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The Opposite of Cheating: Teaching for Integrity in the Age of AI
In these days of an ever-expanding internet, generative AI, and term paper mills, students may find it too easy and tempting to cheat, and teachers may think they can’t keep up. What’s needed, and what Tricia Bertram Gallant and David A. Rettinger offer in this timely book, is a new approach—one that works with the realities of the twenty-first century, not just to protect academic integrity but also to maximize opportunities for students to learn.
The Opposite of Cheating presents a positive, forward-looking, research-backed vision for what classroom integrity can look like in the GenAI era, both in cyberspace and on campus. Accordingly, the book outlines workable measures teachers can use to better understand why students cheat and to prevent cheating while aiming to enhance learning and integrity.
Bertram Gallant and Rettinger provide practical suggestions to help faculty revise the conversation around integrity, refocus classes and students on learning, reconsider the structure and goals of assessment, and generally reframe our response to cheating. At the core of this strategy is a call for teachers, academic staff, institutional leaders, and administrators to rethink how we “show up” for students, and to reinforce and fully support quality teaching, learning, and assessment. With its evidentiary basis and its useful tips for instructors across disciplines, levels of experience, and modes of instruction, this book offers a much-needed chance to pause, rethink our purpose, and refocus on what matters—creating classes that center human interactions that foster the personal and professional growth of our students.
The Opposite of Cheating presents a positive, forward-looking, research-backed vision for what classroom integrity can look like in the GenAI era, both in cyberspace and on campus. Accordingly, the book outlines workable measures teachers can use to better understand why students cheat and to prevent cheating while aiming to enhance learning and integrity.
Bertram Gallant and Rettinger provide practical suggestions to help faculty revise the conversation around integrity, refocus classes and students on learning, reconsider the structure and goals of assessment, and generally reframe our response to cheating. At the core of this strategy is a call for teachers, academic staff, institutional leaders, and administrators to rethink how we “show up” for students, and to reinforce and fully support quality teaching, learning, and assessment. With its evidentiary basis and its useful tips for instructors across disciplines, levels of experience, and modes of instruction, this book offers a much-needed chance to pause, rethink our purpose, and refocus on what matters—creating classes that center human interactions that foster the personal and professional growth of our students.
274 pages, Paperback
First published January 1, 2024
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Displaying 1 - 24 of 24 reviews
August 7, 2025
You can tell it was started before GenAI and had to pivot. Some really great sections on teaching integrity and identity, which is more what I was hoping for—tactical advice (scaffolding, banks) is pretty commonplace.
March 18, 2026
A solid overview of why students cheat and what strategies are most effective in encouraging most students to not cheat. Some of the generative AI-specific content felt like an afterthought (which makes sense, since this book was planned / already being written before ChatGPT burst onto the scene). There are definitely a few techniques mentioned in this book which I plan to research more and implement myself (e.g. oral assessments)!
December 18, 2025
I was disappointed that, in a book full of recommendations to ‘collaborate’ with LLMs, the chapter on ‘infusing ethics into teaching and learning’ only paid lip service to the ethical ills of AI, with one solitary sentence mentioning the theft and human exploitation involved in the creation of Generative AI.
This aside, the book has a tidy diagnosis of why students cheat (low self-efficacy, unclear course expectations, moral disengagement, focus on performance rather than learning, etc.), and some sensible (not always obvious) strategies for putting learning at the centre of classes instead of grades.
This aside, the book has a tidy diagnosis of why students cheat (low self-efficacy, unclear course expectations, moral disengagement, focus on performance rather than learning, etc.), and some sensible (not always obvious) strategies for putting learning at the centre of classes instead of grades.
May 6, 2026
Good insights into the impacts of AI on education, but even better thoughts and ideas about how to build classroom community that leads students into purposeful learning rather than simple task completion, with or without AI assistance.
April 28, 2026
Cheating often comes from morally disengaging via behaviors of “neutralizing”:
1. Denial of responsibility: the student justifies their behavior by claimant they didn’t she intentionally or the behavior was an accident
2. . Denial of the victim or tonight with harm: western believe that cheating is a victimless crime, and that their actions benefit them all harming no one.
3. Condemnation of the containers: the student blames, Professor, the academic integrity office for the University, more broadly for their behavior. They believe that the instructor doesn’t like them is out to get them, or the system is right against them.
4. Appeals to higher loyalty: the student uses loyalty to rationalize, cheating, for example, asking a friend for help who they expect loyalty from.
Motivations:
Instead of “Mastery” (love of learning, understanding the subject for the sake of understanding) most students have extrinsic (get an A, get a good job) and performance (do as well as peers) motivations on the whole.
Good pedagogy- Students are less likely to cheat in classes where:
- [ ] they had individual relationships with their instructors;
- [ ] they had the opportunity and desire to engage with the material inside and outside of class;
- [ ] they had formed cohesive relationships with at least some of their classmates;
- [ ] the course was enjoyable overall;
- [ ] their time was well spent; and
- [ ] the course was well organized.
Define what cheating and AI is in the syllabus, with examples of the actions that would count. Ex. Using the work of GenAI or someone else and submitting it as your own would be dishonest. Using unauthorized test aids is unfair to your peers in class. A false excuse for missing an assignment erodes trust. However, the syllabus is not enough. The book recommends teachers having the conversation about what integrity is with students and explaining the why.
Don’t put a policy in the syllabus you aren’t willing to follow through on if a student cheats (consider accidents or niece mistakes (don’t ask for a roll you don’t want to reward))
Mixed research but possible benefits from integrity nudging through repeated opportunities (usually before a large assignment or test) that invites students to promise or pledge to not cheating. Perhaps have them read the pledge at the front and sign it at the end.
Codify ethical standards with the class (agree and set the ground rules together, (build buy in and have them decide what to agree to.))
Arbitrarily assigning deadlines supports no one, perhaps have one floating, free, late assignment, pass, or incentivize students to submit earlier so if they submit by the first deadline, they get a lot of feedback. Second deadline a little feedback third deadline no feedback. - Cath Ellis
Avoid all or nothing grading, given points for attendance, and do a medium amount of assessments throughout the year, rather than one big one or a million small ones
Choose one course design strategy that you will implement next term and one that you will think more about for later adoption:
a. Design or redesign learning objectives
b. Craft a learner-centered syllabus
c. Implement flexible deadlines
d. Switch the focus away from grades
e. Engender metacognition
f. Scaffold big projects
g. Rethink grading
2. Consider how GenAI impacts your course design choices. How might you use GenAI to help you redesign your courses?
3. Talk to your department chair about your thoughts around course design. Fill them in on what you've learned and why you're thinking about making these changes. Ensure they're on board with your efforts.
4. For department chairs, consider what training, sup-port, and funding you have in place to enable faculty to research, rethink, and implement these course designs.
5. For administrators, give some thought to the emphasis on grading at your institution. Convene a task force to consider alternative approaches, including the merits of suspending students with low grade point averages.
Make sure that your teaching and learning professionals are well supported as they work with faculty to create innovative alternatives to traditional assessments.
6. Finally, for institutional leaders, consider establishing a computer-based testing facility to allow frequent, mastery-based assessments that, when executed prop-erly, not only promote learning but reduce cheating opportunities.
Team based learning has some interesting ideas about student ownership of work.
Authentic assessment: challenging, as similar as possible to a meaningful task, and involving performing a task or completing a project many times in a collaborative fashion.
Designing Assessment for Integrity
Next Steps
1. Reflect on the following strategies. Based on the classes you teach and your discipline, choose one strategy you can implement next term and another you'll spend more time learning about:
a. Infuse integrity into lessons and assessments
b. Align expectations with assessment rubrics
c. Allow and co-opt collaboration
d. Give opportunities for revision
e. Give students choice and control
f. Make your assessments authentic
g. Plan for cognitive offloading
h. Include oral assessments
2. If you have already read the course design and communicating integrity chapters, consider how your chosen strategy connects to the ones you chose from them.
3. Play with some GenAl tools to plan how they might help you deploy your chosen strategy.
4. For administrators, provide professional development opportunities for faculty interested in creating grading rubrics. Provide the infrastructure to enable faculty to share rubrics, assignments, and other assessment tools.
5. Also for administrators, consider making instructional designers available to help instructors design or redesign in-person, hybrid, and online courses.
STRATEGIES THAT PROMOTE SUCCESS WITH INTEGRITY
Next Steps
1. Reflect on these strategies. Based on the classes you teach and your discipline, choose one strategy you can implement next term and another you'll spend more time learning about:
a. Model the behaviors you want to see
b. Be engaging and intentional
c. Be present as an instructor
d. Create a sense of belonging
e. Engage in universal learning design to make your class more accessible
f. Develop teacher metacognition
2. If you have already read the assessment design, course design, and communicating integrity chapters, consider how your chosen strategy connects to strategies you selected in those chapters.
3. Make a presence worksheet for one of your classes.
Observe how and whether you are present, either in person or through class structures, and make changes to create a more vibrant community of learners.
4. For institutional leaders, ask yourself how you are modeling integrity on a daily basis and in front of your instructors and students. Is your institution creating a sense of belonging for all students, and if so, how are the institutional efforts helping (or not helping) class cultures? Finally, do instructors have sufficient support to make their classes more accessible, or are you unintentionally creating an accommodation-dependent culture?
PROTECTING
ASSESSMENT INTEGRITY
Students could write some of the test questions used in assessment, which offloads work that the instructor must do to write and rewrite
Getting to know students through icebreakers can pull double duty if they are moving around the room, would you rather style, answering questions like “would you rather give an oral presentation or show a side by side coding comparison in R?” So that you can get them thinking about the form/content of the class, while they identify like minded peers.
Next Steps
1. Interrogate your learning objectives to determine which are still valid and which need to be updated given the existence of GenAl.
2. Examine your assessments in light of what you have decided about your learning objectives. Are the assessments still valid or do you need to redesign any of them? Which are assessments of learning (summative rather than formative) and thus need to be secured?
3. For any assessment you are redesigning, consider whether any part of it can or should be cognitively offloaded to GenAl.
4. For summative assessments or assessments that students need to complete without the aid of GenAI, choose at least one of the following strategies for securing them:
a. Generating new questions every term
b. Using randomization techniques
c. Deploying technology (e.g., lockdown browsers)
d. Proctoring students as they complete the assessment
5. For administrators, consider the value of closely exam. ining assessment security tools that your instructors might use. Make sure that the tools you're considering meet the criteria we've outlined before buying or renewing your contracts.
6. Also for institutional leaders, examine the value of establishing a computer-based testing facility on your campus that provides students with consistent and secure testing conditions, as well as of purchasing assessment software like Prairie Learn that enables instructors to individualize and randomize assessment questions.
INFUSING ETHICS INTO TEACHING AND LEARNING
1. Cheating in assignments should earn a 0, while an honest try should still score higher. Maybe late work allows for a turn in with a deduction, but not worse than cheating would merit
CONCLUSION
1. Revise how you think and talk about integrity
2. Refocus on learning
3. Rethink your educational persona
4. Reconsider the nature and point of assessment
5. Reimagine how you show up for your students
6. Revisit assessment security for a new era
7. Reframe how you respond to cheating
8. Provide quality teaching learning and assessment resources
1. Denial of responsibility: the student justifies their behavior by claimant they didn’t she intentionally or the behavior was an accident
2. . Denial of the victim or tonight with harm: western believe that cheating is a victimless crime, and that their actions benefit them all harming no one.
3. Condemnation of the containers: the student blames, Professor, the academic integrity office for the University, more broadly for their behavior. They believe that the instructor doesn’t like them is out to get them, or the system is right against them.
4. Appeals to higher loyalty: the student uses loyalty to rationalize, cheating, for example, asking a friend for help who they expect loyalty from.
Motivations:
Instead of “Mastery” (love of learning, understanding the subject for the sake of understanding) most students have extrinsic (get an A, get a good job) and performance (do as well as peers) motivations on the whole.
Good pedagogy- Students are less likely to cheat in classes where:
- [ ] they had individual relationships with their instructors;
- [ ] they had the opportunity and desire to engage with the material inside and outside of class;
- [ ] they had formed cohesive relationships with at least some of their classmates;
- [ ] the course was enjoyable overall;
- [ ] their time was well spent; and
- [ ] the course was well organized.
Define what cheating and AI is in the syllabus, with examples of the actions that would count. Ex. Using the work of GenAI or someone else and submitting it as your own would be dishonest. Using unauthorized test aids is unfair to your peers in class. A false excuse for missing an assignment erodes trust. However, the syllabus is not enough. The book recommends teachers having the conversation about what integrity is with students and explaining the why.
Don’t put a policy in the syllabus you aren’t willing to follow through on if a student cheats (consider accidents or niece mistakes (don’t ask for a roll you don’t want to reward))
Mixed research but possible benefits from integrity nudging through repeated opportunities (usually before a large assignment or test) that invites students to promise or pledge to not cheating. Perhaps have them read the pledge at the front and sign it at the end.
Codify ethical standards with the class (agree and set the ground rules together, (build buy in and have them decide what to agree to.))
Arbitrarily assigning deadlines supports no one, perhaps have one floating, free, late assignment, pass, or incentivize students to submit earlier so if they submit by the first deadline, they get a lot of feedback. Second deadline a little feedback third deadline no feedback. - Cath Ellis
Avoid all or nothing grading, given points for attendance, and do a medium amount of assessments throughout the year, rather than one big one or a million small ones
Choose one course design strategy that you will implement next term and one that you will think more about for later adoption:
a. Design or redesign learning objectives
b. Craft a learner-centered syllabus
c. Implement flexible deadlines
d. Switch the focus away from grades
e. Engender metacognition
f. Scaffold big projects
g. Rethink grading
2. Consider how GenAI impacts your course design choices. How might you use GenAI to help you redesign your courses?
3. Talk to your department chair about your thoughts around course design. Fill them in on what you've learned and why you're thinking about making these changes. Ensure they're on board with your efforts.
4. For department chairs, consider what training, sup-port, and funding you have in place to enable faculty to research, rethink, and implement these course designs.
5. For administrators, give some thought to the emphasis on grading at your institution. Convene a task force to consider alternative approaches, including the merits of suspending students with low grade point averages.
Make sure that your teaching and learning professionals are well supported as they work with faculty to create innovative alternatives to traditional assessments.
6. Finally, for institutional leaders, consider establishing a computer-based testing facility to allow frequent, mastery-based assessments that, when executed prop-erly, not only promote learning but reduce cheating opportunities.
Team based learning has some interesting ideas about student ownership of work.
Authentic assessment: challenging, as similar as possible to a meaningful task, and involving performing a task or completing a project many times in a collaborative fashion.
Designing Assessment for Integrity
Next Steps
1. Reflect on the following strategies. Based on the classes you teach and your discipline, choose one strategy you can implement next term and another you'll spend more time learning about:
a. Infuse integrity into lessons and assessments
b. Align expectations with assessment rubrics
c. Allow and co-opt collaboration
d. Give opportunities for revision
e. Give students choice and control
f. Make your assessments authentic
g. Plan for cognitive offloading
h. Include oral assessments
2. If you have already read the course design and communicating integrity chapters, consider how your chosen strategy connects to the ones you chose from them.
3. Play with some GenAl tools to plan how they might help you deploy your chosen strategy.
4. For administrators, provide professional development opportunities for faculty interested in creating grading rubrics. Provide the infrastructure to enable faculty to share rubrics, assignments, and other assessment tools.
5. Also for administrators, consider making instructional designers available to help instructors design or redesign in-person, hybrid, and online courses.
STRATEGIES THAT PROMOTE SUCCESS WITH INTEGRITY
Next Steps
1. Reflect on these strategies. Based on the classes you teach and your discipline, choose one strategy you can implement next term and another you'll spend more time learning about:
a. Model the behaviors you want to see
b. Be engaging and intentional
c. Be present as an instructor
d. Create a sense of belonging
e. Engage in universal learning design to make your class more accessible
f. Develop teacher metacognition
2. If you have already read the assessment design, course design, and communicating integrity chapters, consider how your chosen strategy connects to strategies you selected in those chapters.
3. Make a presence worksheet for one of your classes.
Observe how and whether you are present, either in person or through class structures, and make changes to create a more vibrant community of learners.
4. For institutional leaders, ask yourself how you are modeling integrity on a daily basis and in front of your instructors and students. Is your institution creating a sense of belonging for all students, and if so, how are the institutional efforts helping (or not helping) class cultures? Finally, do instructors have sufficient support to make their classes more accessible, or are you unintentionally creating an accommodation-dependent culture?
PROTECTING
ASSESSMENT INTEGRITY
Students could write some of the test questions used in assessment, which offloads work that the instructor must do to write and rewrite
Getting to know students through icebreakers can pull double duty if they are moving around the room, would you rather style, answering questions like “would you rather give an oral presentation or show a side by side coding comparison in R?” So that you can get them thinking about the form/content of the class, while they identify like minded peers.
Next Steps
1. Interrogate your learning objectives to determine which are still valid and which need to be updated given the existence of GenAl.
2. Examine your assessments in light of what you have decided about your learning objectives. Are the assessments still valid or do you need to redesign any of them? Which are assessments of learning (summative rather than formative) and thus need to be secured?
3. For any assessment you are redesigning, consider whether any part of it can or should be cognitively offloaded to GenAl.
4. For summative assessments or assessments that students need to complete without the aid of GenAI, choose at least one of the following strategies for securing them:
a. Generating new questions every term
b. Using randomization techniques
c. Deploying technology (e.g., lockdown browsers)
d. Proctoring students as they complete the assessment
5. For administrators, consider the value of closely exam. ining assessment security tools that your instructors might use. Make sure that the tools you're considering meet the criteria we've outlined before buying or renewing your contracts.
6. Also for institutional leaders, examine the value of establishing a computer-based testing facility on your campus that provides students with consistent and secure testing conditions, as well as of purchasing assessment software like Prairie Learn that enables instructors to individualize and randomize assessment questions.
INFUSING ETHICS INTO TEACHING AND LEARNING
1. Cheating in assignments should earn a 0, while an honest try should still score higher. Maybe late work allows for a turn in with a deduction, but not worse than cheating would merit
CONCLUSION
1. Revise how you think and talk about integrity
2. Refocus on learning
3. Rethink your educational persona
4. Reconsider the nature and point of assessment
5. Reimagine how you show up for your students
6. Revisit assessment security for a new era
7. Reframe how you respond to cheating
8. Provide quality teaching learning and assessment resources
April 10, 2025
This was written, in part, before Chat-GPT burst onto the scene and it shows. At times, it feels like the authors tacked some prose about generative AI onto an already written draft. In spite of this, they successfully present their central thesis: Establishing a culture of academic integrity requires both explaining its importance and creating standards to preserve it. The authors acknowledge the tension between allowing students to make mistakes in a learning environment while enforcing standards of conduct--a balance that I find challenging in practice. Because the stakes are so high, any suggestion of impropriety is likely to be met with a strenuous defense, especially from law students where there could be implications related to character and fitness for the bar. Sometimes I suspect copying (or, more likely, unsanctioned collaborative work) but would have a very hard time proving it.
Another thing I like about the book is it provides advice on assessment integrity. This is an important topic when it comes to generative AI. While the suggestions in the book are necessarily broad, implementation of these principles needs to be done in course-specific ways. This is a topic I have been thinking about a lot. I want my students to ultimately adopt an attitude of co-intelligence, meaning working with AI collaboratively, but to do so they must learn some skills independent of AI use. That means introductory and advanced courses will likely take different approaches to AI use. It also means that assessments in introductory courses will need to be intentionally designed to minimize cheating by using AI. For me, this means creating the types of non-authentic assessments that I might otherwise avoid.
By situating AI-related integrity concerns in a more comprehensive framework, the book offers useful insights into how to tackle these emerging issues in education. Recommended.
Another thing I like about the book is it provides advice on assessment integrity. This is an important topic when it comes to generative AI. While the suggestions in the book are necessarily broad, implementation of these principles needs to be done in course-specific ways. This is a topic I have been thinking about a lot. I want my students to ultimately adopt an attitude of co-intelligence, meaning working with AI collaboratively, but to do so they must learn some skills independent of AI use. That means introductory and advanced courses will likely take different approaches to AI use. It also means that assessments in introductory courses will need to be intentionally designed to minimize cheating by using AI. For me, this means creating the types of non-authentic assessments that I might otherwise avoid.
By situating AI-related integrity concerns in a more comprehensive framework, the book offers useful insights into how to tackle these emerging issues in education. Recommended.
July 4, 2025
This book echoes a lot of already existing best practices, but pieced together with a different focus--how to reduce students' desire and opportunities to cheat. I picked this up because students' use of AI has gotten out of control, including using AI to write personal reflections and metacognition (ironically, both listed among the best practices to avoid such cheating). To be clear, not every student is using AI, and I found it to be generally the same students who would have simply plagiarized in pre-AI days.
I did not appreciate the authors' suggestion to have students use AI to do research on the environmental problems associated with AI. Instead, having students learn to do real research on this real problem is probably better.
There were some interesting tips about flexible deadlines and oral examinations, which I will be doing more research into. But, the bottom line is that the authors really emphasize revising classes to a "mastery orientation" (also called "competency-based education"), which is extremely labor-intensive: give students the choice of their assessments and their grades, give more frequent, lower-stakes assignments, offer them multiple attempts to revise assignments, meet with all students individually...I mean, in a world in which I did not have any other obligations, including eating and sleeping, and I had 30 hours in the day, this could work? Is this aimed at faculty who work at non-teaching-intensive institutions?
I'll likely be incorporating some of the recommended items, such as oral exams, but I will never be incorporating AI into my classes until billionaires no longer exist and AI technology has become carbon-neutral.
Geez, I did not mean for this review to sound so snarky. I am burned out. There are some gems in it, and it was a useful refocusing of best practices towards a discussion of academic honesty. But it also had really high expectations for faculty and as such I think is not going to be easily implemented by faculty at teaching-intensive institutions.
I did not appreciate the authors' suggestion to have students use AI to do research on the environmental problems associated with AI. Instead, having students learn to do real research on this real problem is probably better.
There were some interesting tips about flexible deadlines and oral examinations, which I will be doing more research into. But, the bottom line is that the authors really emphasize revising classes to a "mastery orientation" (also called "competency-based education"), which is extremely labor-intensive: give students the choice of their assessments and their grades, give more frequent, lower-stakes assignments, offer them multiple attempts to revise assignments, meet with all students individually...I mean, in a world in which I did not have any other obligations, including eating and sleeping, and I had 30 hours in the day, this could work? Is this aimed at faculty who work at non-teaching-intensive institutions?
I'll likely be incorporating some of the recommended items, such as oral exams, but I will never be incorporating AI into my classes until billionaires no longer exist and AI technology has become carbon-neutral.
Geez, I did not mean for this review to sound so snarky. I am burned out. There are some gems in it, and it was a useful refocusing of best practices towards a discussion of academic honesty. But it also had really high expectations for faculty and as such I think is not going to be easily implemented by faculty at teaching-intensive institutions.
August 9, 2025
The book is a solid resource for all teachers in higher education. I was happy with many of the suggestions that the authors provided regarding overall classroom integrity, trust, and transparency - particularly because I already utilize these tools in my classes. However, I was looking for very specific information on tackling/preventing AI. The authors, and rightly so, spent much of the book focusing on why AI is used to begin with. After reading the book, I’ve come to the conclusion that there has to a be different approach for each discipline, and clearly High Ed needs to take a new approach to teaching. I do intend to take a few suggestions from the authors and implement changes in my syllabus (due dates for example). Overall, I am happy I read the book and discussed it with colleagues , but still do not feel I have clear-cut answers. Maybe that is asking too much of the authors (especially since a new version of ChatGPT - GPT-5- was just this week).
Read
October 20, 2025Interesting read but will be dispiriting to anyone looking for a quick fix (because there isn’t one). The subtitle suggests a heavy focus on AI which isn’t evident in the text; it’s much more focused on general best practices to prevent cheating or deal with it once it’s happened. Occasionally something is tacked on that relates to AI. All becomes clearer in the conclusion, where the authors write about drafting the book before chatGPT was released, then revising while chatGPT was around and rapidly being developed and adopted. I do think their ideas are useful in the context of genAI, but anyone looking for specific guidance around handling genAI in their classes will probably be disappointed.
May 17, 2025
Overall great book with useful ideas and discussions about better teaching methods to discourage cheating as well as how to deal with it when it happens. They do discuss AI, but it’s clear the book had been mostly written before AI had become ubiquitous. This book could really benefit from more specifics about how to handle AI misconduct, especially in online courses. Still, a good and useful read.
March 30, 2026
It was very clear that this book was started before ChatGPT was on the scene. Some of the bits about AI felt like such an afterthought. Especially early on the book felt more like it was just about cheating and not about AI.
I was hoping for novel ways to think about AI in terms of meeting high educational standards and creating meaningful pedagogy but I was very let down by this. This book was about cheating. Not "the opposite of cheating".
I was hoping for novel ways to think about AI in terms of meeting high educational standards and creating meaningful pedagogy but I was very let down by this. This book was about cheating. Not "the opposite of cheating".
September 20, 2025
This was a smart and practical way of thinking about ways of mitigating cheating in contemporary times. In addition to being full of strategies, what I especially appreciated was the approach to thinking about cheating that acknowledged that it is something that nearly everyone is inclined to do given certain conditions.
January 9, 2026
nothing new for me, as an educational psychologist who regularly presents on this topic already... but a great overview/ resource overall!! All educators would benefit from thinking about cheating and academic integrity in a more holistic, contextual way and priactively designing their course policies, assignments, and interactions with students with these principles in mind.
January 23, 2026
Read this for work. An interesting read about why students cheat, and how to prevent it in the age of AI. Flexibility and teaching ethics stood out to me here.
Luckily, I'm not a teacher who actually has to apply these strategies in the real world. Depressing and disheartening to have to grapple with these tech changes.
Luckily, I'm not a teacher who actually has to apply these strategies in the real world. Depressing and disheartening to have to grapple with these tech changes.
May 3, 2026
Immensely useful, with many good ideas to chew on. I had the pleasure of listening to Tricia Bertram-Gallant speak about this book, and I’m inclined even more to like it because of her deep thinking, practicality, and unabashed criticism of genAI’s many faults.
August 26, 2025
A great read heading into my first semester teaching. Definitely going to incorporate some of their strategies!
October 30, 2025
A really great read which practical ideas on how education needs to pivot in the AI world. I can see myself returning to this as a reference.
November 11, 2025
Reminded me of a lot of things we told faculty during the pandemic. some good tips but nothing new or earth shattering.
December 23, 2025
I thought this book was great! I highly recommend if you work in education.
January 22, 2026
Important, but rather depresssing.
March 27, 2026
This book is filled with good ideas for faculty who want to think strategically about how to structure assignments in an AI world.
April 21, 2026
If you're in higher ed, this is a very useful book to read and reference!
July 14, 2025
As a writing professor at a mid-sized university, I was part of two interdisciplinary summer reading groups that chose this book for discussion. Both groups were intensely focused on questions around cheating-with-AI. This book inspired excellent discussions. There isn't much that I found "new" in terms of material or pedagogical practice, but some of the graduate students in the group did. More broadly, the points the authors raise about why students cheat and how instructors can develop student-focused learning environments and learning objectives were at the heart of our discussions and takeaways. I'd recommend this book for other like-minded book groups.
May 27, 2025
Gamechanger
Displaying 1 - 24 of 24 reviews