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Advancing clinical integration in undergraduate dental education through AI-enabled instructional design: a
Selçuk Akturan1, Ömer Faruk Güdük2, İpek Nur Berberoğlu2
1Faculty of Medicine, Department of Medical Education, Karadeniz Technical University, Trabzon, Türkiye.
Background:
Despite growing interest in artificial intelligence (AI) in health professions education, qualitative evidence for integarting AI-supported instructional redesign on teaching practices and students' experiences in undergraduate dental education remains limited. The aim of this study was to explore the educational impact of AI-supported instructional redesign of lessons in undergraduate dental education.
Methods:
We conducted this inductive qualitative thematic analysis in an undergraduate dental education setting. Existing lessons were redesigned using AI-supported recommendations to strengthen alignment between learning objectives, authentic clinical contexts, and expected clinical outcomes. Data were collected through classroom observations and students' focus group discussions. An inductive thematic analysis was performed, and findings from multiple data sources were curated, collecetd, and triangulated to enhance credibility.
Results:
AI-supported instructional redesign transformed teaching by promoting authentic clinical scenarios, clinically oriented discussions, and explicit reasoning activities. Thematic analysis identified four interconnected themes: (1) a shift from teacher-centred knowledge delivery to facilitation of clinical reasoning; (2) transformation from passive attendance to active cognitive engagement; (3) building clinical meaning through authentic clinical contexts and collaborative dialogue; and (4) creating conditions for professional learning through psychological safety. AI functioned as a pedagogical design-support tool rather than replacing the educators' instructional role. Overall, the observed educational changes appeared to arise primarily from the pedagogical redesign enabled by AI-supported planning rather than from students' direct interaction with AI.
Conclusion:
This study endorses the role of AI-supported instructional redesign in enriching the existing undergraduate dental curriculum. This approach can potentially help educators align learning objectives, instructional strategies, and authentic clinical contexts. The reported educational modifications reflect primarily the implementation of learner-centred and clinically oriented pedagogical strategies, with AI functioning as a design-support mechanism rather than as a direct instructional agent.