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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
Youn Seon Lim – Applied Measurement in Education, 2024
Educational testing has been criticized for its disconnect from modern cognitive science and its limited role in improving instruction and student learning. Reform efforts emphasize the need for testing to provide specific diagnostic insights into students' skills and knowledge. Cognitive diagnosis (CD), an emerging paradigm in educational…
Descriptors: Q Methodology, Matrices, Models, Design

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