Digital intelligence in dental technology education: curriculum and practical teaching reform

Abstract

Oral healthcare is rapidly progressing from basic digitalization toward increasingly AI-enabled and data-driven practice, reshaping the competencies required of dental technology professionals and challenging traditionally technician-oriented educational models. This narrative review examines how digital intelligence can support curriculum development and practical teaching reform in dental technology education, with particular attention to application-oriented undergraduate universities. Drawing on representative literature related to digital workflows, virtual simulation, haptic systems, three-dimensional printing, large language models, generative artificial intelligence (AI), blended learning, and interprofessional and industry–education collaboration, this review critically synthesizes current evidence and proposes a literature-informed integrative conceptual framework for competency-based curriculum planning. Available evidence suggests that digital intelligence may broaden educational objectives beyond manual technical skills to include digital design, data interpretation, intelligent decision support, ethical awareness, and interdisciplinary communication. These technologies may also support a transition from conventional repetitive training toward more progressive combinations of virtual simulation, physical operation, chairside observation, project-based learning, and workplace-oriented internship. However, important controversies and challenges remain. Artificial intelligence and virtual simulation should remain supervised complements rather than replacements for teachers, conventional laboratory training, or clinical experience. AI-generated outputs may be affected by hallucination, algorithmic bias, limited explainability and reproducibility, and student overdependence, thereby requiring faculty validation, human oversight, and clear governance under evolving regulatory conditions. Current research gaps include limited dental technology-specific evidence, insufficient long-term evaluation of competency development and workplace transferability, and persistent barriers related to equipment investment, software access, faculty training, and curriculum alignment. Future reform should therefore move from tool-centered adoption toward competency-centered curriculum reconstruction, emphasizing progressive virtual–physical–clinical integration, personalized assessment, faculty development, medicine–engineering collaboration, and sustainable industry–education synergy. Overall, digital intelligence-driven reform may help align dental technology education with changing practice needs; however, its sustained educational benefits remain uncertain because current evidence is derived mainly from pilot studies, cross-sectional surveys, short-term simulations, and review-based synthesis.