Rethinking Cheating and AI: A Reflection on Academic Integrity (Part 1)

Illustration titled "Rethinking Cheating and AI: Academic Integrity" featuring a student writing at a desk while a robot labeled "AI" observes. Surrounding them are educational icons, including a checkmark, a flowchart, and documents. A megaphone and bold text emphasize the message, set against a warm beige and orange color scheme. Created using Chat GPT.

​Earlier today, while returning home from regional support work, I listened to an episode of Jennifer Gonzalez’s Cult of Pedagogy podcast featuring Tony Frontier. In it, he discussed “Catch Them Learning: A Pathway to Academic Integrity in the Age of AI.” If you haven’t had a chance to listen, I highly recommend it. Frontier shares powerful insights from his soon-to-be-released book, AI With Intention: Principles and Action Steps for Teachers and School Leaders.

Having delivered many professional learning sessions over the past two years on artificial intelligence (AI) in schools, I’ve spent considerable time thinking about academic integrity and its evolving relationship with generative AI. When I survey classroom educators about AI, concerns about cheating consistently rise to the top. These concerns are valid and must be thoughtfully addressed when integrating AI tools in K–12 settings. I’m fortunate to work in North Carolina, the fourth state in the U.S. to issue AI guidelines supporting responsible use with students and educators.
The podcast, along with my own experiences and our state’s guidance, inspired me to share some reflections on AI, academic integrity, and the conditions that either discourage or unintentionally encourage cheating.


Reflecting on Integrity and Student Pressure

As a high school teacher for over sixteen years, I vividly remember the sting of discovering a student had cheated on an assignment. Early in my career, I took it personally—like a betrayal. Over time, however, I came to understand that these incidents weren’t always personal. More often, they were responses to pressure.

I spent most of my career at a competitive high school where students strove to attend top colleges. Many carried the weight of personal ambition alongside family expectations. That pressure often translated into stress, anxiety, and at times, poor decisions.

Looking back, I also had to reflect on my own role. I taught primarily chemistry and AP-level courses where the stakes were high. In retrospect, I contributed to a classroom culture that may have increased the likelihood of students considering shortcuts. While I emphasized mastery of key concepts—like balancing equations and stoichiometric conversions—the pressure to perform on summative assessments sometimes overshadowed that message.

I’m not excusing cheating—it’s still a choice students make—but I do recognize that the structure and emphasis of assessments can unintentionally create environments where students feel that cheating is the only option to keep up.
Pacing guides, testing schedules, and curricular demands often forced students to test before they had truly mastered the material. That misalignment between expectations and readiness is something we, as educators, must own and address.


Design Thinking: A Shift in Approach

Later in my career, I taught a Design Thinking course, and the experience was transformative—for my students and for me. Due to a restructuring of our school’s schedule, time constraints were lifted. We had space to build skills, iterate, and explore. Students identified problems they cared about and developed solutions through structured, yet flexible, inquiry.

In this environment, we eliminated many of the conditions that can lead to cheating. Time was no longer a constant pressure (though we still had deadlines). Students received individualized support to build the skills they needed. The learning was authentic, and the relevance was clear. Most importantly, we assessed students throughout the process—not just at the end.

This approach resonated with a key insight from the podcast: the importance of aligning formative assessments with summative ones. That alignment helped us avoid the common disconnect between what students are doing day-to-day and what they're ultimately evaluated on - the results.  Students were more engaged, more confident, and far less inclined to take shortcuts.


Moving Forward With Intention

Too often, we operate within systems that limit our ability to truly support student growth. Now, with AI in the mix, we must be even more intentional in how we design learning. AI should augment, not replace, the learning process.
We must build classroom environments that value learning, skill development, and critical thinking over performance for performance’s sake. Students need guidance on how to use AI appropriately and ethically. And educators need to model this, clearly outlining expectations and use cases for AI based on the learning goals of each assignment.

If we fail to design with intention, we risk allowing AI to mask gaps in understanding—producing a false sense of proficiency that ultimately shortchanges students.

Let’s use this moment to rethink how we assess learning, support skill-building, and foster environments of trust and integrity.


Stay tuned for Part II of this post in the coming weeks.

Disclaimer:  The original post was written by Brian Whitson and edited using Chat GPT.  The original blog was edited by Chat GPT to make it more concise for readers.  Changes incorporated reflect subtitles as well a stronger parallel between verb tenses and changes certain words.  All changes were reviewed and either accepted or edited to reflect the author's true voice.  The image above was also created by Chat GPT based on the blog post.
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