Evidence-Based Learning Strategies in Medicine Using Artificial Intelligence

Abstract

Large language models (LLM) like ChatGPT, are transforming the landscape of medical education. They offer a vast range of applications, such as tutoring (personalized learning), patient simulation, generation of exam questions, and streamlined access to information. The rapid advancement of medical knowledge and the need for personalized learning underscore the relevance and timeliness of exploring innovative strategies for integrating artificial intelligence (AI) into medical education. In this paper, we propose coupling evidence-based learning strategies such as active recall and memory cues with AI to optimize learning. These strategies include the generation of tests, mnemonics, and visual cues.