Book Bytes: The Opposite of Cheating: Teaching for Integrity in the Age of AI
June 11, 2025 / Digital Learning / Tags: Book Bytes, Online Teaching, Digital Learning
"Enhancing learning and integrity is, after all, The Opposite of Cheating and is premised on an optimistic, growth-oriented approach to addressing cheating."
Video (5:02)
- All instructors/faculty
- Administrators & Institutional leaders
- Instructional Designers
Key Takeaways
- The opposite of cheating is learning, not just integrity.
The authors emphasize that the true antidote to cheating is not stricter surveillance or harsher penalties - it's meaningful learning. When students are engaged, supported, and see value in what they are learning, they are far less likely to cheat. This book encourages educators to focus on designing learning experiences that are relevant, motivating, and rooted in curiosity. - We must rethink assessment in the age of AI.
With generative AI tools capable of completing many traditional assignments, the author urge faculty to revisit what and how they assess learning. Are your assessments still measuring what matters? Are they authentic, reflective, or real-world skills, and resistant to automation? This book provides strategies for designing assessments that promote integrity and deeper learning. - Build relationships and foster trust in your courses.
At the heart of academic integrity is the student-teacher relationship. Gallant and Rettinger advocate for a human-centered approach to teaching - one that prioritizes empathy, communication, and trust. When students feel seen, supported, and respected, they are more likely to act with integrity. This relational approach is especially critical in a digital world where students may feel increasingly disconnected.
Coming Soon! The Opposite of Cheating will be an FGCU eBook. Read it for free!
References:
Gallant, T. B., & Rettinger, D. A. (2024). The opposite of cheating: Teaching for integrity in the age of AI. Harvard Education Press.
Portions of this blog post and video script were developed with support from OpenAI’s ChatGPT, used to refine and condense initial drafts.
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