Health students at one Saudi university say AI helps them study, but 83% got no AI training
Study title: 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
A cross-sectional survey of 310 students in health programs at the University of Bisha in Saudi Arabia found near-universal use of AI: 90% (279 students) used ChatGPT for academic purposes. Students rated AI as improving study efficiency (3.70 out of 5), understanding of complex topics (3.90) and retention of information (3.55), and 54.2% said it improved their grades.
Read the study abstract
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. Resu…

Both sides are scored from claims and sources, not community votes.
G 57The G score combines the specificity and measured human impact of the grounded gain claim with the strength of this Trace’s cited sources.In brief
The adoption has outpaced preparation. 82.6% of respondents had received no formal AI training, and only small shares had taken online courses (8.1%), electives (7.4%), seminars (5.2%) or required courses (3.2%). Meanwhile 61% expressed ethical concern, mainly about privacy and data security, and 88.7% supported structured AI training in medical education.
The findings rest on self-reports from one institution, so they show perceived benefit rather than measured learning gains. Students rated AI's overall effect on academic performance as only moderate (3.10 out of 5). The authors warn that without instruction students may fall prey to automation bias and call for longitudinal work on clinical decision-making skills.
Main points
- The sample was 310 students aged 18 to 26, drawn by stratified two-stage cluster sampling; 48.1% were MBBS students and 39.0% were nursing students.
- ChatGPT was used by 90% of students, followed by Grammarly (31.9%) and Gemini (12.6%); students used 1.90 AI tools on average.
- The most common uses were summarizing content (72.9%), clarifying complex concepts (71.6%) and practice exam questions (70.3%).
- Students reported better time management (58.7%), improved grades (54.2%) and enhanced knowledge acquisition (53.2%); none reported no effect.
- Higher-GPA students used AI tools significantly more often (ANOVA F = 15.56, p < 0.001), an association rather than proof of cause.
- Ethical concern scores differed by gender (female 3.50 versus male 2.96, p = 0.0015) and by program (MBBS 3.44 versus nursing 2.79, p = 0.0114), but not by age or residence.
- Knowledge scores rose from 3.03 with no training to 4.5 with three types of training, and younger students were more likely to have sought elective or online training (p = 0.0303).
The gain
Health science students at the University of Bisha rated AI as improving their study efficiency (3.70/5) and understanding of complex topics (3.90/5), and 54.2% said it improved their grades.
The problem
Although 90% of 310 surveyed health science students used ChatGPT, 82.6% had received no formal AI instruction and 61% voiced ethical concerns, leaving them exposed to automation bias.
The rundown
Researchers at the University of Bisha used interviewer-administered questionnaires adapted from earlier studies, covering AI knowledge and training, frequency of tool use, and perceived academic impact and ethics, with 5-point Likert scales. Respondents reported moderate AI knowledge, averaging 3.08 out of 5, and 71.7% rated their comfort with AI study tools at 4 or 5.
Usage was heavy: 32.3% used AI frequently and 15.8% always, against 4.2% who never did. About 42.3% judged AI's impact on their academic performance as moderate, 23.2% as high and 9.0% as very high. Students linked higher GPAs with using more AI tools, and regression showed greater tool use predicted higher perceived impact scores.
Training was scarce: 256 students reported none, and 275 (88.7%) supported adding structured AI training to medical education. Younger students and certain programs had more training, and the authors suggest focusing on older students with less access and standardizing training across programs.
Ethical concern centred on privacy and data security in education and healthcare. Female students scored higher than male students, and public health and midwifery students scored higher than nursing students. The authors recommend AI literacy programs covering data privacy, algorithmic bias and professional responsibility, tailored to different programs.
Sources
- Peer-reviewedBMC Medical Education2026-11-03
ace

The debate