UIC Faculty Collaborate on AI-Centered Assignments
Introduction
The AI Teaching & Learning Advisory Committee worked together this past year to compile examples of assignments engaging AI that might serve as a starting point for UIC faculty at large. These examples spark faculty's curiosity, serving as a rough draft that can be adapted, revised, and developed.
The project is motivated by a need to support AI literacy at UIC. This involves collaborating to define critical AI literacy both generally and within specific academic disciplines, and equipping students for a future profoundly influenced by AI, which is essential for developing the workforce of tomorrow.
After several meetings discussing possible assignments, faculty on the subcommittee gathered their results, provided feedback, made revisions, and placed their work on a public-facing UIC webpage: Generative AI-Centered Assignments for UIC Faculty.The assignments are clustered by academic division, but each assignment represents a different form of AI use for the classroom, making them easily portable across disciplinary boundaries.
Common Patterns of AI-Centered Assignments
The process of developing and discussing these assignments led to the recognition of some common patterns. Broadly speaking, AI-centered assignments tend to sort into three categories: oriented “at” AI, “beside” AI, or “through” AI.
At AI: One way to engage AI in classrooms is to approach it as an object of inquiry in a traditional mode by providing external information and perspective on it and then testing students’ comprehension and retention of that knowledge. This kind of assignment treats AI externally—as something to be studied rather than directly used.
Beside AI: Many assignments place AI-assisted and non-AI-assisted work side by side for comparison. Students might complete a task on their own, then have AI do the same, or complete it twice—once with and once without AI. This format invites critical reflection and metacognition about the task, its demands, and how best to collaborate with technology to achieve specific goals.
Through AI: The most difficult kind of assignment to generate is one that would be virtually unimaginable without the AI itself. Here, AI’s unique features are used to create a novel challenge and experience. In our library, Patrick Fortmann of German Studies uses AI to guide students through adapting a fairytale step by step, reinforcing literary theory and offering a personalized view of the complexities of adaptation.
Generating Conversations About AI in the Classroom
Compiling these examples also sets a stage for continuing conversation among faculty and administrators about the ways, both positive and negative, that AI can transform education.
Several years ago (in the 80s) B.J. Fogg, a computer scientist at Stanford with a background in rhetoric, began formalizing a field of study in “computers as persuasive technologies.”[1] Computers, Fogg observed, possess a different set of limitations and affordances than humans. Cataloging them can sharpen our understanding of “human-computer interactions.” Obviously, such an understanding has never been more salient to higher education than it is right now.
Many of Fogg’s observations about computers as persuasive technologies seem even more pertinent after the rise of AI. Since teaching is always a persuasive process to some degree, understanding how computers function persuasively illuminates how they might contribute to a course or classroom.
As persuasive tools, computers can increase self-efficacy, provide tailored information, trigger decision-making, simplify or organize, and provide structure and process.[2] Drawing on these observations, we developed the following prompts for your own thinking:
- Could you use AI to increase students’ self-efficacy?
- Could you use AI to provide students with tailored information?
- Could you use AI to trigger decision-making for students at targeted points in a module or assignment?
- Could you use AI to simplify or organize material for students in ways that facilitate intellectual development?
- Could you use AI to provide structure and process for students?
As persuasive media, computers simulate cause and effect, environments, and objects. Foff points out how computers’ graphical interface can produce persuasive effects. For example, Blackboard and Canvas simulate objects like digital “folders” and “documents.” They also simulate simple cause and effect relationships, e.g., finishing one assignment unlocks another.
AI seems to simulate these kinds of things too, but with notable differences. What kinds of environments, causes and effects, and objects could an AI be used to simulate? And could such simulations enhance some aspect of your course?
[1] Fogg, personal communication, but see his website: https://www.bjfogg.com/about
[2] Much of the following is based on a handbook chapter by B.J. Fogg, Gregory Cuellar, and David Danielson, but the material is also repeated in his textbook, Persuasive Technology: Using Computers to Change What We Think and Do (2003).
Learning, Technology, and Solutions
LTS plays a crucial role in monitoring trends and developments in educational technology and in building relationships with vendors to provide faculty and students with the best available tools. This work is directly linked to the meaningful interactions that occur during classes—thoughtful and challenging exchanges between students, teachers, and the community they foster. The AI use cases we explore are not merely attempts to standardize or simplify the integration of AI into courses. Instead, they serve as an essential bridge between LTS’s efforts to pilot innovative technology to enhance teaching and learning and the real-world experiences of professors and students who are striving to create a better future.