Healy Padraig Mark, O'Tuathaigh Colm, Heavin Ciara, McCarthy Nora, Latifi Syed
School of Medicine, Medical Education Unit, University College Cork, Cork, Ireland.
Division of Medical Education, Weill Cornell Medicine - Qatar, Doha, Qatar.
JMIR Res Protoc. 2025 Aug 21;14:e69979. doi: 10.2196/69979.
In health professions education (HPE), the concept of precision education is being explored, with the intention of tailoring learning experiences to the unique needs of learners. Recommender systems can assist academic decision-making. They can be used to personalize content delivery, suggest appropriate learning pathways, propose schedules, recommend suitable institutes, supervisors, and courses, and provide learner feedback. Given abundant learning resources, selecting the right one can be daunting. Recommender systems may address this challenge by offering tailored suggestions that align with learners' requirements and abilities.
This study aims to examine the literature related to the use of recommender systems in HPE.
This review will be conducted following the methodological framework proposed by Arksey and O'Malley. A comprehensive search will be conducted across the MEDLINE, CINAHL Plus with Full Text, ERIC, Academic Search Premier, and Web of Science databases, as well as gray literature sources including arXiv and Google Scholar. These searches will focus on the period from January 2000 to February 2025. In addition, backward and forward citation searching will be carried out. Articles will be screened independently by 2 reviewers; discrepancies resolved by consensus or a third reviewer. The selection process will involve an initial screening of titles and abstracts to identify potentially relevant articles. If initial screening is inconclusive, full-text review will ensure articles meet inclusion criteria. The main eligibility criteria for inclusion in the review are studies involving health professions students or educators, focusing on the concept, development, or application of recommender systems. Data extraction will be performed using a customized data charting template covering article, study, and recommender system details. The extracted data will be analyzed and displayed in both tabular and graphical formats, supplemented by a narrative interpretation. The findings will be synthesized by mapping the existing literature to identify key concepts, research gaps, and types of evidence, highlighting similarities and differences in how recommender systems are applied in HPE. This reporting will be in accordance with the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. Data extraction and analysis will be conducted using Covidence.
The current phase of the study involves selecting studies for the scoping review as specified in this protocol. The search, screening, and data extraction will begin in February 2025. The results of the study and the submission of a manuscript for peer review are expected in the winter of 2025.
This study aims to comprehensively map the extent of recommender systems in HPE. By identifying effective practices and existing gaps, it will serve as a valuable resource for health professions educators, enabling them to make informed decisions about integrating these systems into educational applications.
INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/69979.
在健康职业教育（HPE）中，人们正在探索精准教育的概念，旨在根据学习者的独特需求定制学习体验。推荐系统可以辅助学术决策。它们可用于个性化内容推送、建议合适的学习路径、制定学习计划、推荐合适的机构、导师和课程，并提供学习者反馈。鉴于学习资源丰富，选择合适的资源可能会让人望而生畏。推荐系统可以通过提供符合学习者要求和能力的定制建议来应对这一挑战。
本研究旨在审查与推荐系统在健康职业教育中的应用相关的文献。
本综述将按照Arksey和O'Malley提出的方法框架进行。将在MEDLINE、CINAHL Plus with Full Text、ERIC、Academic Search Premier和Web of Science数据库以及包括arXiv和谷歌学术在内的灰色文献来源中进行全面搜索。这些搜索将集中在2000年1月至2025年2月期间。此外，还将进行前后向引文搜索。文章将由2名评审员独立筛选；分歧通过协商一致或由第三名评审员解决。选择过程将包括初步筛选标题和摘要以识别潜在相关文章。如果初步筛选不确定，则进行全文审查以确保文章符合纳入标准。纳入本综述的主要合格标准是涉及健康职业学生或教育工作者的研究，重点是推荐系统的概念、开发或应用。将使用涵盖文章、研究和推荐系统详细信息的定制数据图表模板进行数据提取。提取的数据将以表格和图形格式进行分析和展示，并辅以叙述性解释。通过将现有文献进行映射以识别关键概念、研究差距和证据类型，突出推荐系统在健康职业教育中的应用方式的异同，从而综合研究结果。本报告将符合PRISMA-ScR（系统评价和Meta分析扩展的范围综述优先报告项目）指南。数据提取和分析将使用Covidence进行。
本研究的当前阶段涉及按照本方案指定选择进行范围综述的研究。搜索、筛选和数据提取将于2025年2月开始。预计2025年冬季将得出研究结果并提交同行评审稿件。
本研究旨在全面描绘推荐系统在健康职业教育中的应用范围。通过识别有效做法和现有差距，它将为健康职业教育工作者提供宝贵资源，使他们能够就是否将这些系统整合到教育应用中做出明智决策。
国际注册报告识别号（IRRID）：PRR1-10.2196/69979。
