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

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 educ…

By the Truvace desk1 min read1 sourcePeer-reviewedTRV-2026-1929· cite & verify
Advancing clinical integration in undergraduate dental education through AI-enabled instructional design: a qualitative thematic analysis
"09-8018-23" by NavyMedicine is marked with Public Domain Mark 1.0. To view the terms, visit https://creativecommons.org/publicdomain/mark/1.0/.

In brief

Researchers redesigned existing undergraduate dental lessons using AI-supported recommendations meant to align learning objectives, real clinical contexts, and expected clinical outcomes. They then observed classes and held student focus groups, analyzing the data thematically.

The findings suggest AI can help educators plan more clinically grounded teaching, but the benefit appears to come from the pedagogy rather than from AI itself. Because the evidence is qualitative, it describes experiences and themes rather than measured learning or clinical performance gains.

Main points

  1. The study used an inductive qualitative thematic analysis in an undergraduate dental education setting.
  2. Data came from classroom observations and student focus group discussions, triangulated to improve credibility.
  3. Four themes emerged, including a move from teacher-centred delivery to facilitating clinical reasoning.
  4. Students shifted from passive attendance to active cognitive engagement.
  5. AI served as a design-support tool and did not replace educators' instructional role.

The gain

Lessons redesigned with AI-supported recommendations produced more authentic clinical scenarios, reasoning activities, and active student engagement in an undergraduate dental setting.

The rundown

The redesign targeted alignment between learning objectives, authentic clinical contexts, and expected clinical outcomes, using AI-supported recommendations to restructure existing lessons.

Four interconnected themes were identified: facilitation of clinical reasoning, active cognitive engagement, building clinical meaning through authentic contexts and collaborative dialogue, and psychological safety for professional learning.

The authors state the changes arose mainly from learner-centred, clinically oriented pedagogical redesign enabled by AI-supported planning, not from students interacting directly with AI.

Sources

  1. Peer-reviewedMedical Education Online2026-10-19

The debate