Crossing the theory threshold: the pedagogical potential of generative artificial intelligence in educational research

PURPOSE: This paper presents findings from an educational research graduate course in which generative artificial intelligence (AI) was incorporated to strengthen learners' understanding of threshold concepts related to theoretical frameworks. Medical and health professionals often struggle with the transition from a clinical role into the educational research role. METHODS: The study posits that the use of generative AI will help learners understand and apply theoretical frameworks beyond a superficial level, furthering their understanding, constructing new knowledge, and strengthening their ability to develop sound educational research studies. Journal and AI transcripts were analyzed for 37 participants. RESULTS: Open-ended codes were grouped into five themes reflecting a developmental progression across phases of threshold crossing: encountering challenge, adapting through iteration, deepening engagement, customizing understanding, and cultivating metacognition. The first two themes represent learners' entry into the troublesome and liminal phases of threshold crossing, while the latter three reflect integrative and transformative shifts in their understanding and use of theory. CONCLUSION: Learner perceptions of using generative AI to acquire theoretical framework threshold concepts are discussed to better understand how AI can be used as a supplemental resource in asynchronous learning environments. Faculty observations of learner performance, suggested generative AI teaching strategies, and potential threats, including AI hallucinations and the clarification of misinformation, are discussed.