AI-Assisted Problem-Based Learning Lifts Knowledge Retention in Physiotherapy Education — Istanbul–Toledo RCT

Developing realistic clinical scenarios for problem-based learning (PBL) is a core but time-intensive part of physiotherapy education, and instructors have limited tools to verify whether AI-assisted versions of this method actually improve what students retain.
In June 2025, Istanbul Medipol University (Turkey) and Universidad de Castilla-La Mancha (Spain) ran a prospective, two-arm randomized controlled trial: 40 physiotherapy students were randomized to either AI-assisted PBL, using ChatGPT-4.0 in small groups to build simulated patient scenarios, evaluation plans and management strategies for chronic low back pain under instructor guidance, or traditional PBL without AI. Of the 40 randomized, 35 completed the trial (19 AI-PBL, 16 traditional PBL).
At 2-week follow-up, the AI-PBL group showed very large gains in knowledge retention (Cohen's d = 3.14) and AI self-efficacy (d = 1.70) relative to traditional PBL, and higher reading motivation (d = 1.31). Clinical competence, measured with the Mini Clinical Evaluation Exercise, was only marginally higher in the AI-PBL group and the difference was not statistically significant (d = 0.42).
The trial's strength is its randomized, peer-reviewed design; its limitation is scale — 35 completers at two universities, a single clinical topic, and a two-week follow-up window — so the very large effect sizes should be read as an early, promising signal rather than a settled result.

Read the full analysis: https://clinicaltrials.gov/study/NCT07010991