ArticleAnnals of translational medicine2020
Artificial intelligence-tutoring problem-based learning in ophthalmology clerkship.
Article in Annals of translational medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 3 of them syntheses that pooled it.
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Who cites it
22 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- The Effectiveness of Artificial Intelligence in Undergraduate Health Professions Education: Systematic Review and Meta-Analysis of Randomized Controlled Trials.JMIR medical education · 2026Pooled it
- AI-Powered Problem- and Case-based Learning in Medical and Dental Education: A Systematic Review and Meta-analysis.International dental journal · 2025Pooled it
- Adherence of randomised controlled trials using artificial intelligence in ophthalmology to CONSORT-AI guidelines: a systematic review and critical appraisal.BMJ health & care informatics · 2023Pooled it
- Performance evaluation of generative pre-trained transformer on the National Veterinary Licensing Examination in Japan.Scientific reports · 2026Article
- Enhancing Medical Education: The Role of Artificial Intelligence Tools in the Teaching-Learning Process.Advances in medical education and practice · 2026Review
- Effects of Artificial Intelligence-Supported Education on Critical Thinking, Problem-Solving, Clinical Reasoning, and Decision-Making in Health Science Education: A Systematic Review of Interventional Studies.Advances in medical education and practice · 2026Review
- Visualizing Multi-Step Decision-Making at a Glance: Pairing Choose Your Own Adventure Style Simulated Cases with a Novel Mapping Framework.Medical science educator · 2025Article
- Application of DeepSeek-assisted problem-based learning in hematology residency training.BMC medical education · 2025Article
- Evaluating the Agreement Between ChatGPT and the Clinical Competency Committee in Assigning ACGME Milestones for Family Medicine Residents.Family medicine · 2025Article
- Leveraging AI-enabled mobile learning platforms to enhance the effectiveness of English teaching in universities.Scientific reports · 2025Article
- Can a large language model create acceptable dental board-style examination questions? A cross-sectional prospective study.Journal of dental sciences · 2025Article
- Artificial intelligence technology in ophthalmology public health: current applications and future directions.Frontiers in cell and developmental biology · 2025Review
- Impact of Artificial Intelligence on the Knowledge, Attitude, and Performance of Ophthalmology Residents: A Systematic Review.Journal of ophthalmic & vision research · 2025Article
- Artificial intelligence in corneal diseases: A narrative review.Contact lens & anterior eye : the journal of the British Contact Lens Association · 2024Review
- Review
- Medical Education 4.0: A Neurology Perspective.Cureus · 2022Review
- Digital Education in Ophthalmology.Asia-Pacific journal of ophthalmology (Philadelphia, Pa.) · 2022Article
- Use of artificial intelligence as a didactic tool to improve ejection fraction assessment in the emergency department: A randomized controlled pilot study.AEM education and training · 2022Article
- The effectiveness of artificial intelligence-based automated grading and training system in education of manual detection of diabetic retinopathy.Frontiers in public health · 2022Article
- Artificial intelligence-based pathologic myopia identification system in the ophthalmology residency training program.Frontiers in cell and developmental biology · 2022Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundArtificial intelligence (AI) is an increasingly popular tool in medical investigations. However, AI's potential of aiding medical teaching has not been explored. This study aimed to evaluate the effectiveness of AI-tutoring problem-based-learning (PBL) in ophthalmology clerkship and to assess the student evaluations of this module.
methodsThirty-eight Grade-two students in ophthalmology clerkship at Sun Yat-Sen University were randomly assigned to two groups. In Group A, students learned congenital cataracts through an AI-tutoring PBL module by exploring and operating an AI diagnosis platform. In Group B, students learned congenital cataracts through traditional lecture given with the same faculty. The improvement in student performance was evaluated by comparing the pre- and post-lecture scores of a specific designed test using paired-T tests. Student evaluations of AI-tutoring PBL were measured by a 17-item questionnaire.
resultsThe post-lecture scores were significantly higher than the pre-lecture scores in both groups (Group A: P<0.0001, Group B: P<0.0001). The improvement of group A in the part of sign and diagnosis test (Part I) was more significant than that of group B (P=0.016). However, there was no difference in the improvement in the part of treatment plan test (Part II) between two groups (P=0.556). Overall, all respondents were satisfied and agreed that AI-tutoring PBL was helpful, effective, motive and beneficial to help develop critical and creative thinking.
conclusionsThe application of AI-tutoring PBL into ophthalmology clerkship improved students' performance and satisfaction. AI-tutoring PBL teaching showed advantage in promoting students' understanding of signs of diseases. The instructors play an indispensable role in AI-tutoring PBL curriculum.
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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 OpenQuestion graph.