ArticleBMC medical education2025
Medical students' attitudes toward AI in education: perception, effectiveness, and its credibility.
Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
61 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Medical Students' Attitudes, Perceptions, and Self-Reported Familiarity With AI in Health Care: Systematic Review and Meta-Analysis.JMIR medical education · 2026Pooled it
- Artificial intelligence-powered virtual standardized patients in teaching history-taking skills to medical students: a randomized controlled trial.BMC medical education · 2026Trial
- The effect of artificial intelligence-based scenarios on the clinical education of rehabilitation students: an anatomy-based randomized controlled study.BMC medical education · 2026Trial
- Artificial intelligence readiness in Pakistan's medical and dental education: training-phase decline, a knowledge-practice paradox, and the role of digital determinants of health.Medical education online · 2026Article
- AI-Empowered Nuclear Medicine Education, Part 3: Practical AI Applications for Learners.Journal of nuclear medicine technology · 2026Article
- AI-Empowered Nuclear Medicine Education, Part 1: Theoretical and Ethical Foundation.Journal of nuclear medicine technology · 2026Article
- Education Research: Integrating AI-Enabled Interactive Case-Based Learning in a Preclinical Neurosciences Course.Neurology. Education · 2026Article
- Article
- Performance of Seven Large Language Models on Anatomy Examination Questions.Clinical anatomy (New York, N.Y.) · 2026Article
- Value Configurations Associated with Artificial Intelligence Literacy Among Medical Students: Findings from NCA and fsQCA.Behavioral sciences (Basel, Switzerland) · 2026Article
- AI Integration in Undergraduate Medical Education: Qualitative Study of Faculty Perspectives in the United Arab Emirates.JMIR medical education · 2026Article
- Current Status of Generative Artificial Intelligence Utilization in Medical Education: A Cross-Sectional Survey of Medical Students and Faculty.JMA journal · 2026Article
- Knowledge, Attitudes, and Practices Related to AI in Learning and Research Among Medical Students in Vietnam: Cross-Sectional Study.JMIR formative research · 2026Article
- From technological optimism to clinical realism: medical students' attitudes toward artificial ıntelligence and ıts career ımplications - a cross-sectional study at a Turkish Medical Faculty.BMC medical education · 2026Article
- Cross-cultural adaptation and psychometric evaluation of the Shinners Artificial Intelligence Perception Scale (SAIP): evidence from Turkish nursing students.BMC nursing · 2026Article
- Reconciling how clinical reasoning is learned in the age of artificial intelligence.NPJ digital medicine · 2026Article
- Knowledge, Attitude, and Perception of Medical Students Toward AI-Based Learning: A Cross-Sectional Study.Public health challenges · 2026Article
- Influence of learning activities and background characteristics on pharmacology exam success in second-year medical students at a French university: the Pharmaquest study.BMC medical education · 2026Article
- Effectiveness and students' perception of tutor-guided AI navigation in undergraduate medical education in Sri Lanka: a quasi-experimental study.BMC medical education · 2026Article
- Are Psychiatry Faculty Prepared to Guide AI Use? A National Survey.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2026Article
1 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe rapid advancement of artificial intelligence (AI) has revolutionized both medical education and healthcare by delivering innovative tools that enhance learning and improve overall outcomes. The study aimed to assess students' perceptions regarding the credibility and effectiveness of AI as a learning tool and to explore the dynamics of integrating AI in medical education. METHODOLOGY: A cross-sectional study was carried out across medical colleges in Pakistan. A 26-question survey was developed using Google Forms from previously validated studies. The survey assessed demographics of participants, basic understanding of AI, AI as a learning tool in medical education and socio-ethical impacts of the use of AI. The data was analyzed using SPSS (v 26.0) to derive descriptive and inferential statistics.
resultA total of 702 medical students aged 18 to 26 years (mean age 20.50 ± 1.6 years) participated in the study. The findings revealed a generally favorable attitude towards AI among medical students (80.3%), with the majority considering it an effective (60.8%) and credible (58.4%) learning tool in medical education. Students agreed that AI learning optimized their study time (60.3%) and provided up-to-date medical information (63.1%). Notably, 65.7% of students found AI more efficient in helping them grasp medical concepts compared to traditional tools like books and lectures, while 66.8% reported receiving more accurate answers to their medical inquiries through AI. The study highlighted that medical students view traditional tools as becoming increasingly outdated (59%), emphasizing the importance of integrating AI into medical education and creating dedicated AI tools (80%) for the medical education.
conclusionThis study demonstrated that AI is an effective and credible tool in medical education, offering personalized learning experiences and improved educational outcomes. AI tools are helping students learn medical concepts by cutting down on study-time, providing accurate answers, and ultimately improving study outcomes. We recommend developing dedicated AI tools for medical education and their formal integration into medical curricula, along with appropriate regulatory oversight to ensure AI can enhance human abilities rather than acting as a replacement for humans.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.