A Multi-level Fusion System for Intelligent Capture and Assessment of Student Activity in Physical Training based on Machine Learning
Yazarlar (6)
Mustafa Altaee
Al-Farahidi University, Irak
Al-Farahidi University, Irak
A. Jawad
National University Of Science And Technology, Irak
National University Of Science And Technology, Irak
Mohammed Abdul Jalil
Al-Turath University, Irak
Al-Turath University, Irak
Sanaa Al-Kikani
Al-Mustaqbal University, Irak
Al-Mustaqbal University, Irak
Ahmed Oleiwi
University Of Warith Al-Anbiyaa, Irak
University Of Warith Al-Anbiyaa, Irak
Doç. Dr. Hatıra GÜNERHAN Kafkas Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SCOPUS dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Journal of Intelligent Systems and Internet of Things | ||
| Dergi ISSN | 2769-786X Scopus Dergi | ||
| Dergi Tarandığı Indeksler | Scopus | ||
| Makale Dili | Türkçe | Basım Tarihi | 01-2023 |
| Cilt / Sayı / Sayfa | 9 / 1 / 8–23 | DOI | 10.54216/JISIoT.090101 |
| Makale Linki | https://doi.org/10.54216/JISIoT.090101 | ||
| Özet |
| To record and evaluate students’ physical education (PE) class participation, this study proposes using machine learning aided physical training framework (ML-PTF). Improve student achievement in PE 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’ PE programs. A important reference path and paradigm for advancing tertiary-level PE 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 … |
| Anahtar Kelimeler |
| A Multi-level Fusion System | Assessment model | Physical Education, Machine learning | Student Activity Prediction |
BM Sürdürülebilir Kalkınma Amaçları
| Atıf Sayıları | |
| SCOPUS | 2 |
| Google Scholar | 3 |