interdisciplinary collaboration across sports science, computer science, and psychology; developing low-cost smart tools (e.g., mobile apps replacing professional devices) to ensure educational equity; and promoting environmentally sustainable smart equipment to support long-term development. The study concludes that digital intelligent technologies have become a key driver in reforming public university PE instruction. Their deep integration with educational practices offers a new paradigm for building an efficient, equitable, and sustainable sports education ecosystem, contributing significantly to the cultivation of high-quality talent under the “Healthy China” national strategy.