Potential Affordances of Generative AI in Language Education: Demonstrations and an Evaluative Framework

Pack, A. & Maloney, J. (2023). Potential Affordance of Generative AI in Language Education: Demonstrations and an Evaluative Framework. Teaching English with Technology 23(2),4-24.

This timely article provides a comprehensive overview of the potential affordances of Artificial Intelligence (AI) in language teaching, particularly the AI chatbot ChatGPT. As the authors note, much of the current discourse on AI in the education sector is concerned with how AI can or could be misused by students. Although serious issues such as plagiarism need attention, the article focuses on the potential of tools such as ChatGPT to support teaching and learning and to save valuable time in developing learning materials, assessment tasks and rubrics for evaluating student writing.

AI chatbots such as ChatGPT work through prompts provided by the users, and the authors offer examples of prompts designed to elicit quality, appropriate responses which can aid instructors in developing materials for instruction and learning and for assessment purposes. The examples provided are based on the Common European Framework of Reference for Languages (CEFR) but could be drawn from other frameworks such as the CLB framework and/ or the LINC curriculum guidelines. The article also includes a discussion of how two existing frameworks, Hubbard‘s (1988, 2021) framework for evaluation and Bronfenbrenner‘s(1979), can be used in combination to assist language instructors in making informed decisions about when, how and why to use generative AI to support materials development and the creation of assessment tasks to be used in their own context.

The authors suggest that by combining elements of each framework, instructors can evaluate the use of AI tools for themselves and their students and consider how their use will align with the values and policies of the institutions and programs in which they work.

Retrievable from: https://files.eric.ed.gov/fulltext/EJ1397173.pdf