AI adaptive learning systems and multidimensional engagement in online Physical Education: large effects
DOI:
https://doi.org/10.47197/retos.v80.119205Keywords:
AI adaptive learning system, online physical education, learning engagement, learning experience, mediation effectAbstract
Introduction: Online physical education has expanded greatly since the COVID-19 pandemic, but it struggles to sustain steady student learning engagement. Artificial intelligence adaptive learning systems offer a promising fix, yet empirical research on their effects in physical education remains insufficient.
Objective: This study aimed to examine how artificial intelligence adaptive learning systems impact student engagement in online physical education and test the mediating role of learning experience.
Methodology: A quasi-experimental design was used with 203 students from Jiangsu Province. A 16-week quasi-experimental cycle was conducted, comprising a 4-week pre-test, 10-week intervention, and 2-week post-test, with data collected through questionnaires, platform analytics, and semi-structured interviews.
Results: Artificial intelligence adaptive learning systems significantly boosted overall learning engagement and its three dimensions. Learning experience partially mediated the relationship, accounting for 54.9% of the total effect, and qualitative data supported these outcomes.
Discussion: The findings aligned with studies in traditional academic subjects and filled the gap of quantitative research in online physical education.
Conclusions: Artificial intelligence adaptive learning systems effectively improve student engagement in online physical education, with learning experience as a critical mediator, providing evidence for the intelligent transformation of online physical education.
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