| dc.creator | Buagrara, Aiman A. | |
| dc.date.accessioned | 2026-07-13T08:28:28Z | |
| dc.date.available | 2026-07-13T08:28:28Z | |
| dc.date.issued | 2026-05-25 | |
| dc.identifier.issn | 2978-0489 | |
| dc.identifier.other | 10.63720/v2i1003 | |
| dc.identifier.uri | https://doi.org/10.63720/v2i1003 | |
| dc.identifier.uri | http://dr.limu.edu.ly/handle/123456789/5245 | |
| dc.description.abstract | Medical education is being reshaped by two major technological disruptions: the rapid expansion of online learning since the COVID-19 pandemic and the equally rapid adoption of artificial intelligence (AI) in teaching, assessment, and clinical training. These developments are often treated as distinct phases of change. In reality, they are part of the same broader challenge: educational institutions have repeatedly adopted new technologies faster than they have developed the pedagogic, ethical, and regulatory frameworks needed to use them well.1-3 | |
| dc.format.extent | pp. 5-6 | |
| dc.language.iso | en | |
| dc.publisher | Open Science Press | |
| dc.relation.ispartofseries | Journal of the Best Available Evidence in Medicine;Vol. 2, No. 1 | |
| dc.rights | © 2026 Open Science Press. All rights reserved. | |
| dc.source | Journal of the Best Available Evidence in Medicine | |
| dc.subject | Online learning | |
| dc.subject | medical education | |
| dc.subject | COVID-19 pandemic adaptation | |
| dc.subject | Artificial intelligence | |
| dc.subject | Generative AI risks | |
| dc.subject | AI literacy | |
| dc.subject | educational governance | |
| dc.title | Online Learning in Medical Education Post-COVID-19 and in the Era of Artificial Intelligence: Lessons Still Being Learned | |
| dc.type | Editorials | |