Factor and cluster analysis of virtual simulation physics experiment

Yimeng Wang; Yuying Li; Jia Guan; Kai Fang; Chen Ni

doi:10.1117/12.3026434

15 March 2024 Factor and cluster analysis of virtual simulation physics experiment

Yimeng Wang, Yuying Li, Jia Guan, Kai Fang, Chen Ni

Proceedings Volume 13075, Second International Conference on Physics, Photonics, and Optical Engineering (ICPPOE 2023); 1307507 (2024) https://doi.org/10.1117/12.3026434
Event: Second International Conference on Physics, Photonics, and Optical Engineering (ICPPOE 2023), 2023, Kunming, China

Abstract

This study utilizes learning analytics techniques, specifically factor analysis and clustering, to explore the commonalities and characteristics among different virtual simulation physics experiments. Additionally, it investigates the behavioral patterns of students in online experiments. The findings demonstrate that the integration of big data and learning analytics in education has revolutionized traditional teaching methods. By analyzing student data from experiments, educators can make more timely and effective adjustments to their teaching decisions, as well as implement scientific and efficient interventions to enhance students' learning experiences. Ultimately, this approach facilitates personalized teaching goals attainment.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yimeng Wang, Yuying Li, Jia Guan, Kai Fang, and Chen Ni "Factor and cluster analysis of virtual simulation physics experiment", Proc. SPIE 13075, Second International Conference on Physics, Photonics, and Optical Engineering (ICPPOE 2023), 1307507 (15 March 2024); https://doi.org/10.1117/12.3026434

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