Enhancing medical education support with artificial intelligence : a qualitative case study.

Abstract

Medical educators are overburdened with administrative responsibilities. The educator shortage is affecting every aspect of academia. The teacher-student relationship needs attention to assure technology does not create isolated learning environments. Artificial intelligence (AI) can be the solution to many of these issues. Educators need an opportunity to understand what AI supported technology is available to them and how it can help them manage their workload and offer quality instruction. This problem of practice used a descriptive qualitative case study. The unified theory of acceptance and use of technology (UTAUT) served as the framework for this case study. Ten medical educators were interviewed to gain an understanding of what knowledge faculty have of AI supported tasks and if they use them. The UTAUT determinants and facilitating conditions guided the development of the research questions. The determinants influence intent to use new technology. They include performance expectancy, effort expectancy and social influence. The facilitating conditions influence direct use based upon the institution’s infrastructure and technical knowledge. The key findings from this study include ease of use, ability to collaborate with peers and most importantly, the institution’s ability to support the new technology’s infrastructure. The ease of use or amount of possible downtime associated with integration was addressed. The faculty were very collaborative and want to be sure peers can access the new technology. Finally, the infrastructure to support long-term use of new technology must be in place prior to their consideration of the new technology. There are several important implications from these findings. AI-driven technology can alleviate some laborious workloads. If offered with leadership support and the institutional infrastructure in place to support it, AI can complement the learning process. In addition, as administrative burdens minimize and educators are more willing to take on additional educator roles, AI can indirectly address the educator shortage.

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