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Yang Zhen; Xiaoyan Zhu – Educational and Psychological Measurement, 2024
The pervasive issue of cheating in educational tests has emerged as a paramount concern within the realm of education, prompting scholars to explore diverse methodologies for identifying potential transgressors. While machine learning models have been extensively investigated for this purpose, the untapped potential of TabNet, an intricate deep…
Descriptors: Artificial Intelligence, Models, Cheating, Identification
ETS Research Institute, 2024
ETS experts are exploring and defining the standards for responsible AI use in assessments. A comprehensive framework and principles will be unveiled in the coming months. In the meantime, this document outlines the critical areas these standards will encompass, including the principles of: (1) Fairness and bias mitigation; (2) Privacy and…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Educational Testing, Ethics
Sinharay, Sandip – Educational Measurement: Issues and Practice, 2021
Technical difficulties occasionally lead to missing item scores and hence to incomplete data on computerized tests. It is not straightforward to report scores to the examinees whose data are incomplete due to technical difficulties. Such reporting essentially involves imputation of missing scores. In this paper, a simulation study based on data…
Descriptors: Data Analysis, Scores, Educational Assessment, Educational Testing
Ozge Ersan Cinar – ProQuest LLC, 2022
In educational tests, a group of questions related to a shared stimulus is called a testlet (e.g., a reading passage with multiple related questions). Use of testlets is very common in educational tests. Additionally, computerized adaptive testing (CAT) is a mode of testing where the test forms are created in real time tailoring to the test…
Descriptors: Test Items, Computer Assisted Testing, Adaptive Testing, Educational Testing