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Wang, Jianjun; Ma, Xin – Athens Journal of Education, 2019
This rejoinder keeps the original focus on statistical computing pertaining to the correlation of student achievement between mathematics and science from the Trend in Mathematics and Science Study (TIMSS). Albeit the availability of student performance data in TIMSS and the emphasis of the inter-subject connection in the Next Generation Science…
Descriptors: Scores, Correlation, Achievement Tests, Elementary Secondary Education
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Meng, Lingqi; Qiu, Chen; Boyd-Wilson, Belinda – British Journal of Educational Technology, 2019
The present study investigated the factor structure of and measurement invariance in the information and communication technology (ICT) engagement construct, and the relationship between ICT engagement and students' performance on science, mathematics and reading in China and Germany. Samples were derived from the Programme for International…
Descriptors: Factor Structure, Information Technology, Error of Measurement, Science Achievement
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Dirlik, Ezgi Mor – International Journal of Progressive Education, 2019
Item response theory (IRT) has so many advantages than its precedent Classical Test Theory (CTT) such as non-changing item parameters, ability parameter estimations free from the items. However, in order to get these advantages, some assumptions should be met and they are; unidimensionality, normality and local independence. However, it is not…
Descriptors: Comparative Analysis, Nonparametric Statistics, Item Response Theory, Models
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Carnoy, Martin – National Education Policy Center, 2015
Stanford education professor Martin Carnoy examines four main critiques of how international test results are used in policymaking. Of particular interest are critiques of the policy analyses published by the Program for International Student Assessment (PISA). Using average PISA scores as a comparative measure of student achievement is misleading…
Descriptors: Criticism, Reputation, Test Validity, Error of Measurement