Open Access Article
Modern Social Science Research. 2026; 6: (7) ; 21-26 ; DOI: 10.12208/j.ssr.20260231.
The construction and practice of an ai-empowered virtual teaching and research community in rehabilitation: A novel paradigm for interdisciplinary talent cultivation
AI赋能康复虚拟教研室的构建与实践——跨学科人才培养新范式
作者：
曲福玲1,
邹晓峰2,
孙中波3,
卢秀泉4,
朱冰5,
赵丽晶6,
刘忠良1,
段晓琴1 *
1吉林大学第二医院康复医学科，吉林大学“康工结合”创新创业基地 吉林长春
2吉林大学体育学院 吉林长春
3长春工业大学 吉林长春
4吉林大学机械与航天航空学院 吉林长春
5吉林大学汽车工程学院 吉林长春
6吉林大学护理学院 吉林长春
*通讯作者：
段晓琴,单位：吉林大学第二医院康复医学科，吉林大学“康工结合”创新创业基地 吉林长春 ；
发布时间: 2026-07-16 总浏览量: 106
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摘要
为响应“健康中国2030”及《中国制造2025》战略，解决康复医学教育中存在的学科壁垒与智能化手段不足等问题，研究构建了AI赋能的康复相关专业虚拟教研室。基于超星微服务架构开发平台，通过“医学范围内融合-医学范围外交叉-校内外共同体构建”的三维路径，分阶段实施建设。研究采用平台开发、协作机制建立与多维评价等方法，对参与项目的412名学生（涵盖临床医学、康复治疗、体育学、机械工程等7个专业）的前后对比分析显示，跨专业能力量表得分由基线（3.12±0.54）提升至（4.32±0.48）（t=18.46，P<0.001）；临床案例解决正确率由72.3%提升至90.3%（χ²=16.72，P<0.001）。43名教师的跨学科教学能力自评得分提升率为93%，团队累计获批校级省部级课题6项，发表SCI 14篇，共建教学资源83项。为“四新”背景下复合型康复人才的“知识-能力-价值”三位一体培养提供了可复制的实践范式，同时指出需在智能技术深度融合与跨校协作机制上持续探索。
关键词： AI赋能；虚拟教研室；跨学科融合；人才培养；教育教学改革
Abstract
To break down disciplinary barriers and fill the gap in intelligent teaching tools within rehabilitation medicine education-an issue highlighted by the “Healthy China 2030” and “Made in China 2025” initiatives-we built an AI‑driven virtual teaching and research office for rehabilitation‑related majors. The platform was developed on Chaoxing’s microservice architecture and rolled out in three phases: intra‑medical integration, cross-disciplinary collaboration with non‑medical fields, and the formation of shared communities across and beyond campuses. Methods included platform construction, collaborative rule‑setting, and multi‑faceted evaluation. A pre-post comparison analysis of 412 students (spanning seven majors including clinical medicine, rehabilitation therapy, sports science, mechanical engineering, etc.) participating in the project revealed that the cross-disciplinary competency scale score increased from the baseline (3.12±0.54) to (4.32±0.48) (t=18.46, P<0.001); the correct rate of clinical case resolution rose from 72.3% to 90.3% (χ²=16.72, P<0.001). Among 43 instructors, 93% reported improved self-assessment scores in cross-disciplinary teaching abilities. The team collectively secured 6 university-level and ministerial-level research grants, published 14 SCI papers, and developed 83 shared teaching resources. This model provides a scalable pathway for training rehabilitation professionals under China’s “Four New” education framework, integrating knowledge, skills, and values. Further work should focus on deeper integration of AI tools and smoother cross‑institutional collaboration mechanisms.
Key words： AI empowerment; Virtual teaching and research community; Interdisciplinary integration; Talent cultivation; Educational reform
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引用本文
曲福玲, 邹晓峰, 孙中波, 卢秀泉, 朱冰, 赵丽晶, 刘忠良, 段晓琴, AI赋能康复虚拟教研室的构建与实践——跨学科人才培养新范式[J]. 现代社会科学研究, 2026; 6: (7) : 21-26.