What we learned about teaching for integrity in the age of AI
Lessons from our team's Special Topics Book and Podcast Club
In this short series, we’re sharing reflections from CxC’s Faculty Development Team Summer Special Topics Book and Podcast Club. Read the first installment sharing reflections from John Warner’s book More Than Words.
In many of our recent conversations with faculty about AI use in the classroom, the subject of cheating comes up quickly. The goal of helping students use generative AI ethically inevitably leads us to questions of academic integrity—what it really means, and how we teach it.
For this session, we turned to the Teaching in Higher Ed podcast featuring Tricia Bertram Gallant and David Rettinger (Episode 568). Their discussion offered a fresh framework for thinking about integrity as something relational and teachable, not just punitive and procedural. The episode grounded our own team conversations about how we help students navigate challenges in communication skill development, persist through difficulty, and clarify what we mean when we talk about “academic integrity.”
Below are a few of our collective reflections—we hope you’ll add your own ideas in the comments.
Cheating as Human, Integrity as Relational
Conversations about academic integrity often focus on crimes, misdemeanors, and consequences—how to detect or prevent infractions. The podcast invited us to think differently: that cheating is part of being human, and that conversations about integrity are also about emotion, shame, and psychosocial context, not just policy.
This perspective led us to reflect on the teaching moments in integrity issues. Students often cheat not out of malice but from pressure, fear, or embarrassment. Labeling them as “cheaters” leaves little space for growth or learning. Instead, we can teach students to understand the process of learning—the value of sitting in challenge and persisting through struggle. Integrity, in this sense, becomes something to practice and cultivate, not just enforce.
Formative vs. Summative Assessment
Assessments are often the focal point of both learning and anxiety. For many students, grades feel like the ultimate measure of success. But what if we shifted that focus?
In C-I pedagogy, we emphasize feedback early and often. Formative assessments—low-stakes, process-oriented checkpoints—help students move through learning, reduce performance pressure, and lessen the temptation to resort to dishonest shortcuts. When learning is framed as a journey rather than a single, high-stakes moment, integrity has more room to grow.
Avoiding “Assessment Security Theater”
We loved this phrase from the conversation: “assessment security theater.” It describes punitive surveillance methods that create the illusion of integrity without actually cultivating it.
Research shared by Todd Zakrajsek (citing Don McCabe) identifies common reasons students cheat: pressure to do well, belief that everyone else is doing it, meaningless or “busy” work, and low risk of being caught. Integrity-supportive assessment design—like mastery-based testing, clear guardrails, and linked assignments—offers a stronger foundation.
In short: guardrails, not gotchas. Build systems that guide students toward ethical choices rather than catching them when they misstep.
Intrinsic vs. Extrinsic Motivation
Education often overemphasizes external rewards—grades, GPA, status—while undervaluing intrinsic motivators like curiosity, meaning, and purpose. We discussed how structural challenges (large class sizes, limited time, general education requirements) complicate this, but also how small shifts can help.
Strategies such as student choice, in project topics, source material, or assessment formats, can foster greater investment. Yes, it’s more complex to teach this way, but it opens meaningful opportunities for engagement and authentic learning.
Rethinking Faculty Roles in Integrity
The rise of AI has pushed many faculty into a defensive stance—policing AI use through bans, detection software, and referrals. When catching cheating becomes central to teaching, it can reshape the learning climate itself.
The podcast encouraged us to imagine a more proactive, teaching-centered approach. Instead of time spent on “don’t cheat” speeches, what if we used that time to inspire students to honor their learning process—their effort, growth, and developing voice? Integrity, reframed, becomes part of the creative act of learning.
We want to hear from you: What practices help you teach for integrity in your classroom? What questions do you have on this approach to AI?
Conversation Models and Teaching Moments
Helping students feel connected to their coursework—especially in the daily grind of quizzes, papers, and exams—is essential. We talked about how scaffolding assignments (breaking them into smaller parts with feedback) can prevent overwhelm and reduce the impulse to outsource work to AI.
Gallant and Rettinger shared practical conversation models for addressing integrity concerns:
Start with observations, not accusations.
Interpret tentatively—leave room for students to explain.
Invite students to describe their process.
Every integrity concern can be a teachable moment, grounded in respectful, transparent communication. When expectations and feedback are clear, and when students feel supported in developing self-efficacy, integrity grows naturally from the learning relationship.
Share Your Reflection
Teaching for integrity in the age of AI is not about fortifying defenses—it’s about building trust, clarity, and care into our teaching. As we continue these conversations, we invite you to join us: What practices help you teach for integrity in your classroom?