Work

Exploring the role of AI in dental education: a mixed-method experimental study from Pakistan

Year: 2026

Type: article

Abstract: BACKGROUND: Case-based learning (CBL) is a cornerstone of dental education, fostering critical thinking and clinical reasoning. In Pakistan, challenges like low facilitator-to-student ratios and faculty shortages hinder CBL effectiveness. Artificial intelligence (AI) offers potential solutions through scalable, structured facilitation, yet its role in dental CBL remains underexplored. OBJECTIVE: The objective of this study was to evaluate the effectiveness and acceptability of artificial intelligence (AI) as a facilitator in case-based learning (CBL) for dental education. It aimed to compare learning outcomes between AI- and human-facilitated sessions using a randomized crossover design, and to explore students’ perceptions and experiences of AI-mediated learning through focus group discussions. METHODOLOGY: A sequential mixed-methods design (QUAN → QUAL) was employed with 16 final-year BDS students in a randomized two-period crossover trial. Phase 1 compared AI-facilitated (via ChatGPT-3.5) and human-facilitated CBL using pre- and post-test MCQs, analyzed with Wilcoxon signed-rank and Mann-Whitney U tests. Phase 2 explored student experiences through focus group discussions (FGDs), analyzed thematically using Braun and Clarke’s framework. Ethical approvals were obtained (ERC #2023-6789-12345, IRB-789/LCMD/2023). RESULTS: Both AI- and human-facilitated groups showed significant post-test score improvements (p < 0.012), with no significant inter-group differences (p ≥ 0.130). AI excelled in factual recall and structured feedback, while human facilitation enhanced emotional engagement and clinical reasoning. FGDs revealed themes of AI’s consistency but limited emotional depth, with students favoring a hybrid model. CONCLUSION: AI-facilitated CBL yields comparable academic outcomes to human facilitation, offering scalability in resource-limited settings. However, human facilitators remain vital for emotional and adaptive learning. A blended approach, integrating AI’s structure with human mentorship, is recommended for optimal dental education.

Source: BMC Medical Education

DOI: 10.1186/s12909-026-08728-4

Authors: Tahera Ayub, Muhammad Shahid Shamim, Rahila Ali, Syed Shirjeel Husain

Institution: Aga Khan University

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDGs: Quality education, Good health and well-being

Open Access status: gold

Estimated APC paid: $2,990