Effectiveness of generative artificial intelligence-based teaching versus traditional teaching methods in medical education: a meta-analysis of randomized controlled trials | BMC Medical Education
Wang B, Jin S, Huang M, Zhang K, Zhou Q, Zhang X, et al. Application of lecture-and-team-based learning in stomatology: in-class and online. BMC Med Educ. 2024;24(1):264. https://doi.org/10.1186/s12909-024-05235-2.
Google Scholar
Zeng HL, Chen DX, Li Q, Wang XY. Effects of seminar teaching method versus lecture-based learning in medical education: a meta-analysis of randomized controlled trials. Med Teach. 2020;42(12):1343–9. https://doi.org/10.1080/0142159x.2020.1805100.
Google Scholar
Saragih ID, Suarilah I, Hsiao CT, Fann WC, Lee BO. Interdisciplinary simulation-based teaching and learning for healthcare professionals: a systematic review and meta-analysis of randomized controlled trials. Nurse Educ Pract. 2024;76:103920. https://doi.org/10.1016/j.nepr.2024.103920.
Google Scholar
Truchot J, Boucher V, Li W, Martel G, Jouhair E, Raymond-Dufresne É, et al. Is in situ simulation in emergency medicine safe? A scoping review. BMJ Open. 2022;12(7):e059442. https://doi.org/10.1136/bmjopen-2021-059442.
Google Scholar
Lee AJ, Goodman S, Corradini B, Cohn S, Chatterji M, Landau R. A serious video game—EmergenCSim™—for novice anesthesia trainees to learn how to perform general anesthesia for emergency Cesarean delivery: a randomized controlled trial. Anesthesiol Perioper Sci. 2023;1(2):14. https://doi.org/10.1007/s44254-023-00016-4.
Google Scholar
Ng JY, Cramer H, Lee MS. Traditional, complementary, and integrative medicine and artificial intelligence: novel opportunities in healthcare. Integr Med Res. 2024;13(1):101024. https://doi.org/10.1016/j.imr.2024.101024.
Google Scholar
Busch F, Hoffmann L, Truhn D, Ortiz-Prado E, Makowski MR, Bressem KK, et al. Global cross-sectional student survey on AI in medical, dental, and veterinary education and practice at 192 faculties. BMC Med Educ. 2024;24(1):1066. https://doi.org/10.1186/s12909-024-06035-4.
Google Scholar
Preiksaitis C, Rose C. Opportunities, challenges, and future directions of generative artificial intelligence in medical education: scoping review. JMIR Med Educ. 2023;9:e48785. https://doi.org/10.2196/48785.
Google Scholar
Waldock WJ, Zhang J, Guni A, Nabeel A, Darzi A, Ashrafian H. The accuracy and capability of artificial intelligence solutions in health care examinations and certificates: systematic review and meta-analysis. J Med Internet Res. 2024;26:e56532. https://doi.org/10.2196/56532.
Google Scholar
Davies NP, Wilson R, Winder MS, Tunster SJ, McVicar K, Thakrar S, et al. ChatGPT sits the DFPH exam: large Language model performance and potential to support public health learning. BMC Med Educ. 2024;24(1):57. https://doi.org/10.1186/s12909-024-05042-9.
Google Scholar
Gilson A, Safranek CW, Huang T, Socrates V, Chi L, Taylor RA, et al. How does ChatGPT perform on The united States medical licensing examination (USMLE)? The implications of large Language models for medical education and knowledge assessment. JMIR Med Educ. 2023;9:e45312. https://doi.org/10.2196/45312.
Google Scholar
Skalidis I, Cagnina A, Luangphiphat W, Mahendiran T, Muller O, Abbe E, et al. ChatGPT takes on the European exam in core cardiology: an artificial intelligence success story? Eur Heart J Digit Health. 2023;4(3):279–81. https://doi.org/10.1093/ehjdh/ztad029.
Google Scholar
Freeman S, Eddy SL, McDonough M, Smith MK, Okoroafor N, Jordt H, et al. Active learning increases student performance in science, engineering, and mathematics. Proc Natl Acad Sci U S A. 2014;111(23):8410–5. https://doi.org/10.1073/pnas.1319030111.
Google Scholar
Boscardin CK, Gin B, Golde PB, Hauer KE. ChatGPT and generative artificial intelligence for medical education: potential impact and opportunity. Acad Med. 2024;99(1):22–7. https://doi.org/10.1097/acm.0000000000005439.
Google Scholar
Wu Y, Zheng Y, Feng B, Yang Y, Kang K, Zhao A. Embracing ChatGPT for medical education: exploring its impact on Doctors and medical students. JMIR Med Educ. 2024;10:e52483. https://doi.org/10.2196/52483.
Google Scholar
Xu T, Weng H, Liu F, Yang L, Luo Y, Ding Z, et al. Current status of ChatGPT use in medical education: potentials, challenges, and strategies. J Med Internet Res. 2024;26:e57896. https://doi.org/10.2196/57896.
Google Scholar
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. Rev Esp Cardiol. 2021;74(9):790–9. https://doi.org/10.1016/j.rec.2021.07.010.
Google Scholar
Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, et al. The Cochrane collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928. https://doi.org/10.1136/bmj.d5928.
Google Scholar
Brożek JL, Akl EA, Compalati E, Kreis J, Terracciano L, Fiocchi A, et al. Grading quality of evidence and strength of recommendations in clinical practice guidelines part 3 of 3. The GRADE approach to developing recommendations. Allergy. 2011;66(5):588–95. https://doi.org/10.1111/j.1398-9995.2010.02530.x.
Google Scholar
Cumpston M, Li T, Page MJ, Chandler J, Welch VA, Higgins JP, et al. Updated guidance for trusted systematic reviews: a new edition of the Cochrane handbook for systematic reviews of interventions. Cochrane Database Syst Rev. 2019;10(10):ED000142. https://doi.org/10.1002/14651858.Ed000142.
Google Scholar
Ba H, Zhang L, Yi Z. Enhancing clinical skills in pediatric trainees: a comparative study of ChatGPT-assisted and traditional teaching methods. BMC Med Educ. 2024;24(1):558. https://doi.org/10.1186/s12909-024-05565-1.
Google Scholar
Bhatia AP, Lambat A, Jain T. A comparative analysis of conventional and chat-generative pre-trained transformer-assisted teaching methods in undergraduate dental education. Cureus. 2024;16(5):e60006. https://doi.org/10.7759/cureus.60006.
Google Scholar
Çiçek FE, Ülker M, Özer M, Kiyak YS. ChatGPT versus expert feedback on clinical reasoning questions and their effect on learning: a randomized controlled trial. Postgrad Med J. 2024;458–63. https://doi.org/10.1093/postmj/qgae170.
Gan W, Ouyang J, Li H, Xue Z, Zhang Y, Dong Q, et al. Integrating ChatGPT in orthopedic education for medical undergraduates: randomized controlled trial. J Med Internet Res. 2024;26:e57037. https://doi.org/10.2196/57037.
Google Scholar
Huang Y, Xu BB, Wang XY, Luo YC, Teng MM, Weng X. Implementation and evaluation of an optimized surgical clerkship teaching model utilizing ChatGPT. BMC Med Educ. 2024;24(1):1540. https://doi.org/10.1186/s12909-024-06575-9.
Google Scholar
Zeng H, Zhu ZW, Hu J, Cui Y. Application of ChatGPT-assisted problem-based learning teaching method in clinical medical education. BMC Med Educ. 2025;25(1):50.
Jiang Y, Fu X, Wang J, Liu Q, Wang X, Liu P, et al. Enhancing medical education with chatbots: a randomized controlled trial on standardized patients for colorectal cancer. BMC Med Educ. 2024;24(1):1511. https://doi.org/10.1186/s12909-024-06530-8.
Google Scholar
Kavadella A, Dias da Silva MA, Kaklamanos EG, Stamatopoulos V, Giannakopoulos K. Evaluation of chatgpt’s real-life implementation in undergraduate dental education: mixed methods study. JMIR Med Educ. 2024;10:e51344. https://doi.org/10.2196/51344.
Google Scholar
Svendsen K, Askar M, Umer D, Halvorsen KH. Short-term learning effect of ChatGPT on pharmacy students’ learning. Explor Res Clin Soc Pharm. 2024;15:100478. https://doi.org/10.1016/j.rcsop.2024.100478.
Google Scholar
Tabuchi H, Nakajima I, Day M, Yoneda T, Tanabe M, Strang N, et al. Comparative educational effectiveness of AI generated images and traditional lectures for diagnosing Chalazion and sebaceous carcinoma. Sci Rep. 2024;14(1):29200. https://doi.org/10.1038/s41598-024-80732-4.
Google Scholar
Wu C, Chen L, Han M, Li Z, Yang N, Yu C. Application of ChatGPT-based blended medical teaching in clinical education of hepatobiliary surgery. Med Teach. 2024;47(3):445–9. https://doi.org/10.1080/0142159X.2024.2339412.
Google Scholar
Kreiter CD, Green J, Lenoch S, Saiki T. The overall impact of testing on medical student learning: quantitative Estimation of consequential validity. Adv Health Sci Educ Theory Pract. 2013;18(4):835–44. https://doi.org/10.1007/s10459-012-9395-7.
Google Scholar
George Pallivathukal R, Kyaw Soe HH, Donald PM, Samson RS, Hj Ismail. A R. ChatGPT for academic purposes: survey among undergraduate healthcare students in Malaysia. Cureus. 2024;16(1):e53032. https://doi.org/10.7759/cureus.53032.
Google Scholar
Cabellos B, de Aldama C, Pozo JI. University teachers’ beliefs about the use of generative artificial intelligence for teaching and learning. Front Psychol. 2024;15:1468900. https://doi.org/10.3389/fpsyg.2024.1468900.
Google Scholar
Borg A, Jobs B, Huss V, Gentline C, Espinosa F, Ruiz M, et al. Enhancing clinical reasoning skills for medical students: a qualitative comparison of LLM-powered social robotic versus computer-based virtual patients within rheumatology. Rheumatol Int. 2024;44(12):3041–51. https://doi.org/10.1007/s00296-024-05731-0.
Google Scholar
Arun G, Perumal V, Urias F, Ler YE, Tan BWT, Vallabhajosyula R, et al. ChatGPT versus a customized AI chatbot (Anatbuddy) for anatomy education: a comparative pilot study. Anat Sci Educ. 2024;17(7):1396–405. https://doi.org/10.1002/ase.2502.
Google Scholar
Holderried F, Stegemann-Philipps C, Herschbach L, Moldt JA, Nevins A, Griewatz J, et al. A generative pretrained transformer (GPT)-powered chatbot as a simulated patient to practice history taking: prospective, mixed methods study. JMIR Med Educ. 2024;10:e53961. https://doi.org/10.2196/53961.
Google Scholar
Komasawa N, Yokohira M. Simulation-based education in the artificial intelligence era. Cureus. 2023;15(6):e40940. https://doi.org/10.7759/cureus.40940.
Google Scholar
Cook DA. Creating virtual patients using large Language models: scalable, global, and low cost. Med Teach. 2025;47(1):40–2. https://doi.org/10.1080/0142159x.2024.2376879.
Google Scholar
Xu Y, Jiang Z, Ting DSW, Kow AW, C, Bello F, Car J, et al. Medical education and physician training in the era of artificial intelligence. Singap Med J. 2024;65(3):159–66. https://doi.org/10.4103/singaporemedj.SMJ-2023-203.
Google Scholar
Driesnack S, Rücker F, Dietze-Jergus N, Bondarenko A, Pletz MW, Viehweger A. A practice-based approach to teaching antimicrobial therapy using artificial intelligence and gamified learning. JAC Antimicrob Resist. 2024;6(4):dlae099. https://doi.org/10.1093/jacamr/dlae099.
Google Scholar
Ossa LA, Rost M, Lorenzini G, Shaw DM, Elger BS. A smarter perspective: learning with and from AI-cases. Artif Intell Med. 2023;135:102458. https://doi.org/10.1016/j.artmed.2022.102458.
Google Scholar
Vertemati M, Zuccotti GV, Porrini M. Enhancing anatomy education through flipped classroom and adaptive learning a pilot project on liver anatomy. J Med Educ Curric Dev. 2024;11:23821205241248023. https://doi.org/10.1177/23821205241248023.
Google Scholar
Gordon M, Daniel M, Ajiboye A, Uraiby H, Xu NY, Bartlett R, et al. A scoping review of artificial intelligence in medical education: BEME guide 84. Med Teach. 2024;46(4):446–70. https://doi.org/10.1080/0142159x.2024.2314198.
Google Scholar
Ullah M, Bin Naeem S, Kamel Boulos MN. Assessing the guidelines on the use of generative artificial intelligence tools in universities: a survey of the world’s top 50 universities. Big Data Cogn Comput. 2024;194. https://doi.org/10.3390/bdcc8120194.
Stogiannos N, Skelton E, Kumar S, Ahmed S, Amedu C, Vince C, et al. Evaluation of a customised, AI-focused educational seminar delivered to final year undergraduate radiography students in the UK: a cross-sectional study. Radiography. 2025;31(3):102926. https://doi.org/10.1016/j.radi.2025.102926.
Google Scholar
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