ArticleCureus2025
Artificial Intelligence Versus Traditional Learning in a Medical School Setting.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline 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-assisted learning in exercise physiology: a quasi-experimental study using PhysioExercise GPT.Frontiers in physiology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionAs technology advances in every aspect of our lives, educational curricula are moving away from traditional didactic lectures toward more interactive modalities. While there are many ways to incorporate non-traditional learning methods into medical curricula, the increasing prevalence of Artificial Intelligence (AI) offers a novel avenue. This study aims to determine whether the use of AI enhances learning as compared to more traditional flipped classroom styles, such as lecture slides and voice-over videos.
methodsIncoming first-year medical students were given learning materials prior to course instruction. Participating students were randomly assigned to three educational groups: PowerPoint slides only (PPT), voice-over videos and PowerPoint slides (VO+PPT), or Artificial Intelligence learning and PowerPoint slides (AI+PPT). After reviewing the materials, all study participants took a 22-question formative quiz. The average overall scores and the scores on the five most "difficult" questions were assessed between groups.
resultsSixty-two incoming students participated in this study. There was no significant change between groups regarding overall scores. The PPT group had significantly lower scores on the five most "difficult" questions when compared to the VO+PPT (p = 0.026) and AI+PPT (p = 0.004) groups. However, there were no significant changes in scores on the five most "difficult" questions between the VO+PPT and AI+PPT groups (p = 0.834).
conclusionsThe VO+PPT and AI+PPT groups performed similarly but significantly better than the PPT-only group regarding performance on "difficult" questions. Overall, our study provides evidence that Artificial Intelligence and voice-over modalities are equally viable methods of learning, depending on the demands of professors and students.
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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.