Journal of Advances in Medical Education & Professionalism

Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review

EHSAN TOOFANINEJAD; SHANE DAWSON; SOMAYE SOHRABI; MASOMEH KALANTARION

Volume 13, Issue 1 , January 2025, , Pages 12-24

https://doi.org/10.30476/jamp.2024.103973.2034

Abstract

Introduction: Learning Analytics (LA) has emerged as a potent tool in medical education, offering data-driven insights and personalized support to learners. This systematic review aims ... Read More

Study of Deep Learning in Medical Education: Opportunities, Achievements and Future Challenges

HOSSEIN MORADIMOKHLES; GWO-JEN HWANG; HOSSEIN ZANGENEH; MARYAM POURJAMSHIDI; AMIR HOSSEIN AMOOEIRAZANI

Volume 12, Issue 3 , July 2024, , Pages 148-162

https://doi.org/10.30476/jamp.2024.99740.1853

Abstract

Introduction: In this era of progress, interest has developed regarding advancing deep learning (DL) in medicine. However, there has been reluctance to use deep learning, particularly ... Read More Introduction: In this era of progress, interest has developed regarding advancing deep learning (DL) in medicine. However, there has been reluctance to use deep learning, particularly among medical educators. The limitations of previous research were examined in this study, along with the extent to which DL can be used in medical education and its potential impact on educational quality. We were interested in discussing DL’s prospects, and determining whether we could benefit from it in medical education.Methods: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol was used to manage this review procedure. Six databases were searched carefully to obtain relevant studies. Our search identified 981 articles from the database based on our standards. After filtering the duplicated articles, 11 studies were included in the systematic review.Results: The results showed that DL applications attracted researchers’ attention in the medical and education technology owing to their effectiveness to provide the personalized assistanceand feedback. Furthermore, the majority of research concentrated on teaching medical students how to utilize DL applications in the classroom, and all of them tried to improve medical students’proficiency with DL instruments in practical applications. Deep learning components in medical learning environments have two segments—in the educational settings like speech recognitionor Video content analysis for affecting students’ learning, and in the medical settings, applying deep learning from diagnosis to prevention. An integration of them can work better in medicaleducation.Conclusion: Medical education uses DL to improve the students’ education. DL is a powerful instrument which has become more famous in terms of superb outcomes. Besides, using DL in medical education is likely to continue as a hotly debated area of research and a well-known classroom strategy.

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Keywords = Data mining

Exploring the Transformative Potential of Learning Analytics in Medical Education: A Systematic Review

Abstract

Study of Deep Learning in Medical Education: Opportunities, Achievements and Future Challenges

Abstract