# A dual-path framework for enhancing student engagement and learning outcomes in sports education: Integrating technology acceptance, self-regulation, and self-efficacy

**Authors:** Guifeng Zheng, Yanting Wang, Juan Du

PMC · DOI: 10.1371/journal.pone.0345809 · PLOS One · 2026-03-25

## TL;DR

This paper explores how mobile technology can improve student engagement and learning in sports education by combining theories of technology acceptance and self-regulation.

## Contribution

The study introduces a new dual-path framework integrating TAM, self-regulated learning, and self-efficacy in hybrid physical education.

## Key findings

- Students' perceived usefulness of mobile apps positively affects their behavioral intentions and self-regulated learning.
- Technology acceptance indirectly enhances learning self-efficacy in hybrid education settings.
- The framework offers practical insights for optimizing technology integration in higher education sports.

## Abstract

The rapid adoption of mobile learning technologies in education has presented new opportunities and challenges for the innovative transformation of physical education. This study expands the Technology Acceptance Model (TAM) to systematically analyze how mobile applications influence learning behaviors in higher education physical education. Specifically, it explores the role of mobile technology in hybrid physical education environments by integrating the theoretical dimensions of self-regulated learning, learning self-efficacy, and technology acceptance. Findings reveal that students’ perceptions of usefulness and attitudes toward usage significantly and positively impact their behavioral intentions and self-regulated learning abilities, while also indirectly enhancing learning self-efficacy. This theoretical extension not only provides valuable insights into the mechanisms driving technology-based educational innovation but also introduces a new analytical framework for hybrid physical education. The findings have important practical implications for technology integration and learning behavior optimization in higher education.

## Full-text entities

- **Genes:** ATM (ATM serine/threonine kinase) [NCBI Gene 472] {aka AT1, ATA, ATC, ATD, ATDC, ATE}, APP (amyloid beta precursor protein) [NCBI Gene 351] {aka AAA, ABETA, ABPP, AD1, APPI, CTFgamma}, SRL (sarcalumenin) [NCBI Gene 6345] {aka SAR}
- **Diseases:** COVID-19 (MESH:D000086382), sports injury (MESH:D001265), TAM (MESH:C000719218)
- **Chemicals:** LSE (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

51 references — full list in the complete paper: https://tomesphere.com/paper/PMC13016278/full.md

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Source: https://tomesphere.com/paper/PMC13016278