ArticleFrontiers in behavioral neuroscience2025
AI-enhanced adaptive testing with cognitive diagnostic feedback and its association with performance in undergraduate surgical education: a pilot study.
Article in Frontiers in behavioral neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Transforming surgical ward rounds: constructivist pedagogy, structured models, and intelligent technologies.Frontiers in medicine · 2026Review
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Authors and funding
3 authors.
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Abstract
Background: Effective feedback in the cognitive domain is essential for surgical education but often limited by resource constraints and traditional assessment formats. Artificial Intelligence (AI) has emerged as a catalyst for innovation, enabling automated feedback, real-time cognitive diagnostics, and scalable item generation, thereby transforming how future surgeons learn and are assessed. Methods: An item bank of 150 multiple-choice questions was developed using AI-assisted item generation and difficulty estimation. A formative Computerized Adaptive Testing (CAT), balanced across three cognitive domains (memory, analysis, and decision) and surgical topics, was delivered via QuizOne Results: Students who voluntarily completed CAT showed higher Progress Test scores, though causality cannot be established due to self-selection bias ( Conclusion: AI-enhanced CAT-Cognitive Diagnostic Modeling (CDM) represents a promising formative approach in undergraduate surgical education, being associated with higher summative performance and providing individualized diagnostic feedback. Refining feedback presentation and enhancing decision-making assessment could further optimize its educational impact.
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