Medical Science Educator, Год журнала: 2024, Номер unknown
Опубликована: Дек. 27, 2024
Язык: Английский
BMC Medical Education, Год журнала: 2025, Номер 25(1)
Опубликована: Янв. 27, 2025
Язык: Английский
Процитировано
4
Medical Teacher, Год журнала: 2025, Номер unknown, С. 1 - 15
Опубликована: Янв. 9, 2025
Health Professions Education (HPE) assessment is being increasingly impacted by Artificial Intelligence (AI), and institutions, educators, learners are grappling with AI's ever-evolving complexities, dangers, potential. This AMEE Guide aims to assist all HPE stakeholders helping them navigate the uncertainty before them. Although impetus AI, grounds its path in pedagogical theory, considers range of human responses, then deals types, challenges, AI roles as tutor learner, required competencies. It discusses difficult ethical issues, ending considerations for faculty development technicalities acknowledgment assessment. Through this Guide, we aim allay fears face change demonstrate possibilities that will allow educators harness full potential
Язык: Английский
Процитировано
1
Medical Teacher, Год журнала: 2025, Номер unknown, С. 1 - 10
Опубликована: Янв. 31, 2025
As artificial intelligence (AI) increasingly influences the healthcare landscape, integrating medical humanities into health professions education becomes essential for cultivating critical thinking and empathetic patient care. Visual Thinking Strategies (VTS), a framework open discussions about visual art, emerges as valuable pedagogical approach within this context. This guide presents comprehensive overview of VTS, including its theoretical foundations practical implementation. It offers insights performing needs assessment, facilitator training session structure, designing running VTS sessions, well methods evaluating program effectiveness. By elucidating these elements, aims to assist educators in successfully incorporating their curricula, enhancing both educational experience quality delivery.
Язык: Английский
Процитировано
0
Forum for education studies., Год журнала: 2025, Номер 3(2), С. 2730 - 2730
Опубликована: Апрель 1, 2025
This paper explores the transformative role of artificial intelligence (AI) in medical education, emphasizing its as a pedagogical tool for technology-enhanced learning. highlights AI’s potential to enhance learning process various inquiry-based strategies and support Competency-Based Medical Education (CBME) by generating high-quality assessment items with automated personalized feedback, analyzing data from both human supervisors AI, helping predict future professional behavior current trainees. It also addresses inherent challenges limitations using AI student assessment, calling guidelines ensure valid ethical use. Furthermore, integration into virtual patient (VP) technology offer experiences encounters significantly enhances interactivity realism overcoming conventional VPs. Although incorporating chatbots VPs is promising, further research warranted their generalizability across clinical scenarios. The discusses preferences Generation Z learners suggests conceptual framework on how integrate teaching supporting learning, aligning needs today’s students utilizing adaptive capabilities AI. Overall, this areas education where can play pivotal roles overcome educational offers perspectives developments education. calls advance theory practice tools innovate practices tailored understand long-term impacts AI-driven environments.
Язык: Английский
Процитировано
0
Medical Teacher, Год журнала: 2025, Номер unknown, С. 1 - 11
Опубликована: Фев. 3, 2025
Faculty development in medical education may take different forms and approaches ranging from standalone workshops short courses up to longitudinal programs postgraduate qualifications, such as Certificates, Diplomas, Master's PhD degrees health professions (HPE). Many places offer staff opportunities help people learn how teach professional students more effectively. Yet higher HPE are expected not only enable graduates be better teachers or assessors but also act on a strategic level support institutional directions advance teaching, learning, assessment scholarship HPE. This guide is for who wish develop programmes provide systematic deeper training those that see themselves educators indeed, the leaders of future. The discusses rationale, plans, process implementation evaluation ten phases. Different variables should considered with respect local context, support, readiness expertise, availability resources, alignment plan college/university methods measure impact these PG programs.
Язык: Английский
Процитировано
0
International Medical Education, Год журнала: 2025, Номер 4(2), С. 11 - 11
Опубликована: Апрель 18, 2025
The integration of Generative Artificial Intelligence (GenAI) into health professions education (HPE) is rapidly transforming learning environments, raising questions about its impact on teaching and learning. This mixed methods study explores clinical educators’ undergraduate students’ perceptions attitudes using GenAI tools in HPE at a tertiary hospital Singapore. Using the Technology Acceptance Model (TAM) Unified Theory Use (UTAUT) as theoretical frameworks, we designed administered survey conducted interviews to assess participants’ perceived usefulness, ease use, concerns related adoption. Quantitative data were analyzed for frequencies percentages, while qualitative responses underwent thematic analysis. Results showed that students demonstrated higher adoption rates (68.7%) compared educators (38.5%), with valuable efficiency, research, personalized However, included over-reliance GenAI, diminished critical thinking, ethical implications. Educators emphasized need institutional guidelines training support responsible integration. Our findings suggest holds great potential enhancing education, structured policies oversight are crucial effective use. These insights contribute ongoing discourse HPE.
Язык: Английский
Процитировано
0
Military Medicine, Год журнала: 2024, Номер unknown
Опубликована: Ноя. 28, 2024
ABSTRACT Introduction The rapid advancement and adoption of large language models (LLMs) in various academic domains necessitate an examination their role scholarly works by medical learners. This paper seeks to discern the implications LLM use learners when preparing for publication. While LLMs possess great potential revolutionize writing process, they can detract from learning process used students residents who are still how research, formulate ideas, write cohesive arguments. Materials Methods An environmental scan both traditional evidence-based sources gray literature was performed glean best practices generative AI education. Sources included peer-reviewed journals, open-source websites, previous publications this field ranging 2015 2023. Results We propose several strategies detect involvement: direct inquiry learner, assessing coherence level content contrast learner’s known capabilities, recognizing patterns shallow insight or depth, utilizing plagiarism AI-specific detection tools, monitoring fabricated citations—a pitfall LLMs. Conclusions Although offer efficiencies writing, unchecked jeopardize development essential critical thinking analytical skills Ultimately, mentors primary investigators responsible ensuring advancing appropriately new emerging technology. study provides a foundational framework educators practices.
Язык: Английский
Процитировано
2
Medical Teacher, Год журнала: 2024, Номер unknown, С. 1 - 5
Опубликована: Ноя. 1, 2024
Язык: Английский
Процитировано
1
Medical Science Educator, Год журнала: 2024, Номер 34(6), С. 1641 - 1646
Опубликована: Ноя. 14, 2024
Язык: Английский
Процитировано
0
Medical Teacher, Год журнала: 2024, Номер unknown, С. 1 - 3
Опубликована: Дек. 24, 2024
Язык: Английский
Процитировано
0