Implementation and Educational Impact of a Story-Centered Curriculum Using a Large Language Model: A Class on Internal Disorders for Physiotherapy Students

Background Story-centered curricula (SCC) can effectively enhance clinical reasoning and learner engagement; however, developing high-fidelity scenarios is resource-intensive. We developed an SCC using a large language model (LLM; ChatGPT, GPT-4) to generate longitudinal respiratory cases for physiotherapy students and evaluated its educational impact. Methodology This single-institution, quasi-experimental study used a non-randomized historical control design. Physiotherapy students in a 15-session course were divided into an SCC group, which completed eight LLM-generated narrative sessions, and a control group, which received traditional case-based sessions without a continuous storyline. The primary outcome was the change in score on a 30-item, 300-point proficiency test administered before and after the intervention. Secondary outcomes included five Likert-scale items evaluating learner experience. Group comparisons used appropriate parametric or non-parametric tests, and multivariable linear regression adjusted for age, sex, program, and pre-test score. Results The final sample consisted of 169 participants, with 92 in the SCC group and 77 in the control group. Baseline characteristics and pre-test median scores were 90 with an interquartile range (IQR) of 70 to 100 in the SCC group and 90 with an IQR of 70 to 110 in the control group, showing no significant differences between groups. The SCC group demonstrated a greater improvement in test performance, with a median change of 105 and an IQR of 78 to 140, compared with a median change of 80 and an IQR of 50 to 110 in the control group (p < 0.001). The SCC group also achieved higher post-test scores, with a median of 195 and an IQR of 160 to 223, compared with a median of 180 and an IQR of 150 to 200 in the control group (p = 0.013). Positive questionnaire responses (scores of 4 or 5) exceeded 90% across all domains, including immersion 87 (94.6%) and learning retention 88 (95.7%). Participation in the SCC program remained an independent predictor of post-test performance, with a regression coefficient of 23.87 and a 95% confidence interval of 11.32 to 36.42 (p < 0.001). Conclusions An SCC utilizing an LLM is an innovative educational approach that effectively balances improved learning outcomes with efficient scenario development, offering significant potential to advance simulation-based education in physiotherapy.