Flipped Learning with Generative Artificial Intelligence

A Narrative Inquiry

Abstract

This study explores the complex process of integrating generative artificial intelligence (GenAI) into a flipped classroom. Employing Clandinin and Connelly’s (2000) narrative inquiry framework, the study collected data from class observations and semi-structured interviews with a lecturer and six English-majored undergraduates before, during, and at the end of a 15-week British Literature course. Bhattacharya’s (2017) inductive analysis model was used to inform the thematic narrative sub-approach. The findings revealed both challenges and benefits associated with using GenAI for flipped learning while highlighting its impact on students’ self-regulated learning and teacher self-efficacy.

This presentation retells stories from the participants’ lived experiences in a GenAI-enabled and flipped classroom. Exemplary learning resources are showcased to demonstrate how GenAI tools can effectively and efficiently facilitate flipped learning. The insights gained from this study contribute to a deeper understanding of the potential of GenAI in transforming educational practices and enhancing the flipped learning experience.