Document Type
Assignment
Abstract
The basic mechanics of this activity are simple: choose a reading from class and try to manipulate the LLM to recreate it as close to the original as possible. As a rule, I generally try to produce and run activities that are modular, interchangeable, and adaptable. This activity is no different. In one course, we used the prompt and only the prompt—no scaffolding. In other courses, we scaffolded LLMs, understood how prompt engineering might work, and worked as a class to construct the prompt we thought would produce a suitable outcome.
For students, the limitations of the LLMs become clear almost immediately. With non-scaffolded classes, students will often attempt to put in the name of a text and instruct the LLM to recreate it—often to some hilarious results. Even with the scaffolded and carefully crafted prompts students begin to recognize the limitations. This might come in the form of length, depth, or even understanding of an abstract concept.
The most unexpected outcome was how deeply the students had to re-engage with content from the class. Of course, we have had discussions about voice, style, tone, message, etc. But, in this case, they felt compelled to clearly articulate these ideas to the LLM.
Publication Date
1-2024
Recommended Citation
Anthony, J. (2024). Introductory Activity for Generative AI. In C. Schnitzler, A. Vee, & T. Laquintano (Eds.), TextGenEd: Continuing Experiments. The WAC Clearinghouse. https://wac.colostate.edu/repository/collections/continuing-experiments/january-2024/prompt-engineering/introductory-activity-for-generative-ai/.
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