The impact of artificial intelligence-assisted teaching on medical students’ learning outcomes: an integrated model based on the ARCS model and constructivist theory
Teaching quality and external environment indirectly enhance medical learning outcomes by strengthening learning motivation. Learning motivation plays a key role in shaping learning attitude, satisfaction, and outcomes, confirming the positive value of AI-assisted teaching in optimizing learning mechanisms. This study contributes to the application of AI-assisted teaching in medical education and provides empirical support for improving medical students' learning performance.
Authors
- J. H. Zou (ORCID: https://orcid.org/0009-0001-2680-5267)
- Yuanyuan Zhang (ORCID: https://orcid.org/0000-0001-6258-0176)
- Xinyu Pang (ORCID: https://orcid.org/0000-0003-2444-4557)
- Xiyi Chen (ORCID: https://orcid.org/0000-0001-7855-1177)
- Hao Zhang (ORCID: https://orcid.org/0000-0002-4582-2556)
- Yingying Li (ORCID: https://orcid.org/0000-0002-2096-8313)
- Xiaopeng Zhang (ORCID: https://orcid.org/0000-0003-1195-9359)
- Fu‐Dong Wang (ORCID: https://orcid.org/0000-0001-7969-9501)
Institutions
- Dalian Medical University (CN)
- Second Affiliated Hospital of Dalian Medical University (CN)
Publication Details
- Journal
- BMC Medical Education
- Published
- 2025-10-02
- DOI
- https://doi.org/10.1186/s12909-025-07826-z
- Citations
- 4
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 2.62