Introduction

AI has become a ubiquitous tool that many students are embracing and using. Students’ engagement with AI may vary, with some students engaging in high-friction practices such as challenging outputs and crafting detailed prompts, while others might rely on “one-shot prompting” or even struggle to differentiate between intentional and unintentional misuse of AI.

This is not the first time that technology has required a reexamination of our teaching practices and approaches. For example, the creation of word processing software shifted writing from pen and paper to typing on a computer; calculators changed how mathematical work was performed; and the internet opened new opportunities for research that no longer needed to take place exclusively in a library.

While the emergence of generative AI may represent one of the most significant technological shifts educators have encountered, it is still another technology that requires us to reconsider how we teach, design learning experiences, and assess student learning.

The Problem

Students are already engaging with AI, but they are doing so in an educational environment where expectations and practices remain uneven. According to the 2026 Lumina Foundation-Gallup State of Higher Education study, 57% of college students report using AI for coursework at least weekly, while 52% report that at least some of their courses do not provide clear guidance about AI use (Lumina Foundation & Gallup, 2026).

At the same time, AI is becoming increasingly present beyond the classroom. Half of employed U.S. adults now report using AI at least occasionally in their work, further underscoring the need for students to develop thoughtful and intentional approaches to working with AI (Gallup, 2026).

As students encounter different AI expectations from course to course, they may be left unsure not only of the rules but also of what constitutes appropriate and meaningful engagement with AI (Gupta & Miller-Cochran, 2026).

The Question

What does AI require us to rethink about learning and assessment?

It is NOT about the AI tool—those will continue to change.

It IS about:

• Reassessing what we want students to learn
• Helping students show us what they are learning beyond a final written essay
• Deemphasizing the final product
• Providing learning “rest stops” on the journey to the final product

Our Approach: Redesigning Assignments in the Age of AI 

In this chapter, we present three distinct approaches instructors can use when redesigning or creating assignments and assessments in the age of AI:

Approach 1: AI-“Resistant” Assignments
This approach focuses on creating environments where AI cannot easily intervene or where its use is intentionally mitigated to ensure foundational learning.

Approach 2: Process-over-Product Assignments
This approach emphasizes the “how” of writing and thinking, treating the final product as a learning proxy rather than the only goal.

Approach 3: “Guardrails over Gotchas” Assignments
This approach moves away from surveillance and policing and toward clear expectations, transparency, and intentional boundaries around AI use and draws from the work of Moriarty, Munro, and Rottig (2026).