Exploring Faculty Preparedness for Artificial Intelligence-Driven Dental Education: A Multicentre Study.

Abstract

Introduction In the modern era, technology, including artificial intelligence (AI), is the centre of digital innovation. AI is revolutionising numerous fields, including the healthcare sector, globally. Incorporating AI in dental education may help in improving the diagnostic accuracy, learners' experiences, and effectiveness of the management of dental education institutions. However, successful implementation of AI requires the faculty's willingness to incorporate it into their practices. Thus, this research aims to explore the readiness of faculty members to integrate AI into dental education. Methodology The study employed a qualitative exploratory design to gather in-depth insights into faculty readiness for AI-driven dental education. Purposive sampling was employed, and 21 faculty members from public and private dental colleges in South Punjab participated in semi-structured interviews. The interviews focused on understanding participants' perceptions, experiences, and challenges related to AI integration in dental education. Thematic analysis was conducted utilising Braun and Clarke's framework to identify key themes and subthemes from the qualitative data using inductive coding. Results Five major themes and 14 subthemes emerged from the data analysis. Faculty members had low AI literacy coupled with diverse perceptions; some participants perceived AI as a solution for revolutionising teaching and learning, while others criticised its misuse as academic misconduct by students, an effect on students' critical thinking, and a threat to conventional jobs. However, most of the respondents also considered AI beneficial for students with remote access or from marginalised populations in terms of accessing and learning from limited resources. Concerns that participants highlighted included a lack of training opportunities, limited facilities, ethical concerns pertaining to data privacy, and assessment bias. Some of the recommendations provided by the respondents include the provision of training opportunities, the allocation of resources and infrastructure, and continuous effective support from institutions for the integration of AI in dental education. Conclusions This study emphasised the readiness of the faculty when it comes to the integration of AI in dental education. The faculty considered AI favourable for digitization and innovative education, although there is a lack of awareness of its application. Regarding the benefits of utilising AI, respondents highlighted its quick response, prediction of students' performance, and flexibility in learning. The challenges included lack of awareness regarding its implementation, inadequate training, lack of availability of resources, lack of institutional support, the problem of data confidentiality, and resistance to change. Suggestions included the provision of technical support, skills training, and the provision of required infrastructure. Participants recommended that AI tools must incorporate cultural and contextually specific content, use technical support for problems, and incorporate constant response systems to improve the AI tools for novice users, especially within developing regions such as Pakistan.