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Gal Kaldes; Elizabeth L. Tighe; Qiwei He – Grantee Submission, 2024
Introduction: Despite the necessity for adults with lower literacy skills to undergo and succeed in high-stakes computer-administered assessments (e.g., GED, HiSET), there remains a gap in understanding their engagement with digital literacy assessments. Methods: This study analyzed process data, specifically time allocation data, from the Program…
Descriptors: Time Management, Adults, Literacy, Computer Assisted 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
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