With adjustments to the way we teach students to think about writing, we can shift the emphasis from product to process
It’s getting close to the beginning of term. Parents are starting to fret about lunch packs, school uniforms and schoolbooks. School leavers who have university places are wondering what freshers’ week will be like. And some university professors, especially in the humanities, will be apprehensively pondering how to deal with students who are already more adept users of large language models (LLMs) than they are.
They’re right to be concerned. As Ian Bogost, a professor of film and media and computer science at Washington University in St Louis, puts it: “If the first year of AI college ended in a feeling of dismay, the situation has now devolved into absurdism. Teachers struggle to continue teaching even as they wonder whether they are grading students or computers; in the meantime, an endless AI cheating and detection arms race plays out in the background.”
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