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Abstract. The objective of this study was to conduct a critical analysis regarding the efficacy of implementing interactive simulators and artificial intelligence (AI) systems into the training process of prospective dental practitioners, based on current data spanning 2020–2025. Research corroborates that VR/AR systems equipped with haptic feedback (e.g., Simodont, Unidental) provide effective simulation of tactile sensations when interacting with enamel, dentin, and pulp. The utilization of VR simulators during the preclinical stage facilitates superior development of manual skills and preparation precision compared to traditional phantom- based methods. Furthermore, the integration of AI enables the automation of student work assessment with an accuracy range of 96–98%. Machine learning algorithms, specifically Random Forest and SVM, demonstrate high performance (90% accuracy) in the differential diagnosis of orofacial pain and trigeminal neuralgia. Specialized platforms, such as AnesthesiaSim, allow for the safe practice of conduction anesthesia skills within a virtual environment featuring “transparent tissue” visualization to prevent trauma to nerve trunks. The primary impediments include the substantial cost of equipment, ethical concerns regarding data privacy, and a degree of skepticism among faculty members concerning the perceived diminution of the educator’s role in the instructional process. Conclusions: The optimal pedagogical approach is a hybrid model that synthesizes VR simulators with traditional methodologies. Simulation technologies and AI are currently becoming indispensable components of modern dental education, ensuring the preparation of competent and confident professionals.
Lychko et al. (Thu,) studied this question.