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Direct linkMulisa, Feyisa; Ebessa, Asrat Dereb – Cogent Education, 2021
There has been a growing interest in determining whether dishonesty in college can be transferred to the professional workplace. There have been few, yet scarce, studies that focused on the link between college and workplace dishonesty. This review aims to bring into the limelight evidence-based consistency of the links between college and…
Descriptors: Ethics, College Students, Student Behavior, Employees
Ehren Helmut Pflugfelder; Joshua Reeves – Journal of Technical Writing and Communication, 2024
The use of generative artificial intelligence (GAI) large language models has increased in both professional and classroom technical writing settings. One common response to student use of GAI is to increase surveillance, incorporating plagiarism detection services or banning certain composing activities from the classroom. This paper argues such…
Descriptors: Technical Writing, Artificial Intelligence, Supervision, Teaching Methods
Jiahui Luo – Assessment & Evaluation in Higher Education, 2024
This study offers a critical examination of university policies developed to address recent challenges presented by generative AI (GenAI) to higher education assessment. Drawing on Bacchi's 'What's the problem represented to be' (WPR) framework, we analysed the GenAI policies of 20 world-leading universities to explore what are considered problems…
Descriptors: Artificial Intelligence, Educational Policy, College Students, Student Evaluation
Sari Atmini; Ruzita Jusoh; Arum Prastiwi; Setyo Tri Wahyudi; Kurniasari Novi Hardanti; Nadafajar Nurmani'ah Widiarti – Cogent Education, 2024
This research investigates the factors influencing plagiarism from the perspective of the fraud diamond framework. It aims to obtain empirical evidence that higher pressure, opportunity, rationalization, and competencies influence an increase in plagiarism. Currently, information technology has rapidly advanced, and artificial intelligence has…
Descriptors: Plagiarism, Accounting, Deception, Guidelines
Christophe O. Soulage; Fabien Van Coppenolle; Fitsum Guebre-Egziabher – Advances in Physiology Education, 2024
Artificial intelligence (AI) has gained massive interest with the public release of the conversational AI "ChatGPT," but it also has become a matter of concern for academia as it can easily be misused. We performed a quantitative evaluation of the performance of ChatGPT on a medical physiology university examination. Forty-one answers…
Descriptors: Medical Students, Medical Education, Artificial Intelligence, Computer Software
Patrik Holm; Ulrik Terp; Christina Fjaeraa Alfredsson – Discover Education, 2025
Academic dishonesty is a growing problem in higher education. This study examines students' attitudes toward cheating. The sample consisted of 318 students enrolled in health science courses at a Swedish university. A survey-based quantitative approach was employed, integrating qualitative responses from open-ended questions. We investigated…
Descriptors: Cheating, Student Attitudes, College Students, Tests
Sam Sedaghat – Journal of Academic Ethics, 2025
Chatbots such as ChatGPT have the potential to change researchers' lives in many ways. Despite all the advantages of chatbots, many challenges to using chatbots in medical research remain. Wrong and incorrect content presented by chatbots is a major possible disadvantage. The authors' credibility could be tarnished if wrong content is presented in…
Descriptors: Plagiarism, Artificial Intelligence, Medical Research, Error Patterns
Download full textMartosenjoyo, Triyatni – Education Quarterly Reviews, 2020
Through genetic tracing, the origins of a person and who their ancestors are can be traced scientifically even though over time their genes have evolved following ecological changes. Likewise, a person's ideas can be traced where the origin comes from through memetic tracing. This article discusses case studies in several works which are assumed…
Descriptors: Architecture, Building Design, Plagiarism, Foreign Countries
Farahian, Majid; Avarzamani, Farnaz; Rezaee, Mehrdad – Journal of Applied Research in Higher Education, 2022
Purpose: Many scholars have recognized the cultural dependency of the concept of plagiarism and have investigated the influence of cultural attitude on university students' plagiarism; however, since the findings are inconsistent and because plagiarism is a major concern in academic institutions in Asia, we were motivated to examine the…
Descriptors: Plagiarism, Cross Cultural Studies, College Second Language Programs, College Students
Parkinson, Ann L.; Hatje, Eva; Kynn, Mary; Kuballa, Anna V.; Donkin, Rebecca; Reinke, Nicole B. – Assessment & Evaluation in Higher Education, 2022
Academic integrity is important, not just in the university setting but beyond, as students graduate and move into professional fields. Discrepancies in the understanding of what constitutes academic dishonesty exist between institutional policies, discipline areas and individual educators, which creates challenges for students trying to uphold…
Descriptors: Integrity, Cheating, Ethics, Plagiarism
Lim, Kieran Fergus – Physics Education, 2022
Undergraduate first-year courses are often mandatory for students in a variety of majors and degrees. Many students view these core courses as of little interest and relevance, which is associated with lack of motivation for study and can lead to cheating. Contract cheating in text-based is difficult to detect and prove. Contract cheating in…
Descriptors: College Freshmen, Contracts, Cheating, Assignments
Domingues, Ivo – Higher Education Research and Development, 2022
Theories concerned with plagiarism issues recognise the need for a holistic approach. However, the literature reviewed does not propose such a theory but relies on reductionist approaches. In this regard, a holistic theory for analysing plagiarism, based on non-reductionist approaches that focus on the agency performed at the micro-level, is…
Descriptors: Holistic Approach, Higher Education, Plagiarism, Personal Autonomy
Johansen, Mikkel Willum; Goddiksen, Mads Paludan; Centa, Mateja; Clavien, Christine; Gefenas, Eugenijus; Globokar, Roman; Hogan, Linda; Merit, Marcus Tang; Nielsen, Soren Saxmose; Olsson, I. Anna S.; Poskute, Margarita; Quinn, Una; Santos, Júlio Borlido; Santos, Rita; Schöpfer, Céline; Strahovnik, Vojko; Wall, P. J.; Sandoe, Peter; Lund, Thomas Boker – International Journal for Educational Integrity, 2022
Plagiarism and other transgressions of the norms of academic integrity appear to be a persistent problem among upper secondary students. Numerous surveys have revealed high levels of infringement of what appear to be clearly stated rules. Less attention has been given to students' understanding of academic integrity, and to the potential…
Descriptors: Foreign Countries, Secondary School Students, Integrity, Cheating
Morrison, Ryan – Online Submission, 2022
Large Language Models (LLM) -- powerful algorithms that can generate and transform text -- are set to disrupt language learning education and text-based assessments as they allow for automation of text that can meet certain outcomes of many traditional assessments such as essays. While there is no way to definitively identify text created by this…
Descriptors: Models, Mathematics, Automation, Natural Language Processing
Vieyra, Michelle L.; Weaver, Kari D. – Issues in Science and Technology Librarianship, 2023
Students often come to college with a limited understanding of how to ethically incorporate and cite source materials in their writing, and this is commonly cited as the leading reason for plagiarism. Studies have shown that students in STEM are more apt to plagiarize as compared to students in the humanities or social sciences, so they are an…
Descriptors: STEM Education, Plagiarism, Ethics, Citations (References)
