POTENTIAL AFFORDANCES OF GENERATIVE AI IN LANGUAGE EDUCATION: DEMONSTRATIONS AND AN EVALUATIVE FRAMEWORK
POTENTIAL AFFORDANCES OF GENERATIVE AI IN LANGUAGE EDUCATION: DEMONSTRATIONS AND AN EVALUATIVE FRAMEWORK

Summary/Abstract: With recent public access to large language models via chatbots, the field of language education is seeing unprecedented levels of interest in how AI will affect language learning and teaching. As attention is primarily focused on student misuse of the technology, the potential affordances of generative AI tools may often be overlooked. In this paper we highlight potential affordances of AI generative tools, such as ChatGPT, for creating language learning and teaching materials and assessments. We offer suggestions on crafting prompts as well as provide example prompts and the materials and assessments generated by ChatGPT in response. We also present a framework for evaluation that combines both of Hubbard’s (1988) framework for CALL evaluation and The Douglas Fir Group’s (2016) transdisciplinary framework that may assist language educators in determining when it is appropriate to leverage generative AI tools. We then briefly illustrate how the framework has been used in our own evaluations. Finally, we suggest language educators consider how the concerns and opinions of using AI- based tools held by individuals and institutions within their own micro, meso, and macro sociocultural levels align or conflict with those of the individuals and institutions of their students’ micro, meso, and macro sociocultural levels.

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