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Shun-Fu Hu; Amery D. Wu; Jake Stone – Journal of Educational Measurement, 2025
Scoring high-dimensional assessments (e.g., > 15 traits) can be a challenging task. This paper introduces the multilabel neural network (MNN) as a scoring method for high-dimensional assessments. Additionally, it demonstrates how MNN can score the same test responses to maximize different performance metrics, such as accuracy, recall, or…
Descriptors: Tests, Testing, Scores, Test Construction
Kang, Taehoon; Chen, Troy T. – Asia Pacific Education Review, 2011
The utility of Orlando and Thissen's ("2000", "2003") S-X[squared] fit index was extended to the model-fit analysis of the graded response model (GRM). The performance of a modified S-X[squared] in assessing item-fit of the GRM was investigated in light of empirical Type I error rates and power with a simulation study having…
Descriptors: Simulation, Item Response Theory, Models, Testing
Rogers, W. Todd – Canadian Journal of Education, 2014
Principals and teachers do not use large-scale assessment results because the lack of distinct and reliable subtests prevents identifying strengths and weaknesses of students and instruction, the results arrive too late to be used, and principals and teachers need assistance to use the results to improve instruction so as to improve student…
Descriptors: Foreign Countries, Group Testing, Multidimensional Scaling, Evaluation Utilization
Gao, Xiaoqing; Maurer, Daphne; Nishimura, Mayu – Journal of Experimental Child Psychology, 2010
We explored the perceptual structure of facial expressions of six basic emotions, varying systematically in intensity, in adults and children aged 7 and 14 years. Multidimensional scaling suggested that three- or four-dimensional structures were optimal for all groups. Two groups of adults demonstrated nearly identical structure, which had…
Descriptors: Nonverbal Communication, Models, Multidimensional Scaling, Children

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