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Fatma Basalan Iz; Rahime Aslankoç; Günferah Sahin – Journal of Academic Ethics, 2024
Cheating in higher education is a significant problem. The study aims to determine nursing students' attitudes and opinions toward cheating in exams. The type of research is descriptive. The research data were collected in the classroom environment of 716 students in day and evening education programs. The research data were collected using…
Descriptors: Nursing Education, Student Attitudes, Cheating, Evening Programs
Ebru Balta; Celal Deha Dogan – SAGE Open, 2024
As computer-based testing becomes more prevalent, the attention paid to response time (RT) in assessment practice and psychometric research correspondingly increases. This study explores the rate of Type I error in detecting preknowledge cheating behaviors, the power of the Kullback-Leibler (KL) divergence measure, and the L person fit statistic…
Descriptors: Cheating, Accuracy, Reaction Time, Computer Assisted Testing
Xu, Yujun; Li, Wenlong – Journal of Academic Ethics, 2023
This paper provides a systematic and critical review of the existing literature on the phenomenon of 'commercial contract cheating' (CCC). Unlike some existing systematic reviews generally on CCC, this paper focuses on the potential causes and suggested preventative measures specifically, intending to develop effective interventions on the basis…
Descriptors: Prevention, Cheating, Contracts, Outsourcing
Grochowalski, Joseph H.; Hendrickson, Amy – Journal of Educational Measurement, 2023
Test takers wishing to gain an unfair advantage often share answers with other test takers, either sharing all answers (a full key) or some (a partial key). Detecting key sharing during a tight testing window requires an efficient, easily interpretable, and rich form of analysis that is descriptive and inferential. We introduce a detection method…
Descriptors: Identification, Cooperative Learning, Cheating, Statistical Analysis
Zhao, Li; Zheng, Yi; Zhao, Junbang; Li, Guoqiang; Compton, Brian J.; Zhang, Rui; Fang, Fang; Heyman, Gail D.; Lee, Kang – Child Development, 2023
Academic cheating is common, but little is known about its early emergence. It was examined among Chinese second to sixth graders (N = 2094; 53% boys, collected between 2018 and 2019) using a machine learning approach. Overall, 25.74% reported having cheated, which was predicted by the best machine learning algorithm (Random Forest) at a mean…
Descriptors: Cheating, Elementary School Students, Artificial Intelligence, Foreign Countries
Leon Katcharian – ProQuest LLC, 2023
Remotely proctored online examinations proliferate in academic and corporate learning environments (Grajek, 2020). Remote (virtual) proctoring allows organizations to efficiently offer tests globally while reducing the costs of proctored testing generally associated with traditional paper-and-pencil and computer-based testing center examinations.…
Descriptors: Computer Assisted Testing, Supervision, Distance Education, Information Security
Kristina M. Brimer – ProQuest LLC, 2023
The study aimed to explore whether cultural dimensions [horizontal individualism (H-I), vertical individualism (V-I), horizontal collectivism (H-C), and vertical collectivism (V-C)] and gender identity predict academic dishonesty tendencies (cheating, copying, collusion) in higher education learners. Using a quantitative approach, participants…
Descriptors: Higher Education, Sexual Identity, Predictor Variables, Cheating
Oravec, Jo Ann – Journal of Interactive Learning Research, 2023
Cheating is a growing academic and ethical concern in higher education. The technological "arms race" that involves cheating-detection system developers versus technology-savvy students is attracting increased attention to cheating issues; it is also generating iterations of technological innovations as corporations, higher educational…
Descriptors: Artificial Intelligence, Cheating, Educational Technology, Ethics
Nodir Adilov; Jeffrey W. Cline; Hui Hanke; Kent Kauffman; Lisa Meneau; Elva Resendez; Shubham Singh; Mike Slaubaugh; Nichaya Suntornpithug – Journal of Education for Business, 2024
This article develops an index to measure the level of susceptibility of courses to cheating using ChatGPT (Chat Generative Pre-trained Transformer), an advanced text-based artificial intelligence (AI) language model. It demonstrates the application of the index to a sample of business courses in a mid-sized university. The study finds that the…
Descriptors: Artificial Intelligence, Cheating, Risk Assessment, Measurement
Bor Luen Tang – Research Ethics, 2024
Scientific research is supposed to acquire or generate knowledge, but such a purpose would be severely undermined by instances of research misconduct (RM) and questionable research practices (QRP). RM and QRP are often framed in terms of moral transgressions by individuals (bad apples) whose aberrant acts could be made conducive by shortcomings in…
Descriptors: Scientific Research, Ethics, Integrity, Cheating
James Stacey Taylor – Journal of Academic Ethics, 2024
I argue that wrong of plagiarism does not primarily stem from the plagiarist's illicit misappropriation of academic credit from the person she plagiarized. Instead, plagiarism is wrongful to the degree to which it runs counter to the purpose of academic work. Given that this is to increase knowledge and further understanding plagiarism will be…
Descriptors: Plagiarism, Cheating, Citations (References), Primary Sources
Xiao Pan Ding; Joey Kei Teng Cheng; Qiqi Cheng; Gail D. Heyman – Applied Developmental Science, 2024
Stories are widely used around the world to try to teach children moral lessons. However, it is often difficult for children to figure out how lessons from stories can be applied to real-life settings. In the present research, we tested whether encouraging children to be like the protagonists helps explain the success of positive moral stories…
Descriptors: Moral Values, Values Education, Story Telling, Ethics
Zhao, Li; Li, Yingying; Sun, Wenjin; Zheng, Yi; Harris, Paul L. – Developmental Science, 2023
There is extensive research on the development of cheating in early childhood but research on how to reduce it is rare. The present preregistered study examined whether telling young children about a story character's emotional reactions towards cheating could significantly reduce their tendency to cheat (N = 400; 199 boys; Age: 3-6 years).…
Descriptors: Psychological Patterns, Ethics, Cheating, Incidence
Bailey, John – Education Next, 2023
This article reports on the release of AI tools that can generate text, images, music, and video with no need for complicated coding but simply in response to instructions given in natural language. AI is also raising pressing ethical questions around bias, appropriate use, and plagiarism. In the realm of education, this technology will influence…
Descriptors: Artificial Intelligence, Technology Uses in Education, Barriers, Affordances
Farida Agus Setiawati; Tria Widyastuti; Kartika Nur Fathiyah; Tiara Shafa Nabila – European Journal of Psychology and Educational Research, 2024
Data obtained through questionnaires sometimes respond to the items presented by social norms, so sometimes they do not suit themselves. High social desirability (SD) in non-cognitive measurements will cause item bias. Several ways are used to reduce item bias, including freeing respondents from not writing their names or being anonymous,…
Descriptors: Social Desirability, Test Bias, Self Concept, Undergraduate Students