Technology-enhanced learning in medical education in the age of artificial intelligence

Forum for education studies., Journal Year: 2025, Volume and Issue: 3(2), P. 2730 - 2730

Published: April 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.

Language: Английский

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A Comparative Bicentric Study on Ultrasound Education for Students: App- and AI-Supported Learning Versus Traditional Hands-on Instruction (AI-Teach Study)

Academic Radiology, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

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The feasibility of using generative artificial intelligence for history taking in virtual patients

BMC Research Notes, Journal Year: 2025, Volume and Issue: 18(1)

Published: Feb. 24, 2025

This study aimed to design and develop a virtual patient program using generative Artificial Intelligence (AI) technology, providing medical students opportunities practice history-taking with chatbot. We evaluated the feasibility of this approach by analyzing quality responses generated Five expert reviewers participated in pilot test, interacting chatbot take history presenting urinary problem Korean AI platform Naver HyperCLOVA X®. They five-item questionnaire rated on five-point Likert scale. The 96 pairs questions answers, totaling 1,325 words 177 sentences. Discourse analysis scripts revealed that 2.6% (34) were deemed implausible categorized into inarticulate hallucinations, missing important information. Participants answers as relevant (M = 4.50 ± 0.32), valid 4.20 0.40), accurate 4.10 0.20), succinct 3.80 0.51), but neutral about their fluency 3.20 0.60). Using for patients is feasible, improvements are needed more articulate natural responses.

Language: Английский

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Advanced Prompt Engineering in Emergency Medicine and Anesthesia: Enhancing Simulation-Based e-Learning

Electronics, Journal Year: 2025, Volume and Issue: 14(5), P. 1028 - 1028

Published: March 5, 2025

Medical education is rapidly evolving with the integration of artificial intelligence (AI), particularly through application generative AI to create dynamic learning environments. This paper examines transformative role prompt engineering in enhancing simulation-based emergency medicine. By enabling generation realistic, context-specific clinical case scenarios, fosters critical thinking and decision-making skills among medical trainees. To guide systematic implementation, we introduce PROMPT+ Framework, a structured methodology for designing, evaluating, refining prompts AI-driven simulations, while incorporating essential ethical considerations. Furthermore, emphasize importance developing specialized models tailored regional guidelines, standard operating procedures, educational contexts ensure relevance alignment current standards practices. The framework aims provide approach engaging AI-generated content, allowing learners reflect on reasoning, critically assess recommendations, consider potential tools training workflows. Additionally, acknowledge certain challenges associated use education, such as maintaining reliability addressing biases outputs. Our study explores how simulations could contribute scalability adaptability potentially offering methods healthcare professionals engage contexts.

Language: Английский

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Exploring the perceptions and experiences of pharmacy students about formative and summative OSCE incorporating AI in preparatory process: A mixed-methods study

Currents in Pharmacy Teaching and Learning, Journal Year: 2025, Volume and Issue: 17(6), P. 102348 - 102348

Published: April 4, 2025

Language: Английский

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