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Yang Zhen; Xiaoyan Zhu – Educational and Psychological Measurement, 2024
The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…
Descriptors: Artificial Intelligence, Models, Cheating, Identification
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Flom, Jacalyn; Green, Karen; Wallace, Steven – Active Learning in Higher Education, 2023
Cheating in higher education has numerous negative implications, including degrading program reputations, inflating student retention rates, and cultivating poor ethical practices, all of which have implications for what students do in the workplace after graduation. Therefore, by understanding the current student population, Generation Z, it is…
Descriptors: Cheating, Ethics, Student Behavior, Age Groups
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Muammer Maral – Journal of Academic Ethics, 2024
This research aimed to identify patterns, intellectual structure, contributions, social interactions, gaps, and future research directions in the field of academic integrity (AI). A bibliometric analysis was conducted with 1406 publications covering the period 1966-2023. The results indicate that there has been significant growth in AI literature…
Descriptors: Integrity, Educational History, Cheating, Plagiarism
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Fendler, Richard J.; Yates, Michael C.; Godbey, Jonathan M. – Journal of Instructional Pedagogies, 2023
This research utilizes a unique, validated, multiple-choice exam design that allows researchers to observe and measure the degree to which students copy answers from their peers. Using data collected from the exam, this study investigates whether asking students to sign an honor code at the start of the exam reduced instances of cheating relative…
Descriptors: Cheating, Prevention, Multiple Choice Tests, Ethics
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Lynch, Joan; Salamonson, Yenna; Glew, Paul; Ramjan, Lucie M. – International Journal for Educational Integrity, 2021
In nursing, expectations of honesty and integrity are clearly stipulated throughout professional standards and codes of conduct, thus the concept of academic integrity has even more impetus in preparing students for graduate practice. However, a disparity between policy and practice misses the opportunity to instil the principles of academic…
Descriptors: College Faculty, Teacher Attitudes, Integrity, Cheating
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Gary Lieberman – Journal of Instructional Research, 2024
Artificial intelligence (AI) first made its entry into higher education in the form of paraphrasing tools. These tools were used to take passages that were copied from sources, and through various methods, disguised the original text to avoid academic integrity violations. At first, these tools were not very good and produced nearly…
Descriptors: Artificial Intelligence, Higher Education, Integrity, Ethics
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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
Jing Lu; Chun Wang; Ningzhong Shi – Grantee Submission, 2023
In high-stakes, large-scale, standardized tests with certain time limits, examinees are likely to engage in either one of the three types of behavior (e.g., van der Linden & Guo, 2008; Wang & Xu, 2015): solution behavior, rapid guessing behavior, and cheating behavior. Oftentimes examinees do not always solve all items due to various…
Descriptors: High Stakes Tests, Standardized Tests, Guessing (Tests), Cheating