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Exploring opportunities and challenges toward ChatGPT for inclusion in sport education

Shu-Hao Chang et al.

Journal of Hospitality, Leisure, Sport & Tourism Education2025https://doi.org/10.1016/j.jhlste.2025.100572article
AJG 1ABDC B
Weight
0.44

Abstract

This study explores how university students perceive Generative AI (i.e., ChatGPT) potential to foster or hinder inclusion in sport education. Using an extended Technology Acceptance Model, the study examined factors such as perceived usefulness, ease of use, trust, novelty, and concerns. Survey data from 266 students revealed that trust and frequency of use predicted perceived opportunities for inclusion, while concerns and gender predicted perceived challenges. Two domain-specific constructs—opportunities for inclusion and challenges for inclusion in sport education—were developed and validated to capture this duality. Findings highlight the need for trust-building, inclusive practices, and gender-sensitive strategies in AI-supported education. • Trust in ChatGPT predicts perceived opportunities for inclusive sport education. • Frequent ChatGPT use is associated with greater optimism and fewer perceived inclusion challenges. • Female students report significantly higher concerns about ChatGPT's cultural sensitivity and ethical risks. • Targeted AI training can build trust, reduce apprehension, and support diverse learner needs. • Inclusive adoption of ChatGPT requires attention to trust, usability, and demographic-specific concerns.

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https://doi.org/https://doi.org/10.1016/j.jhlste.2025.100572

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@article{shu-hao2025,
  title        = {{Exploring opportunities and challenges toward ChatGPT for inclusion in sport education}},
  author       = {Shu-Hao Chang et al.},
  journal      = {Journal of Hospitality, Leisure, Sport & Tourism Education},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1016/j.jhlste.2025.100572},
}

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Exploring opportunities and challenges toward ChatGPT for inclusion in sport education

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Evidence weight

0.44

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.