Prince George (Canada): (The Conversation) As another school year begins, large language models (LLMs) present difficult questions around learning, thinking, plagiarism, and authorship for educators.

New approaches to assignments and assessment are required, as student papers using LLM technology demand additional labour. Professors have expressed frustration, worry, and anxiety.

As an assistant professor of English whose research focuses on the histories of writing and how it is taught, I have been involved in many discussions about this topic. The immediate issue of LLMs in the classroom points to a larger reality: for too long, instructors and universities have treated students' writing difficulties as a deficiency in the mind instead of recognising that writing, as a technology for thinking, is cognitively demanding. Writing helps us understand our own ideas better, and where people are involved in thinking and invention, it needs to be taught in that spirit.

Why consider AI output as writing?
LLM technology creates, at best, a facsimile of a textual object, producing output that resembles text based on existing material. When generated for assignments, it mimics standard academic English, which has a special relationship to truth. This artificial output exposes academic writing as a social construction, challenging long-held notions of its absoluteness.

Historical and social concerns
Standard academic writing has historically been taught as the “default” style, shaped by literary and technical streams that reinforced the status quo, often perpetuating inequities tied to colonialism and racism. Correctness is contextual and subjective; judging intelligence solely on academic writing can drive reliance on LLMs.

Revisiting the final product
If instructors only value a correct final product, a computer can easily replicate it. But to support students' inquiry and thought, writing must be seen as a social process involving listening and engagement.

Re-think what writing is
This involves allowing students to submit work in progress, providing feedback on drafts, and teaching writing as invention that considers audience, context, and power structures. Writing experts must be involved in AI policy creation, or universities risk producing students alienated from their own ideas.

The study of writing is uniquely positioned to guide institutions in navigating these urgent questions.(The Conversation)