This study aims to evaluate the role of AI as an educational tool from an ethical and pedagogical perspective as it delves into the perceptions of the teaching community whose resistance to technology integration into conventionally managed classrooms has been well established in a large number of studies. The study uses a mixed methods design to gather data from 50 English, Translation, and Linguistics faculty members at Ha'il University whose collective and individual views on the ethical and pedagogical issues are analyzed using a questionnaire and individual interviews. Results indicate an overall high perception (M = 3.49, Std = 0.808) among the teachers towards the ethical use of AI in their teaching experience and (M = 3.84, Std = 0.833), on the pedagogical implications of AI in the learning process. Findings also indicate that educators are aware of solutions to ensure maintenance of ethics with inclusion of AI in teaching, including training students on the use of AI, regulating the learning environment, using AI-based plagiarism detector and reformulating the assessment systems. They also report pedagogical considerations that help in the integration of AI tools in the EFL classroom. The study concludes with recommending that both EFL instructors and students be aware about the ways and need to ensure safer use of AI in the learning process.
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http://dx.doi.org/10.1016/j.actpsy.2024.104605 | DOI Listing |
Med Teach
January 2025
Department of Medical Education, Dartmouth College Geisel School of Medicine at Dartmouth, Hanover, NH, USA.
Health Professions Education (HPE) assessment is being increasingly impacted by Artificial Intelligence (AI), and institutions, educators, and learners are grappling with AI's ever-evolving complexities, dangers, and potential. This AMEE Guide aims to assist all HPE stakeholders by helping them navigate the assessment uncertainty before them. Although the impetus is AI, the Guide grounds its path in pedagogical theory, considers the range of human responses, and then deals with assessment types, challenges, AI roles as tutor and learner, and required competencies.
View Article and Find Full Text PDFBMC Med Educ
January 2025
Visual Thinking Strategies and an Independent Writer and Educator, Baltimore, MD, USA.
Background: Visual Thinking Strategies (VTS) is an evidence-based pedagogical approach that uses art analysis and structured inquiry to enhance observation, critical thinking, and teamwork, especially in medical training for clinical skills development. This study aimed to compare the short-term and delayed follow-up effects of integrating Visual Thinking Strategies and Visual Thinking Activity (VTA) tasks based on the PRISM Model with Observation Exercises (OE) on medical students' observation skills, including the number of observations, number of words used, and time spent describing observations.
Method: This pre- and post-test experimental study with a control group was conducted among first-year medical students at Gonabad University of Medical Sciences during the 2023-2024 academic year.
Environ Sci Pollut Res Int
January 2025
Department of Environmental Health, Health Promotion Research Center, Zahedan University of Medical Sciences, Zahedan, Iran.
BMC Geriatr
January 2025
Department of Ophthalmology, LKS Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong.
Background: The prevalence of age-related eye disorders is increasing with the aging of the global population. Community-based visual health education for the elderly has become a crucial intervention. With the advancement of technology, the application of extended reality (XR), such as virtual reality (VR) and augmented reality (AR), in health education has become more popular.
View Article and Find Full Text PDFAdv Physiol Educ
January 2025
Assistant Professor, Department of Physiology, All India Institute of Medical Sciences, Deoghar, Jharkhand - 814152, India.
The integration of large language models (LLMs) in medical education offers both opportunities and challenges. While these AI-driven tools can enhance access to information and support critical thinking, they also pose risks like potential overreliance and ethical concerns. To ensure ethical use, students and instructors must recognize the limitations of LLMs, maintain academic integrity, handle data cautiously, and instructors should prioritize content quality over AI detection methods.
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