BMC Med Educ. 2026 Aug 4;26(1):1763. doi: 10.1186/s12909-026-09650-5.
ABSTRACT
BACKGROUND: This study evaluated whether a structured pedagogical framework integrating large language models (LLMs) into residency training could develop clinical reasoning competencies that transfer to independent performance.
METHODS: In this prospective randomized controlled trial, residents were assigned to Teacher-Student-Machine Interaction Autonomous Learning (TSM-AL) group or traditional teaching group. The TSM-AL framework positioned LLMs as supervised cognitive auxiliaries within a five-step case analysis process featuring controlled information release, predefined reasoning tasks, and structured utilization guidelines. Six formative assessments were conducted over 16 weeks, followed by summative examinations under both LLM-assisted and unassisted conditions. Outcomes included clinical reasoning scores, entrustable professional activity (EPA) levels, global faculty ratings, expert-aligned diagnostic accuracy, and standardized patient examination performance.
RESULTS: Significant between-group differences in diagnostic pathway completeness emerged at week 14 (3.53 ± 1.36 vs. 2.68 ± 1.49, P = 0.018) and week 16 (3.35 ± 1.43 vs. 2.37 ± 1.51, P = 0.009). In the unassisted final examination, the TSM-AL group demonstrated significantly higher clinical reasoning scores (7.32 ± 2.30 vs. 5.12 ± 1.66, P < 0.001). EPA distributions differed significantly (P = 0.034), with fewer TSM-AL residents requiring complete supervision (11.76% vs. 29.41%). Global faculty ratings also differed significantly (P = 0.019), with 23.53% of TSM-AL residents achieving Level 5 compared to none in the traditional group. Expert alignment for core problem identification (67.65% vs. 44.12%, P = 0.042) and differential diagnosis matching (73.53% vs. 50.00%, P = 0.046) favored the TSM-AL group. Standardized patient examination scores were significantly higher in the TSM-AL group (80.88 ± 3.82 vs. 78.71 ± 3.90, P = 0.025). Notably, TSM-AL residents performed better without LLM assistance than with assistance.
CONCLUSIONS: The TSM-AL framework significantly enhanced clinical reasoning competencies that transferred to independent performance, demonstrating that structured LLM integration develops autonomous reasoning rather than fostering technological dependency.
PMID:42968068 | DOI:10.1186/s12909-026-09650-5
