Jul 2026· MENTOR revista de investigación educativa y deportiva· Vol 5, pp. 249-259· 0 citations· 6 references
TL;DR
It was concluded that the integration of AI into the training of health professionals requires a deliberate pedagogical approach, the strengthening of faculty digital competencies, and specific institutional ethical frameworks.
Abstract
Artificial intelligence (AI) poses pedagogical challenges of particular relevance in the training of health professionals. The objective of this research was to explore the perceptions of university faculty in the health sciences regarding the challenges and opportunities of AI in teaching-learning processes in Ecuadorian universities. The study used a qualitative approach with an interpretive phenomenological design. Semi-structured interviews were conducted with 15 faculty members from health-related programs at four universities in Ecuador between February and April 2026. The analysis was carried out through thematic coding using Atlas.ti 23. Four categories emerged: (1) opportunities of AI in clinical teaching; (2) ethical and epistemological tensions; (3) gaps in faculty continuing education; and (4) proposals for curricular integration. Participants acknowledged the potential of AI to personalize learning and support diagnostic reasoning, but expressed concerns about technological dependence and the privacy of clinical data. It was concluded that the integration of AI into the training of health professionals requires a deliberate pedagogical approach, the strengthening of faculty digital competencies, and specific institutional ethical frameworks.
It is crucial to consider educators' perceptions and the potential outcomes when using AI in health sciences education, and addressing ethical concerns and providing appropriate training are crucial for ensuring successful and equitable AI integration in the curriculum.
N. Hachoumi, Mohamed Eddabbah, A. E. El Adib· Health Sciences Investigatio...· 0 citations
Artificial intelligence (AI), treated in this study as an umbrella term for AI-enabled clinical and educational technologies rather than as a single platform, is reshaping medical education, including how diagnostic skills, treatment planning, and patient care are taught. This study examines AI integration in medical education through the perceptions and readiness of clinical educators. Guided by the Unified Theory of Acceptance and Use of Technology, the study explores factors influencing AI adoption in medical training, including performance expectancy, effort expectancy, social influence, and facilitating conditions. In this exploratory study, semi-structured interviews were conducted with 15 clinical educators in the south-central United States who supervise third-year medical students. Findings suggested six recurring themes: the technological learning curve, the need for hands-on learning, institutional support, mentorship, preservation of human elements, and generational differences in comfort with AI. While some AI-enabled applications may support adaptive and personalized learning, educators expressed concerns about maintaining empathy, patient interaction, and human-centered care. The findings suggest that effective AI integration may require strategic institutional support, ongoing training, and pedagogical change. This study provides insight into developing AI-ready medical education models that balance technical competence with humanistic values.
T. Murphy, Ginger Vaughn, Rob E. Carpenter et al.· International Medical Educat...· 0 citations
Background: The emergence of generative artificial intelligence (AI), particularly with platforms like OpenAI, has brought about a paradigm shift in problem-solving and decision-making approaches. One sector that has notably embraced AI is education, where its integration has revolutionized traditional teaching and learning methods. While prior reports have highlighted the opportunities AI presents in education, they also emphasize the associated risks. Despite these concerns, proponents argue that incorporating AI into education could potentially better prepare students for evolving industry demands.
Objective: The objective of this study is to explore the perceptions of faculty and students at the University of [blinded] regarding AI usage in education.
Methods: The study, approved by the [blinded] Institutional Review Board, employed a mixed-methods design. Quantitative data were collected through a cross-sectional survey distributed to faculty and students. The survey included questions on demographics and perceptions of AI in education. Participants were also given the option to express interest in follow-up interviews. Interviews were conducted with willing participants to further explore their views on AI in education.
Results: The quantitative data revealed that the majority of the faculty and students were aware of and somewhat familiar with AI tools. They generally perceived AI as a beneficial addition to education. However, concerns about AI included potential dependency and the ethical implications of AI-generated content. The follow-up interviews provided deeper insights, with participants expressing optimism about AI's potential to transform education while emphasizing the need for robust ethical guidelines and training to maximize its benefits.
Conclusion: The findings suggest a positive perception of AI among both faculty and students at [blinded], highlighting its potential to enhance personalized learning and better prepare students for future industry demands. However, there is a clear need for comprehensive ethical guidelines and training to address concerns about dependency and the ethical use of AI. The study emphasizes the importance of balancing the benefits of AI with the associated risks to ensure its effective and responsible integration into educational practices. Continued research and dialogue are essential to navigate the evolving landscape of AI in education, ultimately aiming to enhance the learning experience and outcomes for students in healthcare education.
Keywords: Artificial intelligence, perceptions, education, survey, interview
X. Gordy· The Journal of Scholarship o...· 0 citations
: This qualitative study explores the knowledge, perceptions, and preparedness of health informatics students at the University of Hail regarding artificial intelligence (AI) in healthcare. Through semi-structured interviews with 15 undergraduate students, the research identifies widespread familiarity and generally positive attitudes toward AI tools such as ChatGPT and Google Gemini. Participants recognize AI as a supportive technology that enhances decision-making and precision medicine while emphasizing the continued importance of human oversight. Despite readiness to engage with AI, significant gaps exist in curriculum design, particularly the lack of practical, simulation-based training and ethical education. The study highlights challenges, including limited specialized courses, technical barriers, and ethical concerns, and presents student-driven recommendations for curriculum reform focused on experiential learning and tiered competency development. These findings contribute empirical evidence to the limited literature on AI preparedness in health informatics education and underscore the need for targeted educational reforms to equip future professionals to integrate AI responsibly and effectively in healthcare.
Muneef Alshammari· Proceedings of the Internati...· 0 citations
OBJECTIVE
Aim: To analyze key aspects of the application of AI as a clinical mentor in telemedicine-based medical education, and to assess the related opportunities, challenges, and attitudes of pediatric students.
PATIENTS AND METHODS
Materials and Methods: A cross-sectional study was conducted to assess the level of digital competence of future pediatricians regarding telemedicine and AI. A total of 251 students from the Faculty of Pediatrics at Bogomolets National Medical University (BNMU) participated in the survey. Participants were aged 17 to 26 years, of whom 17.9% were male and 82.1% were female. The questionnaire included items on demographic characteristics, knowledge and use of telemedicine and AI tools, self-assessment of digital competence, and attitudes toward the integration of AI in healthcare. Data were analyzed using descriptive statistics and presented as relative frequencies (%).
RESULTS
Results: The study assessed digital competence and the use of AI among 251 future pediatricians regarding telemedicine-based medical education. Survey results indicated active engagement with AI tools in educational and professional tasks (63.7% positive responses), moderate confidence in integrated digital devices (55.0%), and cautious self-assessment of clinical decision support systems (53.4%). These findings informed the development and revision of courses at BNMU, enhancing students' practical skills and digital competence.
CONCLUSION
Conclusions: Future pediatricians actively engage with digital tools and AI, although confidence is higher in AI tasks than in integrated devices or clinical decision systems. The findings guided the development of updated courses to strengthen digital competence, practical skills, and critical evaluation of AI. Successful telemedicine implementation requires addressing data security, regulation, human-centred care, and digital inclusion to ensure safe, effective, and equitable healthcare.
Inna I. Kucherenko, Oxana Vygovska, Vadym G Terentyuk et al.· Wiadomosci lekarskie· 0 citations
Although baseline knowledge of AI among medical students and faculty members was limited, both groups demonstrated strong positive attitudes and a clear demand for further training, highlighting the importance of integrating structured AI education into medical curricula to support the responsible and effective use of emerging technologies.
Ay Sıla Çaloğlu, Halid Durna, Zeynep Naz Ergen et al.· Journal of Medical Education...· 0 citations