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Mike Perkins; Jasper Roe; Binh H. Vu; Darius Postma; Don Hickerson; James McGaughran; Huy Q. Khuat – International Journal of Educational Technology in Higher Education, 2024
This study investigates the efficacy of six major Generative AI (GenAI) text detectors when confronted with machine-generated content modified to evade detection (n = 805). We compare these detectors to assess their reliability in identifying AI-generated text in educational settings, where they are increasingly used to address academic integrity…
Descriptors: Artificial Intelligence, Inclusion, Computer Software, Word Processing
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Anna Filighera; Sebastian Ochs; Tim Steuer; Thomas Tregel – International Journal of Artificial Intelligence in Education, 2024
Automatic grading models are valued for the time and effort saved during the instruction of large student bodies. Especially with the increasing digitization of education and interest in large-scale standardized testing, the popularity of automatic grading has risen to the point where commercial solutions are widely available and used. However,…
Descriptors: Cheating, Grading, Form Classes (Languages), Computer Software
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Roseyoana Logisian Subekti; Herdian Herdian; Zalik Nuryana – Electronic Journal of Research in Educational Psychology, 2024
Introduction: This study aimed to investigate the relationship between Achievement Goal Orientation, Self-Efficacy, and Academic Dishonesty among college students during online learning. Method: A total of 238 students from students colleges in Indonesia completed an online questionnaire consisting of scales measuring Achievement Goal Orientation,…
Descriptors: Outcomes of Education, Electronic Learning, Goal Orientation, Self Efficacy
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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
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Slade C. McAfee; Jon-Marc G. Rodriguez – Journal of Chemical Education, 2024
Academic integrity is often a concern instructors have when teaching, with past research indicating the classroom environment is one of the largest factors in determining students' likelihood to cheat. In this commentary, we intend to start a dialogue with instructors regarding the importance of creating a classroom environment that values…
Descriptors: Science Instruction, Chemistry, Undergraduate Study, Course Descriptions
Sinharay, Sandip; Johnson, Matthew S. – Journal of Educational and Behavioral Statistics, 2021
Score differencing is one of the six categories of statistical methods used to detect test fraud (Wollack & Schoenig, 2018) and involves the testing of the null hypothesis that the performance of an examinee is similar over two item sets versus the alternative hypothesis that the performance is better on one of the item sets. We suggest, to…
Descriptors: Probability, Bayesian Statistics, Cheating, Statistical Analysis
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Ucar, Arzu; Dogan, Celal Deha – International Journal of Assessment Tools in Education, 2021
Distance learning has become a popular phenomenon across the world during the COVID-19 pandemic. This led to answer copying behavior among individuals. The cut point of the Kullback-Leibler Divergence (KL) method, one of the copy detecting methods, was calculated using the Youden Index, Cost-Benefit, and Min Score p-value approaches. Using the cut…
Descriptors: Cheating, Identification, Cutting Scores, Statistical Analysis
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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
Sinharay, Sandip; Johnson, Matthew S. – Grantee Submission, 2021
Score differencing is one of six categories of statistical methods used to detect test fraud (Wollack & Schoenig, 2018) and involves the testing of the null hypothesis that the performance of an examinee is similar over two item sets versus the alternative hypothesis that the performance is better on one of the item sets. We suggest, to…
Descriptors: Probability, Bayesian Statistics, Cheating, Statistical Analysis
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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
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Brian W. Stone – Teaching of Psychology, 2025
Background: Students in higher education are using generative artificial intelligence (AI) despite mixed messages and contradictory policies. Objective: This study helps answer outstanding questions about many aspects of AI in higher education: familiarity, usage, perceptions of peers, ethical/social views, and AI grading. Method: I surveyed 733…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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Liandi van den Berg – International Journal for Educational Integrity, 2025
Due to the coronavirus disease 2019 (COVID-2019) and the sudden shift to online learning, higher education institutions adopted various approaches to reduce cheating in online assessments, mainly involving online live proctoring (OLP). The international assessment integrity regulation trend also applied to a university in South Africa, where…
Descriptors: Foreign Countries, College Faculty, College Students, Computer Assisted Testing
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Chaojin Wu – British Journal of Sociology of Education, 2025
Publishing is a critical avenue for scholars and a significant challenge for Chinese doctoral students. This study employs online ethnography to examine discussions on academic publishing anomie in the 'Graduated Group', including interviews with 10 doctoral students to explore the dynamics of academic misconduct. Under the high-pressure…
Descriptors: Publish or Perish Issue, Cheating, Risk Assessment, Doctoral Students
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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
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Olivier Leclerc – Research Evaluation, 2025
Detecting and punishing violations of research integrity requires first having to prove them. However, establishing proof of research misconduct presents a number of challenges. Firstly, it has to be conducted in a variety of contexts, including before research integrity officers, university disciplinary committees, civil courts, criminal courts,…
Descriptors: Cheating, Research, Identification, Integrity
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