Academic Integrity In The Age Of Artificial Intelligence
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Academic Integrity in the Age of Artificial Intelligence
Powerful generative Artificial Intelligence (AI) has defined and transformed our modern era, and the fundamental conceptualization of academia stands at a crossroads. Academic Integrity in the Age of Artificial Intelligence delves deep into the seismic shifts and intricate challenges brought forth by the proliferation of AI technologies, exploring the intricacies between innovation and integrity. The rise of generative AI, exemplified by ChatGPT, has set a cascade of change across diverse sectors, including higher education, medicine, and the arts. This book dissects the multifaceted impact of AI on the academic landscape. With AI's ability to craft text and imagery mirroring human creativity, the lines between authentic scholarship and synthetic deception blur. The book examines the delicate balance between productivity and ethics while weaving a comprehensive tapestry of insights from various stakeholders. From academics grappling with the definition of AI-assisted breaches of academic integrity to policymakers reshaping the future of higher education, this book engages a myriad of voices. It scrutinizes the nascent challenges in assessment design, the urgent need to update antiquated integrity policies, and the importance of research ethics in an AI-driven world. This book is ideal for educators, policymakers, students, and technologists through the complicated terrain of AI ethics.
The Opposite of Cheating
Author: Tricia Bertram Gallant
language: en
Publisher: University of Oklahoma Press
Release Date: 2025-03-11
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.
Artificial Intelligence, Pedagogy and Academic Integrity
This book addresses the implications of artificial intelligence for teaching, learning and academic integrity in higher education. It explores policies about the use of Generative Artificial Intelligence (GenAI), describes how to teach writing in the era of GenAI, and how instructors can design courses and assessments that prevent plagiarism while building the necessary skills for critical thinking and writing. Together, the chapters include research results, case studies, teaching methodologies, course design ideas, analysis of power and gatekeeping, and best practices related to GAI from a diverse range of researchers from English and French Canada, the United States, England, Ukraine and Croatia. The authors approach the advent and rapid spread of GenAI in higher education by examining its use from different perspectives with a particular focus on its impact on academic integrity. Taking a communication studies approach, consideration is given to the role GenAI might play disrupting power structures in universities to improve access for students who are non-traditional or English Language Learners. The book also explores how reimagining teaching methodologies can help to mitigate academic integrity violations due to misuse of GenAI and to teach students to use GenAI with integrity as a research and brainstorming tool. Students need to learn how to assess the reliability of GenAI’s output as the develop the skills for research and writing. Methods of teaching writing and research skills using GenAI are explored in an effort to ensure that critical thinking skills are developed successfully. Most instructors who use writing-intensive assessments believe that essential critical thinking skills are developed via the writing process; often, ideas become concrete as one writes about them. Teaching with GenAI can provide opportunities for instructors to guide their students into a deeper analysis and critique of their research.