Prompt Engineering

In Continuing Experiments, we added a new subcategory—prompt engineering—to reflect the continued importance of iterating prompts and platforms to achieve writing goals with generative AI.

Rhetorical Prompt Engineering

Bryan Kopp
Christopher McCracken
Lindsay Steiner
Louise Zamparutti

University of Wisconsin-La Crosse

This assignment introduces students to generative text technology through a scaffolded set of tasks in which they intervene in a classic professional and technical writing case study: the risk communication surrounding the Three Mile Island nuclear disaster. Students used ChatGPT to understand the case, to analyze and revise one of the memos implicated in the meltdown, to document and reflect on their revision strategies, and to develop a set of best practices for working with generative AI in technical communication. 

Introductory Activity for Generative AI

Josh Anthony
Gonzaga University

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.

Applying Advanced Generative AI Prompting Techniques

Emily Dux Speltz and Abram Anders
Iowa State University

This assignment is designed to enhance students' proficiency in advanced AI prompting techniques. The primary goal is to transform students who are already familiar with basic AI tool usage into advanced users capable of employing complex prompts effectively. Overall, we have found the activity to be successful in encouraging students to experiment with various advanced prompting techniques in a risk-free setting, allowing them to identify the prompting methods that resonated most with them. 

The Gen/ReGen Log: Refining the Rhetoric of Structured Prompts

Brian Gogan
Western Michigan University

This assignment offers students an exploratory space—literally, a tabular document accompanied by an iterative process—within which they can refine the rhetoric of structured prompts and experiment with prompt engineering. As students focus on discrete rhetorical concepts, honing prompts to yield more optimal results, they further explore the relationships between production and reception, intent and interpretation. The assignment may be adapted for use in a single class or iterated across a weeks-long portion of a course to allow for differentiated learning. Weeks after having completed their last Gen/ReGen Log, my students still reference this assignment. Some of my students—themselves, college or high school educators—report success using Gen/ReGen Logs with their own students.

Translinguo: Critically Making Chatbot Prototypes by Learning How to Write Generative AI prompts 

Anuj Gupta
University of Arizona

In this assignment, students critically tackle the biases exhibited by large language models (LLMs) like ChatGPT against world Englishes and other marginalized language varieties by using prompt engineering as a means to reprogram these biases for more equitable AI outputs. This assignment, originally developed for my ENGL 430: UX Research Methods class, introduces students to ChatGPT prompts as a digital genre and presents prompt engineering as a critical making activity through which they can iteratively design prototypes of innovative chatbots to tackle social problems they see in generative AI tools. This assignment resulted in innovative designs and thoughtful reflections on AI, language, and ethics.