Generative artificial intelligence and language teaching and learning: Productive and responsible use and research possibilities

Since the public release of ChatGPT in November 2022, there has been intense wonder, surprise, excitement, concern, and worry about the capabilities of generative artificial intelligence (GenAI) tools and their rapid adoption into our personal and professional practices. Indeed, ChatGPT is the fastest-growing internet application in history (Hu, 2023). GenAI tools have begun to be integrated into almost all fields and disciplines including language teaching and learning (Crompton and Burke 2024; Jeon and Lee 2023). When well-prompted, these tools can efficiently and (often) accurately perform many tasks commonly associated with human intelligence, including text generation, text summarization, translation, analysis, as well as, image, code, audio and video generation. However, releasing these tools has raised significant ethical issues that users should be aware of so they can use them critically (Moorhouse et al., 2023) and many questions that require empirical research.
This seminar, with its practical focus, aims to provide an accessible introduction to GenAI tools and their application for language teaching and learning. It will define GenAI and give an overview of types of GenAI tools, consider the utility of GenAI for language teaching and learning purposes, and raise some issues language teachers should consider when integrating GenAI into language teaching and learning. It concludes by proposing some critical empirical research areas that need urgent study.
Benjamin Luke Moorhouse is an Assistant Professor in the Department of Education Studies at Hong Kong Baptist University (HKBU). His research focuses on the lived experiences and competencies of teachers, and the role of technology in English-language teaching and learning. Benjamin was in the top 2% of cited scholars in the world in 2022 and 2023. He has been leading the GenAI task force at HKBU. His research has been published in journals such as TESOL Quarterly, System, RELC Journal, and ELT Journal.

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