Integrating Critical thinking and embracing Artificial Intelligence: Dual Pillars for advancing dental education

Abstract

Among various clinical skills, critical thinking (CT) is foundational for quality patient care. However, existing literature suggests deficiencies in applying analytical reasoning skills in healthcare education. As CT integration gains momentum in dentistry, the rapid advancement of artificial intelligence (AI) technologies introduces new dynamics. This article explores the potential impacts of emerging technologies of AI on the development and application of CT in the dental profession.

Methods

A narrative literature review of English-language publications was conducted using sources such as PubMed, MEDLINE, ScienceDirect, Wiley-Online-Library, and Oral-Health-Group. Our review focused on relevant articles published up to June 30,2024, representing a peak period of CT awareness. The search terms used included: “Critical thinking,” “healthcare,” “rubric,” “dental education,” and “Artificial intelligence.” No inclusion or exclusion criteria were applied. The search strategies aimed to synthesize collective healthcare experience in implementing CT in education, providing a cohesive understanding of the current state of CT and highlighting gaps in its integration in education.

Results

Strategies for incorporating CT into dental education are still developing. Although dental educators recognize the importance of CT-based curricula, barriers hinder effective implementation. Additionally, the rise of advanced technologies with human-like cognitive and non-cognitive capabilities necessitates agile, adaptable strategies to integrate CT in dental education. A simplified model is proposed for integrating AI into the development of CT skills at multiple levels in dental education. Furthermore, a rubric for assessing CT skills in problem-based learning is presented.

Conclusion

This review emphasizes the urgent need to strategically prioritize CT integration in dental education. Inadequate application of CT may increase the risk of AI misuse, and overreliance on AI could potentially undermine clinical decision-making. We propose that emerging technologies should be embraced as tools to enhance the development of CT skills while mitigating potential negative impacts. Plausible approaches to addressing this challenge are outlined.