Using Multiple GenAI Tools in Pronunciation Teaching: An AI-Assisted Teaching Flowchart in Blended Learning and Flipped Learning

Ka Long Roy Chan, Marymount University, Hong Kong University of Science and Technology

Jinyu Liu, Hong Kong University of Science and Technology

https://doi.org/10.9743/JEO.2025.22.3.6

Abstract: This brief article explores the integration of Generative Artificial Intelligence (GenAI) tools into blended learning environments for designing and teaching pronunciation tasks. Adapting Calamlam’s (2016) conceptual framework, a flowchart is proposed to guide the use of three GenAI tool types to enhance pronunciation instruction: Listen-Mimic Type, Analyze-Feedback Type, and Practice-Feedback Type. The framework facilitates effective use of both synchronous and asynchronous learning opportunities. While this study offers a theoretical overview, it highlights the potential for broader application across various language skills. Future research is necessary to evaluate the effectiveness of these tools and their role in the evolving educational landscape.

Keywords: GenAI, blended learning, flipped classroom, pronunciation teaching