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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
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
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
Ibrahim Adeshola; Adeola Praise Adepoju – Interactive Learning Environments, 2024
The launch of OpenAI ChatGPT's language-generation model has raised alarms within many sectors, especially the academic sector. Several academicians have urged universities to develop new forms of assessment after the launch of ChatGPT, which solves academic questions in less than a few minutes. Academic cheating is not a new phenomenon, and the…
Descriptors: Opportunities, Barriers, Artificial Intelligence, Natural Language Processing
Lydia Arnold; James Croxford – Teaching in Higher Education, 2025
Authentic assessment is a widely discussed concept in higher education, but it has a problem: the concept has become so all-encompassing that its meaning is now unclear. The notion has been expanded and diluted. For example, adding social justice to the definition or positioning exams as authentic, adds to the contradictions inherent within in the…
Descriptors: Performance Based Assessment, Higher Education, Vocabulary, Evaluation Methods
Matthew Landers – Higher Education for the Future, 2025
This article presents a brief overview of the state-of-the-art in large language models (LLMs) like ChatGPT and discusses the difficulties that these technologies create for educators with regard to assessment. Making use of the 'arms race' metaphor, this article argues that there are no simple solutions to the 'AI problem'. Rather, this author…
Descriptors: Ethics, Cheating, Plagiarism, Artificial Intelligence
Debby R. E. Cotton; Peter A. Cotton; J. Reuben Shipway – Innovations in Education and Teaching International, 2024
The use of artificial intelligence in academia is a hot topic in the education field. ChatGPT is an AI tool that offers a range of benefits, including increased student engagement, collaboration, and accessibility. However, is also raises concerns regarding academic honesty and plagiarism. This paper examines the opportunities and challenges of…
Descriptors: Integrity, Cheating, Artificial Intelligence, Man Machine Systems
Shashi Nallaya; Sheridan Gentili; Scott Weeks; Katherine Baldock – Issues in Educational Research, 2024
Various factors such as regulatory body mandates, graduate employability challenges, decreasing student engagement and increasing academic misconduct in higher education have motivated universities to explore alternative approaches to teach and assess. Accordingly, the oral assessment has taken precedence in many contexts as a popular form of…
Descriptors: Test Validity, Test Reliability, Cheating, Higher Education
Edmund De Leon Evangelista – Contemporary Educational Technology, 2025
The rapid advancement of artificial intelligence (AI) technologies, particularly OpenAI's ChatGPT, has significantly impacted higher education institutions (HEIs), offering opportunities and challenges. While these tools enhance personalized learning and content generation, they threaten academic integrity, especially in assessment environments.…
Descriptors: Artificial Intelligence, Integrity, Educational Strategies, Natural Language Processing
Esteban Guevara Hidalgo – International Journal for Educational Integrity, 2025
The COVID-19 pandemic had a profound impact on education, forcing many teachers and students who were not used to online education to adapt to an unanticipated reality by improvising new teaching and learning methods. Within the realm of virtual education, the evaluation methods underwent a transformation, with some assessments shifting towards…
Descriptors: Foreign Countries, Higher Education, COVID-19, Pandemics
Martin Braun – New Directions in the Teaching of Natural Sciences, 2024
During the COVID pandemic, universities around the globe had to move not only their content delivery online, but also their assessments. Due to COVID causing significant upheaval in Higher Education (HE), this enforced experiment also afforded an opportunity to reflect on traditional, invigilated, closed book exams (ICBE) resulting in research and…
Descriptors: COVID-19, Pandemics, Computer Assisted Testing, Educational Technology
Zeenath Reza Khan – Journal of Academic Ethics, 2024
The global surge in academic misconduct during the COVID-19 pandemic, exacerbated by remote teaching and online assessment, necessitates a comprehensive understanding of the multidimensional aspects and stakeholders' perspectives associated with this issue. This paper addresses the prevalent use of answer-providing sites and other types of…
Descriptors: COVID-19, Pandemics, Stakeholders, Integrity
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
Malcolm Tight – Assessment & Evaluation in Higher Education, 2024
This article presents a literature review of published research focused on challenging cheating in higher education. A brief overview of the literature on cheating in higher education is offered, showing the global interest in the topic, the varied ways in which it has been defined, and evidence on its incidence and causes. The range of methods…
Descriptors: Cheating, Higher Education, Global Approach, Discipline Problems
Mengkorn Pum; Sarin Sok – Asian Journal of Distance Education, 2024
With current state-of-the-art advances in artificial intelligence (AI), especially large language models, such as Google's Gemini, Microsoft's Copilot, and ChatGPT, among others, a plethora of research on this phenomenon has been conducted worldwide aiming to examine its limitations, benefits and ethical implications. Nonetheless, such a…
Descriptors: Foreign Countries, Artificial Intelligence, Technology Uses in Education, Computer Software
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