{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T11:17:43Z","timestamp":1774955863328,"version":"3.50.1"},"reference-count":0,"publisher":"International Association of Online Engineering (IAOE)","issue":"06","license":[{"start":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T00:00:00Z","timestamp":1774915200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Interact. Mob. Technol."],"abstract":"<jats:p>With the advancement of mobile technologies, personalized physical education (PE) has emerged as a critical component of intelligent education. However, existing recommendation models commonly suffer from limited adaptability, insufficient multimodal data integration, and poor alignment between learning paths and learners\u2019 real-time states. To address these challenges, this study proposes a three-layer architecture for personalized recommendation and learning path optimization that integrates multi-source perception, dynamic cognition, and real-time optimization. The core innovations of the proposed model include: (1) a lightweight multi-source heterogeneous data fusion module designed for efficient on-device processing; (2) a dynamic tri-state assessment model incorporating skill mastery, fatigue level, and interest level to achieve accurate real-time perception of learners\u2019 states; and (3) a duallayer optimization mechanism based on online learning to enable end\u2013cloud collaborative learning path optimization. This study provides a novel technical paradigm for mobile technology\u2013enabled intelligent physical education, offering significant theoretical contributions and practical application value.<\/jats:p>","DOI":"10.3991\/ijim.v20i06.60861","type":"journal-article","created":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T10:34:42Z","timestamp":1774953282000},"source":"Crossref","is-referenced-by-count":0,"title":["A Mobile-Based Personalized Physical Education Recommendation and Learning Path Optimization Model"],"prefix":"10.3991","volume":"20","author":[{"given":"Jianxin","family":"Zhao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Zhu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"2371","published-online":{"date-parts":[[2026,3,31]]},"container-title":["International Journal of Interactive Mobile Technologies (iJIM)"],"original-title":[],"link":[{"URL":"https:\/\/online-journals.org\/index.php\/i-jim\/article\/download\/60861\/17139","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/online-journals.org\/index.php\/i-jim\/article\/download\/60861\/17139","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T10:34:42Z","timestamp":1774953282000},"score":1,"resource":{"primary":{"URL":"https:\/\/online-journals.org\/index.php\/i-jim\/article\/view\/60861"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,31]]},"references-count":0,"journal-issue":{"issue":"06","published-online":{"date-parts":[[2026,3,31]]}},"URL":"https:\/\/doi.org\/10.3991\/ijim.v20i06.60861","relation":{},"ISSN":["1865-7923"],"issn-type":[{"value":"1865-7923","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,31]]}}}