Abstract
As generative AI tools become embedded in writing instruction, educators face urgent questions about how these technologies encode and reinforce language standardization — particularly for multilingual and multidialectal students. This practitioner reflection describes a series of AI-powered "remix" activities developed and refined in corequisite writing labs. Building on a prior action research study, this paper turns to the pedagogical questions that emerged after the study: how AI tools might be used not as writing shortcuts but as objects of critical inquiry. Drawing on frameworks including critical literacy, plurilingualism, culturally relevant pedagogy, and AI literacy, we describe four remix activity types — text to image, genre transformation, tone adjustment, and translation comparison — each anchored by a critical question about AI's assumptions and values. Across these activities, students examined how AI systems privilege certain language varieties, surfaced tacit knowledge about genre and audience, and engaged in substantive discussions about language power and standardization. We argue that AI tools, approached critically, can become productive sites for developing the metalinguistic awareness students need to make informed rhetorical choices rather than simply submit to the judgments encoded in the tools they use.
Recommended Citation
Anderson, Lauren and VanDemark, Eric. (). AI-Powered Remixes: Using Generative AI to Critically Examine Text, Genre, and Language in First Year College Writing. i.e.: inquiry in education: Vol. 18: Iss. 1, Article 6.Retrieved from: https://digitalcommons.nl.edu/ie/vol18/iss1/6