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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