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R. Harrad; R. Keasley; L. Jefferies – Higher Education Research and Development, 2024
Academic misconduct and academic integrity are issues of importance to Higher Education Institutions (HEIs). Phraseologies and practices may conflate unintentional mistakes with attempts to gain illegitimate advantage, with some groups potentially at higher risk. HEIs across the United Kingdom (UK) responded to a Freedom of Information Act (FOI)…
Descriptors: Integrity, Cheating, College Students, Student Characteristics
Mike Perkins; Jasper Roe; Darius Postma; James McGaughran; Don Hickerson – Journal of Academic Ethics, 2024
This study explores the capability of academic staff assisted by the Turnitin Artificial Intelligence (AI) detection tool to identify the use of AI-generated content in university assessments. 22 different experimental submissions were produced using Open AI's ChatGPT tool, with prompting techniques used to reduce the likelihood of AI detectors…
Descriptors: Artificial Intelligence, Student Evaluation, Identification, Natural Language Processing
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
Elkhatat, Ahmed M.; Elsaid, Khaled; Almeer, Saeed – International Journal for Educational Integrity, 2021
One of the main goals of assignments in the academic environment is to assess the students' knowledge and mastery of a specific topic, and it is crucial to ensure that the work is original and has been solely made by the students to assess their competence acquisition. Therefore, Text-Matching Software Products (TMSPs) are used by academic…
Descriptors: Plagiarism, Identification, Assignments, Computer Software
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
Cingillioglu, Ilker – International Journal of Information and Learning Technology, 2023
Purpose: With the advent of ChatGPT, a sophisticated generative artificial intelligence (AI) tool, maintaining academic integrity in all educational settings has recently become a challenge for educators. This paper discusses a method and necessary strategies to confront this challenge. Design/methodology/approach: In this study, a language model…
Descriptors: Artificial Intelligence, Essays, Integrity, Cheating
Rowena Harper; Felicity Prentice – International Journal for Educational Integrity, 2024
Teaching staff play a pivotal role in the prevention, detection and management of cheating in higher education. They enact curriculum and assessment design strategies, identify and substantiate suspected cases, and are positioned by many as being on the 'front line' of a battle that threatens to undermine the integrity of higher education. Against…
Descriptors: College Faculty, Teacher Attitudes, Cheating, Prevention
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
Dawson, Phillip; Sutherland-Smith, Wendy; Ricksen, Mark – Assessment & Evaluation in Higher Education, 2020
Contract cheating happens when students outsource their assessed work to a third party. One approach that has been suggested for improving contract cheating detection is comparing students' assignment submissions with their previous work, the rationale being that changes in style may indicate a piece of work has been written by somebody else. This…
Descriptors: Cheating, Identification, Accuracy, Computer Software
Oravec, Jo Ann – Education Policy Analysis Archives, 2022
Cheating behaviors have been construed as a continuing and somewhat vexing issue for academic institutions as they increasingly conduct educational processes online and impose metrics on instructional evaluation. Research, development, and implementation initiatives on cheating detection have gained new dimensions in the advent of artificial…
Descriptors: Artificial Intelligence, Bibliometrics, Cheating, Identification
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
Emery-Wetherell, Meaghan; Wang, Ruoyao – Assessment & Evaluation in Higher Education, 2023
Over four semesters of a large introductory statistics course the authors found students were engaging in contract cheating on Chegg.com during multiple choice examinations. In this paper we describe our methodology for identifying, addressing and eventually eliminating cheating. We successfully identified 23 out of 25 students using a combination…
Descriptors: Computer Assisted Testing, Multiple Choice Tests, Cheating, Identification
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
Editorial Projects in Education, 2024
Addressing academic integrity in the age of AI is essential to ensure honesty and student success. This Spotlight will help you learn about how educators nationwide are approaching AI in teaching and learning; review data investigating how many students are actually using AI to cheat; examine strategies teachers are using to fight AI cheating;…
Descriptors: Integrity, Artificial Intelligence, Teaching Methods, Computer Software
Kasler, Jonathan; Sharabi-Nov, Adi; Shinwell, Eric S.; Hen, Meirav – International Journal for Educational Integrity, 2023
Research has indicated the importance of internal motivation as a factor in reducing academic misconduct in higher education and some commentators have also cited prosocial values as buffers against the temptation to cheat. In light of this research, the goal of the present research was to study the roles of motivation and prosocial values in…
Descriptors: Cheating, Prosocial Behavior, Prevention, Social Values
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