学术集中项目开发：一种可推广的、数据驱动的方法。
Scholarly Concentration Program Development: A Generalizable, Data-Driven Approach.
作者信息
Burk-Rafel Jesse, Mullan Patricia B, Wagenschutz Heather, Pulst-Korenberg Alexandra, Skye Eric, Davis Matthew M
机构信息
J. Burk-Rafel is a fourth-year medical student, University of Michigan Medical School, Ann Arbor, Michigan. P.B. Mullan is professor of medical education, Department of Learning Health Sciences, University of Michigan Medical School, Ann Arbor, Michigan. H. Wagenschutz is codirector, Paths of Excellence, and codirector for leadership, University of Michigan Medical School, Ann Arbor, Michigan. A. Pulst-Korenberg is a resident physician, Department of Emergency Medicine, University of Washington Medical Center, Seattle, Washington. E. Skye is codirector, Paths of Excellence, house director, M-Home Learning Community, and associate professor, University of Michigan Medical School, Ann Arbor, Michigan. M.M. Davis is professor of pediatrics, division head of Academic General Pediatrics, and director of the Smith Child Health Research Center, Ann and Robert H. Lurie Children's Hospital, Northwestern Feinberg School of Medicine, Chicago, Illinois.
出版信息
Acad Med. 2016 Nov;91(11 Association of American Medical Colleges Learn Serve Lead: Proceedings of the 55th Annual Research in Medical Education Sessions):S16-S23. doi: 10.1097/ACM.0000000000001362.
PURPOSE
Scholarly concentration programs-also known as scholarly projects, pathways, tracks, or pursuits-are increasingly common in U.S. medical schools. However, systematic, data-driven program development methods have not been described.
METHOD
The authors examined scholarly concentration programs at U.S. medical schools that U.S. News & World Report ranked as top 25 for research or primary care (n = 43 institutions), coding concentrations and mission statements. Subsequently, the authors conducted a targeted needs assessment via a student-led, institution-wide survey, eliciting learners' preferences for 10 "Pathways" (i.e., concentrations) and 30 "Topics" (i.e., potential content) augmenting core curricula at their institution. Exploratory factor analysis (EFA) and a capacity optimization algorithm characterized best institutional options for learner-focused Pathway development.
RESULTS
The authors identified scholarly concentration programs at 32 of 43 medical schools (74%), comprising 199 distinct concentrations (mean concentrations per program: 6.2, mode: 5, range: 1-16). Thematic analysis identified 10 content domains; most common were "Global/Public Health" (30 institutions; 94%) and "Clinical/Translational Research" (26 institutions; 81%). The institutional needs assessment (n = 468 medical students; response rate 60% overall, 97% among first-year students) demonstrated myriad student preferences for Pathways and Topics. EFA of Topic preferences identified eight factors, systematically related to Pathway preferences, informing content development. Capacity modeling indicated that offering six Pathways could guarantee 95% of first-year students (162/171) their first- or second-choice Pathway.
CONCLUSIONS
This study demonstrates a generalizable, data-driven approach to scholarly concentration program development that reflects student preferences and institutional strengths, while optimizing program diversity within capacity constraints.
目的
学术集中项目（也称为学术项目、途径、轨道或追求）在美国医学院越来越普遍。然而，尚未描述系统的、数据驱动的项目开发方法。
方法
作者研究了《美国新闻与世界报道》评选出的研究或初级保健排名前25的美国医学院的学术集中项目（n = 43所机构），对集中领域和使命声明进行编码。随后，作者通过学生主导的全校范围调查进行了有针对性的需求评估，了解学习者对10个“途径”（即集中领域）和30个“主题”（即潜在内容）的偏好，这些将补充他们所在机构的核心课程。探索性因素分析（EFA）和容量优化算法确定了以学习者为中心的途径开发的最佳机构选择。
结果
作者在43所医学院中的32所（74%）确定了学术集中项目，包括199个不同的集中领域（每个项目的平均集中领域数：6.2，众数：5，范围：1 - 16）。主题分析确定了10个内容领域；最常见的是“全球/公共卫生”（30所机构；94%）和“临床/转化研究”（26所机构；81%）。机构需求评估（n = 468名医学生；总体回复率60%，一年级学生中为97%）显示学生对途径和主题有众多偏好。对主题偏好的EFA确定了八个因素，与途径偏好系统相关，为内容开发提供了信息。容量建模表明，提供六个途径可以保证95%的一年级学生（162/171）获得他们的第一或第二选择途径。
结论
本研究展示了一种可推广的、数据驱动的学术集中项目开发方法，该方法反映了学生偏好和机构优势，同时在容量限制内优化项目多样性。
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