Article: AI-driven recommendation for personalised physical education training Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.6 pp.27 - 44 Abstract: The objective of this study is to explore how personalised AI-based physical education (PE) tools can enhance learning outcomes and physical fitness among college students. The research investigates the potential of AI to make PE more adaptive and data-driven through innovative motion-sensing and analytics-based game applications. Seventy-two students were divided into twelve groups, with half using AI-enhanced mobile apps that provided real-time feedback and guidance. Over eight weeks, the AI-enhanced group demonstrated significant improvements in core, upper-body, and lower-body strength (p < 0.01). The AI systems adapt continuously, offering immediate corrective feedback to improve performance. These results suggest that AI can effectively personalise physical training, promote independent exercise, and increase engagement in physical activity, contributing to sustainable fitness development. Inderscience Publishers - linking academia, business and industry through research

Title: AI-driven recommendation for personalised physical education training

Authors: Ermao Xu

Addresses: School of Physical Education, Changzhou University, Changzhou, Jiangsu, 213164, China

Abstract: The objective of this study is to explore how personalised AI-based physical education (PE) tools can enhance learning outcomes and physical fitness among college students. The research investigates the potential of AI to make PE more adaptive and data-driven through innovative motion-sensing and analytics-based game applications. Seventy-two students were divided into twelve groups, with half using AI-enhanced mobile apps that provided real-time feedback and guidance. Over eight weeks, the AI-enhanced group demonstrated significant improvements in core, upper-body, and lower-body strength (p < 0.01). The AI systems adapt continuously, offering immediate corrective feedback to improve performance. These results suggest that AI can effectively personalise physical training, promote independent exercise, and increase engagement in physical activity, contributing to sustainable fitness development.

Keywords: artificial intelligence; personalised physical education; recommendation system; motion analysis; fitness training; data-driven learning.

DOI: 10.1504/IJICT.2026.151556

International Journal of Information and Communication Technology, 2026 Vol.27 No.6, pp.27 - 44

Received: 10 Oct 2025
Accepted: 11 Nov 2025
Published online: 06 Feb 2026 *

Title: AI-driven recommendation for personalised physical education training

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