Evidence map›Paper›PMID 42895785›Full record

ArticleMedical education online2026

Advancing clinical integration in undergraduate dental education through AI-enabled instructional design: a qualitative thematic analysis.

Selçuk Akturan, Ömer Faruk Güdük, İpek Nur Berberoğlu, Elif Özlem Ardıç Kemerkaya, Salman Yousuf Guraya

Abstract read
In one paragraph

Article in Medical education online, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Selçuk AkturanFaculty of Medicine, Department of Medical Education, Karadeniz Technical University, Trabzon, Türkiye.ORCID 0000-0003-4448-8899
Ömer Faruk GüdükDepartment of Pediatric Dentistry, Faculty of Dentistry, Karadeniz Technical University, Trabzon, Turkey.ORCID 0000-0003-0930-4935
İpek Nur BerberoğluDepartment of Pediatric Dentistry, Faculty of Dentistry, Karadeniz Technical University, Trabzon, Turkey.ORCID 0000-0001-7754-9104
Elif Özlem Ardıç KemerkayaDepartment of Educational Sciences, Division of Educational Measurement and Evaluation, Trabzon University, Trabzon, Türkiye.ORCID 0000-0003-2983-2970
Salman Yousuf GurayaGulf Medical University College of Medicine, Ajman, United Arab Emirates.ORCID 0000-0001-5183-023X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite 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.

methodsWe 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.

resultsAI-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.

conclusionThis 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.

Indexed as

Artificial IntelligenceEducation, DentalClinical CompetenceFocus GroupsHumansLearningQualitative ResearchStudents, DentalTeachingArtificial intelligenceclinical integrationcurriculum developmentdental educationoutcome-based education

Identifiers

PMID42895785
PMCPMC13686208

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.