A Mixed-Methods Analysis of the Six Core Competencies and AI Literacy Reflected in Medical Students' Self-Assessment During Small-Group Discussions

Core Competency, Reflective Thinking

Accreditation Council for Graduate Medical Education (ACGME), core competencies, AI literacy

This study aims to examine how the six Accreditation Council for Graduate Medical Education (ACGME) core competencies and AI literacy are reflected in medical students' self-assessment narratives following small-group discussions. A mixed-methods design will be used to analyze approximately 500 de-identified self-assessment reflection reports submitted by fourth-year medical students who completed an integrated pathology and pharmacology small-group discussion course at National Taiwan University during the 2023-2026 academic years.

This study aims to examine how the six Accreditation Council for Graduate Medical Education (ACGME) core competencies and AI literacy are reflected in medical students' self-assessment narratives following small-group discussions. A mixed-methods design will be used to analyze approximately 500 de-identified self-assessment reflection reports submitted by fourth-year medical students who completed an integrated pathology and pharmacology small-group discussion course at National Taiwan University during the 2023-2026 academic years. Reports containing fewer than 300 words or lacking substantive reflection will be excluded. Deductive thematic analysis will be conducted using the six ACGME core competencies-Patient Care, Medical Knowledge, Practice-Based Learning and Improvement, Interpersonal and Communication Skills, Professionalism, and Systems-Based Practice-as an a priori coding framework. Open coding will be applied to identify emerging themes not adequately captured by this framework, including AI use and literacy, professional identity formation, faculty facilitation, and self-directed learning strategies. Two researchers will independently code all reports using a predefined codebook, and inter-rater reliability will be assessed using Cohen's kappa. Quantitative content analysis will examine the frequencies, proportions, co-occurrence patterns, and academic-year differences in competencies and emerging themes. Qualitative and quantitative findings will subsequently be integrated through joint displays.

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Taiwan