Article detail · 2023
A Multi-level Fusion System for Intelligent Capture and Assessment of Student Activity in Physical Training based on Machine Learning
Journal
American Scientific Publishing GroupISSN 2769-786X
The ISSN points to another catalog journal; the name is from the YÖKSİS record.
- Year
- 2023
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue American Scientific Publishing Group
- Catalog match (ISSN) Journal of Intelligent Systems and Internet of Things (discontinued)
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
To record and evaluate students' physical education class participation, this study proposes using a Machine Learning aided Physical Training Framework (ML-PTF). Improve student achievement in physical education with the help of the Multi-level Fusion System that employs machine learning strategies. The system integrates sensor data, video data, and contextual data to deliver a holistic and precise evaluation of student engagement. This study's simulation analysis shows that the ML-PTF improves the reliability of evaluating universities' physical education programs. A important reference path and paradigm for advancing tertiary-level physical education for graduates, the multi-level fusion system also provides an investigation of information technology and language education integration. The experimental findings demonstrate that the ML-PTF is superior to other approaches in terms of learning rate, f1-score, precision, and probability, as well as student engagement, involvement, and recognition accuracy.
Topics
Citations
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1 citations
OpenAlex cited_by_count (cache / database)