Physicians’ awareness, attitudes, perceived barriers, and adoption of clinical and generative artificial intelligence in Saudi Arabia: a nationwide analytical cross-sectional survey Abdulelah Ibrahim Alrasheed, Amr Jamal, Mohamad-Hani Temsah, Fawzia Abdullah Alkhraiji, Abdulaziz Alhokair, Mohannad Ali Alqarni, Mansour Ibrahim Alrasheed, Omar AlRahbeeni, Mojahed Mohammed Otayf International Journal of Medical Informatics.2026; 222: 106730. CrossRef
Purpose This paper presents findings from an educational research graduate course in which generative artificial intelligence (AI) was incorporated to strengthen learners’ understanding of threshold concepts related to theoretical frameworks. Medical and health professionals often struggle with the transition from a clinical role into the educational research role.
Methods The study posits that the use of generative AI will help learners understand and apply theoretical frameworks beyond a superficial level, furthering their understanding, constructing new knowledge, and strengthening their ability to develop sound educational research studies. Journal and AI transcripts were analyzed for 37 participants.
Results Open-ended codes were grouped into five themes reflecting a developmental progression across phases of threshold crossing: encountering challenge, adapting through iteration, deepening engagement, customizing understanding, and cultivating metacognition. The first two themes represent learners’ entry into the troublesome and liminal phases of threshold crossing, while the latter three reflect integrative and transformative shifts in their understanding and use of theory.
Conclusion Learner perceptions of using generative AI to acquire theoretical framework threshold concepts are discussed to better understand how AI can be used as a supplemental resource in asynchronous learning environments. Faculty observations of learner performance, suggested generative AI teaching strategies, and potential threats, including AI hallucinations and the clarification of misinformation, are discussed.
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The new wave of generative artificial intelligence in medical education Eulho Jung, Anita Samuel Korean Journal of Medical Education.2026; 38(1): 1. CrossRef
Purpose With the accelerated adoption of artificial intelligence (AI) in medicine, the integration of AI education into medical school curricula is gaining significant attention. This study aimed to gather the perceptions of faculty members and students regarding the integration of AI education into medical curricula in the Korean context.
Methods Faculty members and medical students’ perspectives on integrating AI into medical curricula were assessed through thematic analysis of free-written responses from 157 faculty members and 125 students in a national online survey on medical AI competencies in South Korea.
Results Three key themes emerged: content, which prioritizes basic knowledge and its practical applications, with an emphasis on ethical and legal responsibilities; curricular design, which advocates for a spiral curriculum tailored to learners' needs; and concerns, which highlight balancing AI integration with the principal goals of medical education while critically evaluating ongoing advancements.
Conclusion Our study adds valuable insights into the content and methods to prioritize AI education. Given the rapid evolution of medical learners and AI technologies, continuous and timely needs assessment for AI curriculum development is crucial to maintain relevance and effectiveness.
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Artificial Intelligence in Neurology and Stroke Education: Current Applications and Future Directions Braydon Dymm, Abdullah Khalid Seminars in Neurology.2026; 46(01): 049. CrossRef
Not all AI is created equal: considerations for equity in medical education Michael Soh, Nidhi Goel, Violet Kulo Korean Journal of Medical Education.2026; 38(1): 15. CrossRef
Are future doctors ready for AI? Artificial intelligence in the field of medicine: perception among medical students in North Karnataka: a cross-sectional study Shamin Eabenson, M. R. Gudadinni, M. C. Yadavannavar, Rekha Udgiri, A. M. Rangoli International Journal Of Community Medicine And Public Health.2026; 13(3): 1384. CrossRef
Bedside skills as context engineering: reframing history taking and physical examination for the AI era Sanghyun Ahn, Eunbae B. Yang Korean Journal of Medical Education.2026; 38(2): 207. CrossRef
Artificial Intelligence in Nursing Education: A Scoping Review of Academic Perspectives Natasha Hawkins, Anthea Fagan, Yumiko Coffey, Henri Dohnt Journal of Advanced Nursing.2026;[Epub] CrossRef
Development of AI competencies within the medical curriculum María Belén Morales-Cevallos, Diego Fabián Vique López, Catherine Hortensia Martínez Avalos, Brigette Carolina Huaraca Morocho, Jhonatan David Silva Ameza, Marwin Leandro Lavayen Leon Frontiers in Medicine.2026;[Epub] CrossRef
Medical AI Use Intention Among Medical Students and Faculty and Its Associations With AI Literacy, Perceived Benefits, and Risks: Cross-Sectional Survey Study Bomyee Lee, Gwanwook Bang, Su Jin Chae JMIR Medical Education.2026; 12: e105032. CrossRef
Transforming Learning in the Digital Age: Examining the Role of AI for Catholic Religious Education Teachers Hartutik Hartutik, Dani Kusuma, Stepanus Istoto Raharjo, Dewi Ratna Jai, Irene Nindita Pradnya, Matilda Stella Pradnya, Johanis Luturmas Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika.2025; 9(2): 429. CrossRef
Development and evaluation of a Wikipedia based group assessment to enhance science communication Katelyn Mroczek, Pru Mitchell, Brian Patrick McSharry, Alice Woods, Belinda Spry, Timothy Paustian, Thiru Vanniasinkam Frontiers in Education.2025;[Epub] CrossRef
From Bainbridge to bedside: applying automation insights to medical curriculum and assignment design in the artificial intelligence era Sangzin Ahn Korean Journal of Medical Education.2025; 37(4): 519. CrossRef
Purpose The perception of faculty members about an individually tailored, flexible-length, outcomes-based curriculum for undergraduate medical students was studied. Their opinion about the advantages, disadvantages, and challenges was also noted. This study was done to help educational institutions identify academic and social support and resources required to ensure that graduate competencies are not compromised by a flexible education pathway.
Methods The study was done at the International Medical University, Malaysia, and the University of Lahore, Pakistan. Semi-structured interviews were conducted from 1st August 2021 to 17th March 2022. Demographic information was noted. Themes were identified, and a summary of the information under each theme was created.
Results A total of 24 (14 from Malaysia and 10 from Pakistan) faculty participated. Most agreed that undergraduate medical students can progress (at a differential rate) if they attain the required competencies. Among the major advantages mentioned were that students may graduate faster, learn at a pace comfortable to them, and develop an individualized learning pathway. Several logistical challenges must be overcome. Providing assessments on demand will be difficult. Significant regulatory hurdles were anticipated. Artificial intelligence (AI) can play an important role in creating an individualized learning pathway and supporting time-independent progression. The course may be (slightly) cheaper than a traditional one.
Conclusion This study provides a foundation to further develop and strengthen flexible-length competency-based medical education modules. Further studies are required among educators at other medical schools and in other countries. Online learning and AI will play an important role.
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A two-step structural equation modeling and explainable machine learning framework for understanding university students’ adoption of generative AI: balancing intrinsic motivations and perceived risks Daixing Zeng, Xiaoqin Xu, Tianxing Zhu, Yong Li, Qiumin Li Frontiers in Psychology.2026;[Epub] CrossRef
Faculty acceptance and use of generative artificial intelligence in their practice Julián Nevárez Montes, Josemaria Elizondo-Garcia Frontiers in Education.2025;[Epub] CrossRef
Trends and applications of artificial intelligence in competency-based education in medical programs: a scoping review Sang Thanh Do, Cuong Ly To, Quoc Kha Vo Huynh, Duy Thanh Huynh, Song Thi-Thu Nguyen, Phuong Thi – Lan Le MedPharmRes.2025; 9(s1): s89. CrossRef
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