Version 1
: Received: 27 December 2023 / Approved: 3 January 2024 / Online: 3 January 2024 (09:56:38 CET)
How to cite:
Vertemati, M.; Zuccotti, G. V.; Porrini, M. Enhancing Anatomy Education Through Flipped Classroom and Adaptive Learning. A Pilot Project on Liver Anatomy. Preprints2024, 2024010218. https://doi.org/10.20944/preprints202401.0218.v1
Vertemati, M.; Zuccotti, G. V.; Porrini, M. Enhancing Anatomy Education Through Flipped Classroom and Adaptive Learning. A Pilot Project on Liver Anatomy. Preprints 2024, 2024010218. https://doi.org/10.20944/preprints202401.0218.v1
Vertemati, M.; Zuccotti, G. V.; Porrini, M. Enhancing Anatomy Education Through Flipped Classroom and Adaptive Learning. A Pilot Project on Liver Anatomy. Preprints2024, 2024010218. https://doi.org/10.20944/preprints202401.0218.v1
APA Style
Vertemati, M., Zuccotti, G. V., & Porrini, M. (2024). Enhancing Anatomy Education Through Flipped Classroom and Adaptive Learning. A Pilot Project on Liver Anatomy. Preprints. https://doi.org/10.20944/preprints202401.0218.v1
Chicago/Turabian Style
Vertemati, M., Gian Vincenzo Zuccotti and Marisa Porrini. 2024 "Enhancing Anatomy Education Through Flipped Classroom and Adaptive Learning. A Pilot Project on Liver Anatomy" Preprints. https://doi.org/10.20944/preprints202401.0218.v1
Abstract
Anatomy education plays a critical role in medical practice, and the level of anatomical knowledge among students and physicians significantly impacts patient care. This article presents a pilot project conducted by the University of Milan aimed at exploring the effectiveness of the Area9's Rhapsode platform, an intelligent tutoring system that uses artificial intelligence to personalize learning and collect data on mastery acquisition. The study focused on liver anatomy and employed a flipped classroom approach, incorporating adaptive learning modules and an interactive in-class session. The project's execution, outcomes and preliminary pedagogical considerations are discussed. The results demonstrated improved learning quality, positive repurposing of study time, enhanced metacognitive awareness among students, with most of students demonstrating conscious mastery of the materials and a clear understanding of their level of competence. This approach, by providing valuable insights into the potential of artificial intelligence-based adaptive learning systems in anatomy education, could address the challenges posed by limited teaching hours, shortage of anatomist and the need for individualized instruction, with recommendations for future research and the expansion of adaptive learning modules to other anatomical districts.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
