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Man, Kaiwen; Harring, Jeffrey R. – Educational and Psychological Measurement, 2023
Preknowledge cheating jeopardizes the validity of inferences based on test results. Many methods have been developed to detect preknowledge cheating by jointly analyzing item responses and response times. Gaze fixations, an essential eye-tracker measure, can be utilized to help detect aberrant testing behavior with improved accuracy beyond using…
Descriptors: Cheating, Reaction Time, Test Items, Responses
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Melvin Prince; Emma Wang – Journal of Further and Higher Education, 2024
Past studies of academic dishonesty typically have been grounded in the theory of planned behaviour. Key predictors of academic dishonesty variables under this framework generally have been attitudes towards academic dishonesty, the impact of peer pressure to engage in such acts, and individual perceptions of related acts. However, planned…
Descriptors: Integrity, Cheating, Ethics, Student Behavior
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Dorea-Bandeira, Ingrid; Oliveira, Vanessa Gusmão de; Araújo-Pereira, Mariana; Andrade, Bruno Bezerril; Nazar, André Nogueira; Quintanilha, Luiz Fernando; Avena, Katia de Miranda – Problems of Education in the 21st Century, 2022
Academic misconduct during medical school is common, with multifactorial causes, and can negatively impact the training and professional performance of future physicians. This study investigated factors linked to academic misconducts among medical students during their training. It is a transversal, quantitative, and analytical study that assessed…
Descriptors: Foreign Countries, Medical Students, Student Attitudes, Perception
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Yang Jiang; Mo Zhang; Jiangang Hao; Paul Deane; Chen Li – Journal of Educational Measurement, 2024
The emergence of sophisticated AI tools such as ChatGPT, coupled with the transition to remote delivery of educational assessments in the COVID-19 era, has led to increasing concerns about academic integrity and test security. Using AI tools, test takers can produce high-quality texts effortlessly and use them to game assessments. It is thus…
Descriptors: Integrity, Artificial Intelligence, Technology Uses in Education, Ethics
Kaiwen Man – Educational and Psychological Measurement, 2024
In various fields, including college admission, medical board certifications, and military recruitment, high-stakes decisions are frequently made based on scores obtained from large-scale assessments. These decisions necessitate precise and reliable scores that enable valid inferences to be drawn about test-takers. However, the ability of such…
Descriptors: Prior Learning, Testing, Behavior, Artificial Intelligence
Jing Lu; Chun Wang; Jiwei Zhang; Xue Wang – Grantee Submission, 2023
Changepoints are abrupt variations in a sequence of data in statistical inference. In educational and psychological assessments, it is pivotal to properly differentiate examinees' aberrant behaviors from solution behavior to ensure test reliability and validity. In this paper, we propose a sequential Bayesian changepoint detection algorithm to…
Descriptors: Bayesian Statistics, Behavior Patterns, Computer Assisted Testing, Accuracy
Jing Lu; Chun Wang; Ningzhong Shi – Grantee Submission, 2023
In high-stakes, large-scale, standardized tests with certain time limits, examinees are likely to engage in either one of the three types of behavior (e.g., van der Linden & Guo, 2008; Wang & Xu, 2015): solution behavior, rapid guessing behavior, and cheating behavior. Oftentimes examinees do not always solve all items due to various…
Descriptors: High Stakes Tests, Standardized Tests, Guessing (Tests), Cheating