AIMC Topic: Curriculum

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Artificial intelligence-based chatbots improve the efficiency of course orientation among medical students: a cross-sectional study.

BMC medical education
BACKGROUND: Large language models (LLMs) like ChatGPT offer new ways to improve academic and administrative workflows in medical education, particularly for students studying in a language that is not their native tongue. We set out to examine whethe...

Large language models as educational collaborators: developing non-conventional teaching aids in pharmacology & therapeutics.

BMC medical education
BACKGROUND: With the growing integration of artificial intelligence in medical education, this study compares the quality and educational robustness of content generated by two large language models (LLMs), DeepSeek-V3 and ChatGPT 4.0, on the emergin...

Understanding how medical students learn in the era of artificial intelligence: a mixed methods study.

BMC medical education
BACKGROUND: As medical education evolves, current teaching practices often remain misaligned with how today's digitally native students prefer to learn. While the use of digital tools is widespread, there is limited clarity on students' learning beha...

Trends analysis and future study of medical and pharmacy education: a scoping review.

BMC medical education
BACKGROUND: This scoping review aims to provide a comprehensive analysis of emerging trends and future developments in medical and pharmacy education, addressing the need to adapt educational approaches to the rapidly evolving healthcare landscape.

Have to Shake It Up: STEM Education Feeling the Heat from Artificial Intelligence.

Chimia
General-purpose AI already correctly solves most traditional assessment problems in first-year STEM education, and it continues to become more proficient with every release. This quiet superheating of familiar practices by increasing AI capabilities ...

Extended Directed Fuzzy Social Network Analysis: A framework and application to curriculum networks in Chinese vocational education.

PloS one
Due to the differences in node types and the diversity of network relationships, Fuzzy Social Network Analysis (FSNA) needs to specifically address the issues of network heterogeneity and relationship ambiguity. To address this challenge, we propose ...

AI Virtual Human-Augmented Game-Based Teaching to Enhance Emotional Intelligence in Nursing Students: Protocol for a Single-Group Pretest-Posttest Action Research Study.

JMIR research protocols
BACKGROUND: The rapid advancement of IT and the complexity of health care demand innovative nursing education that moves beyond lectures and workshops. Nursing students must acquire clinical knowledge alongside emotional intelligence (EI), empathic c...

AI's Accuracy in Extracting Learning Experiences From Clinical Practice Logs: Observational Study.

JMIR medical education
BACKGROUND: Improving the quality of education in clinical settings requires an understanding of learners' experiences and learning processes. However, this is a significant burden on learners and educators. If learners' learning records could be aut...

Determinants of student adoption of artificial intelligence applications in higher education.

Scientific reports
The integration of artificial intelligence (AI) into educational settings has the potential to transform learning experiences; however, its adoption among students remains impacted by various factors. The current study assesses the determinant factor...

Preparing future-ready public health professionals: a blended, AI-integrated pedagogical innovation.

BMC medical education
INTRODUCTION: In the evolving landscape of higher education, especially in public health, innovative pedagogical approaches are essential to promote deeper learning and real-world readiness. This study explored a blended, mixed-method teaching interv...