Generative AI is the most influential technology in writing in decades—nothing since the word processor has promised as much impact. Publicly-accessible Large Language Models (LLMs) such as ChatGPT have enabled students, teachers, and professional writers to generate writing indirectly, via prompts, and this writing can be calibrated for different audiences, contexts and genres. At the cusp of this moment defined by AI, TextGenEd collects early experiments in pedagogy with generative text technology, including but not limited to AI. The fully open access and peer-reviewed collection features 34 undergraduate-level assignments to support students' AI literacy, rhetorical and ethical engagements, creative exploration, and professional writing text gen technology, along with an Introduction to guide instructors' understanding and their selection of what to emphasize in their courses. TextGenEd enables teachers to integrate text generation technologies into their courses and respond to this crucial moment.
The entire collection at a glance. Click on the blue links to navigate to the different sections.
Meet Annette Vee, Timothy Laquintano, and Carly Schnitzler.
We invite college instructors working with text generation technologies (e.g., GPT-3, Markov models, Tracery) to submit relevant classroom assignments and activities to an open access edited collection to be published by the WAC Clearinghouse in Aug 2023.