Bridging technology and pedagogy: a cross-sectional analysis of AI use, self-reported academic effects, and ethical concerns among students across diverse health science curricula
Abstract Background Artificial Intelligence has emerged as a transformative force in health professions education, yet its impact on academic success and students' ethical concerns remains underexplored. This study evaluates AI utilization patterns and their perceived effects on learning outcomes among health science students. Methods Using a stratified two-stage cluster sampling design, data were collected from 310 students across various health-related programs via interviewer-administered questionnaires. Results Participants reported moderate familiarity with AI (mean knowledge score 3.08 ± 1.06). While 90% (n = 279) of students used ChatGPT, a significant training gap persists: 82.6% of respondents received no formal instruction on AI. AI usage frequency was significantly associated with higher GPAs (ANOVA, F = 15.56). Ethical concerns were prevalent (61%), with significant variance by gender (p = 0.0015) and academic program (p = 0.0114). Conclusion AI tools significantly enhance perceived study efficiency and comprehension of complex topics. However, disparities in formal training and significant ethical concerns necessitate the integration of a structured curriculum. Implications for Practice: Faculty should implement "proactive" AI training that addresses automation bias and ethical literacy to ensure equitable technological competency across healthcare disciplines.
Authors
- Ibrahim Awad Eljack Ibrahim (ORCID: https://orcid.org/0000-0002-5010-6001)
- Abubakar Mohammed Jibo (ORCID: https://orcid.org/0000-0003-4654-6669)
- Dalal Mohammed Alhuian (ORCID: https://orcid.org/0009-0007-2444-3008)
- Abdullah M. Alshahrani (ORCID: https://orcid.org/0000-0002-9188-4088)
- Ghada Ayed Mohammed Alqarni (ORCID: https://orcid.org/0009-0003-9598-1146)
- Ayidh Faleh Alshahrani
- Khalid Hassan S Alshahrani
- M. A. S. Alghamdi (ORCID: https://orcid.org/0009-0008-9476-0882)
- S. H. Alharthi (ORCID: https://orcid.org/0009-0004-4424-627X)
- A. M. Almarhabi (ORCID: https://orcid.org/0009-0002-7093-8398)
- M. T. M. Almuawi (ORCID: https://orcid.org/0009-0001-4219-8313)
- K. H. S. Alshahrani (ORCID: https://orcid.org/0009-0002-8633-7132)
Institutions
- University of Bisha (SA)
Publication Details
- Journal
- BMC Medical Education
- Published
- 2026-11-03
- DOI
- https://doi.org/10.1186/s12909-026-10645-5
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- University of Bisha