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Liao, Manqian; Patton, Jeffrey; Yan, Ray; Jiao, Hong – Measurement: Interdisciplinary Research and Perspectives, 2021
Item harvesters who memorize, record and share test items can jeopardize the validity and fairness of credentialing tests. Item harvesting behaviors are difficult to detect by the existing statistical modeling approaches due to the absence of operational definitions and the idiosyncratic nature of human behaviors. Motivated to detect the…
Descriptors: Data Analysis, Cheating, Identification, Behavior Patterns
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
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
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
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
Man, Kaiwen; Harring, Jeffrey R. – Educational and Psychological Measurement, 2021
Many approaches have been proposed to jointly analyze item responses and response times to understand behavioral differences between normally and aberrantly behaved test-takers. Biometric information, such as data from eye trackers, can be used to better identify these deviant testing behaviors in addition to more conventional data types. Given…
Descriptors: Cheating, Item Response Theory, Reaction Time, Eye Movements
A Sequential Bayesian Changepoint Detection Procedure for Aberrant Behaviors in Computerized Testing
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
Maeda, Mitsuko – Compare: A Journal of Comparative and International Education, 2021
This study examines Cambodian students' exam cheating practices throughout their schooling. Based on a thorough analysis of interviews with 19 university students, the study found that, although cheating was more prevalent at the secondary level, individual students' cheating experiences varied in frequency and timing (i.e. when they started,…
Descriptors: Tests, Cheating, College Students, Student Experience
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
Suyadi; Nuryana, Zalik; Asmorojati, Anom Wahyu – International Journal of Evaluation and Research in Education, 2021
This research aimed to analyze the insertion of anti-corruption education in Islamic education. In the context of anti-corruption education, especially students in tertiary institutions, corrupt practices are manifested in the form of corrupt behavior, such as plagiarism, cheating, truancy, and hitchhiking in group assignments, even though they do…
Descriptors: Islam, Neurosciences, Religious Education, Prevention

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