The Generative Part of GenAI

Working with generative AI presents unique challenges due to its dynamic and ever-changing nature. Unlike traditional sources, generative AI content is constantly evolving, which makes replicating queries, responses, and results difficult. This constant change highlights the importance of thoroughly documenting your use of generative AI in your research, including not only citations but also maintaining a record of the specific queries and responses you've used.

To overcome these challenges and ensure the accuracy and replicability of your work, it's crucial to save and archive all relevant information related to your generative AI interactions. This includes storing your initial queries, AI-generated responses, and any other contextual details that could help demonstrate your use of generative AI. This ensures transparency in the research process and, paired with citations, maintains the integrity of your research and supports your findings in the face of AI's inherent unpredictability.

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.