{ "abstract": "Background\n\nThis 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\n\nIn 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\n\nSignificant 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\n\nThe 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.", "abstract_shown": true, "affiliations": [ "Department of Surgery and Field Surgery, Changzheng Hospital, Navy Military Medical University, Shanghai, 200003, China.", "Department of Orthorpedic Oncology, Changzheng Hospital, Navy Military Medical University, 415th Fengyang Road, Shanghai, 200003, China.", "Department of Emergency Medicine, Naval Medical Center, 338th West Huaihai Road, Shanghai, 200050, China.", "Department of Cardiology, the 961st Hospital of Joint Logistic Support Force of PLA, 189th Jianhua Middle Road, Qiqihar City, 161000, Heilongjiang Province, China.", "Department of Cardiology, Shanghai Changzheng Hospital, Naval Medical University, No. 415, Fengyang Road, Huangpu District, Shanghai, China.", "Department of Orthorpedic Oncology, Changzheng Hospital, Navy Military Medical University, 415th Fengyang Road, Shanghai, 200003, China. Liboczspine@smmu.edu.cn.", "Medical Administration Division, Chinese PLA General Hospital, 28th Fuxing Road, Beijing, 100853, China. yingtianhello@163.com.", "Department of Orthorpedic Oncology, Changzheng Hospital, Navy Military Medical University, 415th Fengyang Road, Shanghai, 200003, China. xuwei_spine@163.com." ], "article_type": "research article", "arxiv": null, "author_total": 10, "authors": [ { "affs": [ 0, 1 ], "name": "Pengru Wang" }, { "affs": [ 2 ], "name": "He Li" }, { "affs": [ 3 ], "name": "Dingyuan Tu" }, { "affs": [ 4 ], "name": "Huilong Qu" }, { "affs": [ 0 ], "name": "Mengli Chang" }, { "affs": [ 0 ], "name": "Qiying Zhang" }, { "affs": [ 1 ], "name": "Gan Xu" }, { "affs": [ 5 ], "name": "Bo Li" }, { "affs": [ 6 ], "name": "Yingtian Wang" }, { "affs": [ 7 ], "name": "Wei Xu" } ], "bibtex": "https://research.draconitic.com/paper/1bhzm9r4eawnk.bib", "cited_by": 0, "doi": "10.1186/s12909-026-09650-5", "fulltext_url": "https://europepmc.org/articles/PMC13726233", "id": "1bhzm9r4eawnk", "issns": [ "1472-6920" ], "landing_url": "https://europepmc.org/article/MED/42968068", "language": "eng", "licence": "CC-BY-NC-ND", "licence_label": "CC BY-NC-ND", "licence_source": "article", "licence_url": "https://creativecommons.org/licenses/by-nc-nd/4.0/", "metadata_licence": null, "native_subjects": [ [ "heading", "Research" ], [ "openalex", "2718|Artificial Intelligence in Healthcare and Education" ] ], "openalex": "W7172439255", "pdf_url": "https://europepmc.org/articles/PMC13726233?pdf=render", "pmcid": "PMC13726233", "pmid": "42968068", "published": "2026-08-04", "publisher": "BMC", "ris": "https://research.draconitic.com/paper/1bhzm9r4eawnk.ris", "sources": [ { "first_seen": "2026-11-03T15:20:54Z", "native_id": "MED:42968068", "source": "europepmc", "url": "https://europepmc.org/article/MED/42968068" }, { "first_seen": "2026-11-05T12:22:37Z", "native_id": "PMC13726233", "source": "pmc", "url": "https://doi.org/10.1186/s12909-026-09650-5" } ], "subjects": [ { "field": "medicine", "origin": "openalex:2718|Artificial Intelligence in Healthcare and Education", "subfield": "epidemiology-public-health" } ], "title": "Teacher-student-machine interaction autonomous learning: a structured LLM-integrated framework for developing independent clinical reasoning in residency training.", "title_text": "Teacher-student-machine interaction autonomous learning: a structured LLM-integrated framework for developing independent clinical reasoning in residency training.", "type": "peer-reviewed", "updated_at": "2026-11-06T12:22:14Z", "url": "https://research.draconitic.com/paper/1bhzm9r4eawnk", "venue": "BMC medical education", "versions": [] }