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Sohrabi, Zohreh, Kavarizadeh, Forouzan, Karimi, Elham, Hosseinzadeh, Zohreh. (1404). Benefits and Challenges of Using Learning Analytics in Medical Education: A Scoping Review. سامانه مدیریت نشریات علمی, (), -. doi: 10.30476/ijvlms.2025.107744.1345
Zohreh Sohrabi; Forouzan Kavarizadeh; Elham Karimi; Zohreh Hosseinzadeh. "Benefits and Challenges of Using Learning Analytics in Medical Education: A Scoping Review". سامانه مدیریت نشریات علمی, , , 1404, -. doi: 10.30476/ijvlms.2025.107744.1345
Sohrabi, Zohreh, Kavarizadeh, Forouzan, Karimi, Elham, Hosseinzadeh, Zohreh. (1404). 'Benefits and Challenges of Using Learning Analytics in Medical Education: A Scoping Review', سامانه مدیریت نشریات علمی, (), pp. -. doi: 10.30476/ijvlms.2025.107744.1345
Sohrabi, Zohreh, Kavarizadeh, Forouzan, Karimi, Elham, Hosseinzadeh, Zohreh. Benefits and Challenges of Using Learning Analytics in Medical Education: A Scoping Review. سامانه مدیریت نشریات علمی, 1404; (): -. doi: 10.30476/ijvlms.2025.107744.1345

Benefits and Challenges of Using Learning Analytics in Medical Education: A Scoping Review

Interdisciplinary Journal of Virtual Learning in Medical Sciences
مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 06 دی 1404
نوع مقاله: Review Article
شناسه دیجیتال (DOI): 10.30476/ijvlms.2025.107744.1345
نویسندگان
Zohreh Sohrabi1؛ Forouzan Kavarizadeh1؛ Elham Karimi2؛ Zohreh Hosseinzadeh* 1
1Center for Educational Research in Medical Sciences, Department of Medical Education, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
2School of Health, Education, Policing and Sciences, Staffordshire Univercity, Staffordshie, UK
چکیده
Background: Learning analytics includes collecting and analysing learners’ data to improve and personalize the learning process. In medical education, its potential value is significant because learning outcomes directly impact patient care. Whereas, research in this field remains scattered. Therefore, this scoping review aimed to map existing literature on the use of learning analytics in medical education, focusing on its definitions, applications, benefits, and challenges, to identify evidence gaps and guide future research and practice.
Methods: Following the Arksey and O’Malley scoping review framework and guided by the PRISMA-ScR checklist, a scoping review of publications addressing learning analytics in medical education was conducted. Relevant literature was identified through searches of international databases, including Scopus, PubMed, Web of Science (WOS), and Education Resources Information Center (ERIC). Searches used predefined keywords and were limited to English-language publications published between 2010 and 2024. Eligible studies included empirical and review articles within all academic levels in medical education context. Two reviewers independently screened and charted the data, and results were synthesized thematically across key domains.
Results: Initially, a total of 2,056 articles were identified. During the first screening stage, studies were filtered based on the relevance of their titles and abstracts, resulting in 196 articles advancing to the second phase. After a thorough full-text review, 20 articles that met all inclusion criteria were finally selected for analysis. The extracted findings were categorized into four main themes: definitions, applications and advantages, disadvantages and challenges, and general information on learning analytics.
Conclusion: Learning analytics offers considerable potential to enhance medical education through personalized learning, better decision-making, and improved outcomes for learners and patients. Yet, its adoption remains limited and fragmented, with challenges including ethical concerns, technical barriers, and the lack of standardized frameworks. Future research should develop standardized frameworks, address ethical and technical issues, and evaluate impacts on learner outcomes and patient care. Current evidence may be biased due to publication and language limitations; future research should include non-English sources and larger, more diverse datasets to enhance validity and generalizability.

تازه های تحقیق

Zohreh Sohrabi (Google Scholar)

Zohreh Hosseinzadeh (Google Scholar)

کلیدواژه‌ها
Learning Analytics؛ Medical؛ Education؛ Learning؛ Educational Technology
مراجع
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