Student voices
Synergising artificial and human intelligence in health science education
Bibliographic Data
| ID | 22423932 |
|---|---|
| Authors | Zijing Hu (0009-0000-4367-4580), Caixia Qiu (0000-0002-9301-2814, Fujian University of Traditional Chinese Medicine), Anqi Wang (0000-0002-8301-6248, Fujian University of Traditional Chinese Medicine), Shungui Xu (0000-0001-9144-8369, Fujian University of Traditional Chinese Medicine, corresponding author), Jing Ye (0000-0002-3971-2780, Fujian University of Traditional Chinese Medicine), Jiawen Zou (Fujian University of Traditional Chinese Medicine), Shuting Liu (0000-0002-7178-2703, Fujian University of Traditional Chinese Medicine), Weixiang Yuan (Maharat Nakhon Ratchasima Hospital), Jiazhe Lv (Fuzhou University) |
| Year | 2026 |
| Volume | 26 |
| Issue | 1 |
| Pages | 185-185 |
| Publication date | 2026-01-05 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | BMC Medical Education (JOURNAL) |
| Journal identifiers | ISSN: 1472-6920 • E-ISSN: 1472-6920 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1186/s12909-025-08545-1 |
| PMID | 41491181 |
| OpenAlex | W7118196899 |
| Language | EN |
| References cited | 41 |
BACKGROUND: There is a dire need to enhance health science education through technology to meet the demands of 21st-century education globally. This study explored the integration of Artificial Intelligence (AI) and Human Intelligence (HI) in health science education. METHODS: Guided by the Technological, Pedagogical, and Content Knowledge and Diffusion of Innovation frameworks, a descriptive qualitative single-case study was conducted within an interpretivist paradigm. Purposive sampling recruited six postgraduate and residency students with dual exposure to conventional and AI-assisted learning. Semi-structured interviews were thematically analysed. RESULTS: Findings revealed that students perceived AI as a valuable supplementary tool that enhanced diagnostic confidence, accelerated knowledge access, and simulated rare clinical scenarios. AI facilitated self-directed learning, structured clinical reasoning, and supported overburdened educators. However, participants cautioned against over-reliance, citing risks such as reduced critical thinking, algorithmic bias, and potential erosion of humanistic care. The adoption of AI was influenced by its relative advantages, alignment with learning preferences, and the possibility of low-risk experimentation; however, challenges arose from the complexity of prompt design and the lack of formal training. CONCLUSION: The study concluded that effective AI-HI integration requires AI literacy, ethical governance, and hybrid models combining technological efficiency with mentorship. Institutional investment in curricula, faculty development, and policy frameworks is essential to ensure responsible, context-sensitive adoption.
Health science · Human capital · Human health · Human intelligence · MEDLINE · Science education · Artificial Intelligence in Healthcare and Education · Biomedical and Engineering Education · Educational Leadership and Innovation
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The investigation of EFL teachers' cognitive emotion regulation, pedagogical beliefs, pedagogical practices, and their engagement across the curriculum
| Highly cited | No |
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