Faculty from across UWSP met monthly during the 2025-26 academic year to discuss emerging uses of generative artificial intelligence and how instructors might incorporate AI into their teaching to better prepare students to enter a workforce that may be expected to use and interact with AI agents. This faculty learning community:
- Engaged in independent readings and thought-provoking discussions about the impact of artificial intelligence on higher education and the workforce at large, with specific emphasis on the fields of employment for which their disciplines prepare students.
- Explored AI literacy frameworks to better understand the competencies our students will need, explaining what it means to prepare students for an AI-driven workforce.
- Collaborated across diverse disciplines, to foster rich conversations about AI’s applications in a wide array of professional contexts.
- Discovered and designed innovative ways to incorporate AI into course assignments, enhancing student engagement and learning outcomes.
Under each of the following headings, you can find the fruits of their labor. Each heading represents a suggested AI-related activity that you can adapt to your teaching context. Assignment template files are provided, in which specific portions that instructors should modify for their specific uses are indicated in bold type that is highlighted yellow. There are also facilitator guides for these exercises.
Special thanks to the members of the FLC, including: Karyn Biasca, Ada Duffy, Aaron Gierhart, Rebecca Henning, Liz Potter-Nelson, Nancy Shefferly, and Joe Zawacki.
Cocreation of Course GAI Policy #
Each course at UWSP must have a policy regarding use of generative AI. But, as we all know, having a policy and getting students to adhere to it are two very different things. Students are unlikely to comply with such policies unless they have some form of buy-in. They need to understand the rationale for the policy, as well as how the policy benefits them.
One way to help establish this kind of buy-in is to enlist students in development of your course AI policy, including when and how AI can be used acceptably, when use is not acceptable, and what the punishment for violations of the policy will be. Cocreation of rules provides students with some ownership, and therefore buy-in for those rules. In addition to allowing student input, this approach forces them to consider thoughtfully the impact of AI use in a variety of course contexts.
GAI Editing with human intent Assignment #
One use of AI tools that holds instructional promise is to help students develop metacognitive awareness of the choices they make in communication. In this assignment, students use AI to suggest changes to student writing. Rather than simply accepting changes, students are tasked with evaluating the suggestions, and reflecting on how each suggestion impacts the meaning, voice, and intent in the student’s work. This allows students to develop the ability to adapt AI outputs to serve specific purposes, providing valuable work-ready skills.
Prompt Engineering Activity #
Given the growing use of AI agents across all professions, ensuring that our students are able to interact effectively with AI will help them develop career readiness. Essential skills include prompting AI agents to produce the desired output, and critically evaluating the outputs elicited by our prompts. This assignment is a good introduction to effective use of generative AI.
Critiquing and Revising GAI output #
Employability in the age of generative AI will hinge on how effectively a prospective employee can partner with AI to produce more or better outputs than either the employee or the AI could produce on their own. It is therefore critical that students develop skill in evaluating and augmenting AI outputs. This assignment is a good introduction to these skills and can be modified according to disciplinary requirements. The structure of the exercise should help students acquire disciplinary content knowledge and familiarity with disciplinary source materials.
Gai assisted workflow development #
Whether as students or employees, success is tied to effective time management. However, this essential skill often presents a stumbling block, especially for those with either immature or compromised executive function. This exercise is designed to help students leverage the organizational capabilities of AI to augment their own scheduling capabilities to develop a realistic workflow.
GAI as a debate partner #
This assignment is designed to help students articulate and understand arguments, evaluate and respond to evidence and counterarguments, and develop perspectives that are appropriate for your discipline by using generative AI as a debate partner.
Role Playing with GAI #
Teaching students appropriate forms of interaction with others can be challenging, in part because skill development requires practice, and students are often reticent or uncomfortable modeling expected interactions with peers. Using generative AI as a partner in role playing exercises can be useful in helping students to develop skills and modify behaviors without the added stress of “performing” in front of others. This exercise can be modified according to discipline.
Training a GAI agent for test prep #
There are some things GAI can do for you. There are a lot of things, like studying and learning, that it can’t. In this exercise, students prepare AI in a simulation of training am AI agent for a specific task. In this case, the specific task is taking the final exam in your course. In order to train the agent, students must identify content essential to achieving learning outcomes in the course. This requires review and study to produce a comprehensive study guide for training the AI agent. In addition to working with AI functions, this exercise facilitates study for a comprehensive final exam.
