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Mike Perkins; Jasper Roe; Binh H. Vu; Darius Postma; Don Hickerson; James McGaughran; Huy Q. Khuat – International Journal of Educational Technology in Higher Education, 2024
This study investigates the efficacy of six major Generative AI (GenAI) text detectors when confronted with machine-generated content modified to evade detection (n = 805). We compare these detectors to assess their reliability in identifying AI-generated text in educational settings, where they are increasingly used to address academic integrity…
Descriptors: Artificial Intelligence, Inclusion, Computer Software, Word Processing
Mike Richards; Kevin Waugh; Mark A Slaymaker; Marian Petre; John Woodthorpe; Daniel Gooch – ACM Transactions on Computing Education, 2024
Cheating has been a long-standing issue in university assessments. However, the release of ChatGPT and other free-to-use generative AI tools has provided a new and distinct method for cheating. Students can run many assessment questions through the tool and generate a superficially compelling answer, which may or may not be accurate. We ran a…
Descriptors: Computer Science Education, Artificial Intelligence, Cheating, Student Evaluation
Mengkorn Pum; Sarin Sok – Asian Journal of Distance Education, 2024
With current state-of-the-art advances in artificial intelligence (AI), especially large language models, such as Google's Gemini, Microsoft's Copilot, and ChatGPT, among others, a plethora of research on this phenomenon has been conducted worldwide aiming to examine its limitations, benefits and ethical implications. Nonetheless, such a…
Descriptors: Foreign Countries, Artificial Intelligence, Technology Uses in Education, Computer Software
Marks, Anthony M.; Cronje, Johannes C. – Educational Technology & Society, 2008
Computer-based assessments are becoming more commonplace, perhaps as a necessity for faculty to cope with large class sizes. These tests often occur in large computer testing venues in which test security may be compromised. In an attempt to limit the likelihood of cheating in such venues, randomised presentation of items is automatically…
Descriptors: Educational Assessment, Educational Testing, Research Needs, Test Items
Cizek, Gregory J. – 2003
This book provides a resource for everything educators need to know about classroom cheating. Six chapters include: (1) "What Do We Know About Cheating in the Classroom" (who is cheating and why); (2) "Why is Cheating a Problem?" (e.g., the ubiquity and the consequences of cheating); (3) "How Does Cheating Occur?"…
Descriptors: Cheating, Classroom Environment, Codes of Ethics, Computer Software
Hamilton, Margaret; Richardson, Joan – Journal of Learning Design, 2007
In this paper, we discuss the role of the educator in terms of designing a learning environment for the student which encourages the student to develop their own academic integrity. In such an environment, there is no need for the student to resort to plagiarism, as the learning and assessment tasks are not conducive to cheating, being unique and…
Descriptors: Foreign Countries, Plagiarism, Student Evaluation, Cheating
Watson, John F. – North American Council for Online Learning, 2007
Online learning is growing rapidly across the United States within all levels of education, as more and more students and educators become familiar with the benefits of learning unconstrained by time and place. Across most states and all grade levels, students are finding increased opportunity, flexibility, and convenience through online learning.…
Descriptors: Definitions, Educational Resources, Student Evaluation, Educational Assessment