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Jonathan Hoseana; Andy Leonardo Louismono; Oriza Stepanus – International Journal of Mathematical Education in Science and Technology, 2025
We describe and evaluate a method to mitigate unwanted student collaborations in assessments, which we recently implemented in a second-year undergraduate mathematics module. The method requires a list of specific pairs of students to be prevented from collaborating, which we constructed based on the results of previous assessments. We converted…
Descriptors: Graphs, Color, College Mathematics, Undergraduate Students
Som Nath Ghimire; Upaj Bhattarai; Raj K. Baral – Journal of Academic Ethics, 2024
The problem of academic dishonesty in general and exam cheating in particular, has been ubiquitous in schools, colleges, and universities around the world. This paper reports on the findings from teachers' and students' experiences and perceptions of exam cheating at Nepali schools, colleges, and universities. In so doing, the paper highlights the…
Descriptors: Ethics, Cheating, Foreign Countries, College Students
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
Müge Uluman Mert; Emine Burcu Tunç – International Journal of Assessment Tools in Education, 2023
The aim of this research study was to analyse the relationship among answer-copying tendency, academic self-efficacy, and fear of negative evaluation. To this end, we formed a structural equivalence model, and we evaluated the mediating role of academic self-efficacy between answer-copying tendency and fear of negative evaluation. A total of 562…
Descriptors: Self Efficacy, Cheating, Student Behavior, Foreign Countries
Jo-ann Larkins; Katherine Seaton – Assessment & Evaluation in Higher Education, 2024
That the manifestation of cheating varies between disciplines is rarely discussed, an unspoken assumption being that assessment takes the form of written prose supported by a bibliography. Students and academics from disciplines, such as mathematics, not fitting this model can feel that their work is regarded as an aberration. 'Plagiarism' is not…
Descriptors: Cheating, Mathematics Instruction, Intellectual Disciplines, Plagiarism
Alireza Maleki – Journal of Academic Ethics, 2024
The evaluation of students in online education poses a notable challenge, primarily due to the potential violation of academic integrity caused by various forms of cheating during online examinations. This study aims to explore the perspectives of English as a Foreign Language (EFL) learners on the reasons for online exam cheating. The study was…
Descriptors: English (Second Language), Second Language Learning, Distance Education, Online Courses
Integrity of Best-Answer Assignments in Large-Enrollment Classes: The Role of Compulsory Attribution
Kurt Schmitz; Veda C. Storey – Journal of Teaching and Learning with Technology, 2024
Many instructional methods that focus on analytical, skill, and competency development have a single or small set of appropriate answers. Best-answer assignments are popular for largeenrollment classes because of the relative ease with which scoring and feedback can be managed at scale. However, cheating is regularly confirmed at disturbingly high…
Descriptors: Large Group Instruction, Assignments, Integrity, Student Evaluation
Colette Melissa Kell; Yasmeen Thandar; Adelle Kemlall Bhundoo; Firoza Haffejee; Bongiwe Mbhele; Jennifer Ducray – Journal of Applied Research in Higher Education, 2025
Purpose: Academic integrity is vital to the success and sustainability of the academic project and particularly critical in the training of ethical and informed health professionals. Yet studies have found that cheating in online exams was commonplace during the COVID-19 pandemic. With the increased use of online and blended learning…
Descriptors: Foreign Countries, Universities, Integrity, Cheating
Len Chan – Canadian Journal of Action Research, 2025
Anonymous marking, as a means to mitigate bias in grading, involves evaluating student work with their identities withheld. Anonymous marking is explored in this self-study to mitigate implicit bias, which negated a practitioner-researcher's educational values. The mixed methods action research findings show withholding student identities during…
Descriptors: Grading, Evaluation Methods, Student Evaluation, Bias
Qualitative Assessment of the Views of Academic Honesty among Freshmen in a Physiology-Based Program
Emily J. Ryan; Lori Sherlock; Edward Ryan; Miriam Leary – Advances in Physiology Education, 2025
Academic dishonesty is becoming more common among university students in science, technology, engineering, and mathematics (STEM)-based programs. This is concerning because these students hold positions of responsibility in their professional careers. The purpose of this qualitative study was to examine if a student's academic standing and/or…
Descriptors: College Freshmen, Ethics, Integrity, Cheating
Jiang, Zhuhan; Huang, Jiansheng – IEEE Transactions on Learning Technologies, 2022
Advanced digital technologies and social media have greatly improved both the learning experience and the assessment convenience, while inadvertently facilitated potential plagiarism and collaborative cheating at the same time. In this article, we will focus on the strategies and their technological implementations to run exams, or in-class tests…
Descriptors: Plagiarism, Educational Technology, Computer Assisted Testing, Cheating
Agwu, Prince; Odii, Aloysius; Orjiakor, Tochukwu; Roy, Pallavi; Nzeadibe, Chidi; Onalu, Chinyere; Okoye, Uzoma Odera; Onwujekwe, Obinna – Quality Assurance in Education: An International Perspective, 2022
Purpose: The purpose of this study is to describe the nature and operations of schools commonly regarded as "Miracle Examination Centres (MECs)" in Nigeria, through the lens of stakeholders in education. This study also assessed stakeholders' perspectives on the possible solutions to the problem of MECs. Design/methodology/approach: The…
Descriptors: Foreign Countries, Educational Malpractice, Cheating, Stakeholders
Griffiths, Barry J. – Research on Education and Media, 2022
This pilot study looks at how the author proactively sought to mitigate the issue of cheating when giving online tests during the Spring 2021 semester, at a time when the COVID-19 pandemic forced many teachers around the world to use modalities that involved distance learning. The genesis, implementation and results of the strategy used during the…
Descriptors: Computer Assisted Testing, Supervision, Cheating, Educational Technology
Jasper Roe; Mike Perkins; Gi Kunchana Chonu; Abhishek Bhati – Higher Education Research and Development, 2024
In this article we report on a study of higher education students' (N = 256) perceptions on the willingness, pressure, and frequency of their peers to cheat in online assessments at an Australian university in Singapore during the COVID-19 induced Online Teaching and Assessment period (COTA). MANOVA was used to identify the differences in…
Descriptors: Student Attitudes, Cheating, COVID-19, Pandemics