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Download full textHsu, Chia-Ling; Chen, Yi-Hsin; Wu, Yi-Jhen – Practical Assessment, Research & Evaluation, 2023
Correct specifications of hierarchical attribute structures in analyses using diagnostic classification models (DCMs) are pivotal because misspecifications can lead to biased parameter estimations and inaccurate classification profiles. This research is aimed to demonstrate DCM analyses with various hierarchical attribute structures via Bayesian…
Descriptors: Bayesian Statistics, Computation, International Assessment, Achievement Tests
Direct linkvon Davier, Matthias; Tyack, Lillian; Khorramdel, Lale – Educational and Psychological Measurement, 2023
Automated scoring of free drawings or images as responses has yet to be used in large-scale assessments of student achievement. In this study, we propose artificial neural networks to classify these types of graphical responses from a TIMSS 2019 item. We are comparing classification accuracy of convolutional and feed-forward approaches. Our…
Descriptors: Scoring, Networks, Artificial Intelligence, Elementary Secondary Education
Koyuncu, Mahmut Sami; Erdemir, Aysenur – International Journal of Contemporary Educational Research, 2019
The aim of the study is to compare TIMSS 2011 proficiency levels with the proficiency levels defined by the researchers using cluster analysis for Turkey, Korean, Norway, and Morocco in 4th and 8 th grades in the fields of science and mathematics. Therefore, it is tried to be reached that these cut-off scores for each country can serve the…
Descriptors: Cutting Scores, Achievement Tests, Elementary Secondary Education, Foreign Countries
Mullis, Ina V. S., Ed.; Martin, Michael O., Ed.; von Davier, Matthias, Ed. – International Association for the Evaluation of Educational Achievement, 2021
TIMSS (Trends in International Mathematics and Science Study) is a long-standing international assessment of mathematics and science at the fourth and eighth grades that has been collecting trend data every four years since 1995. About 70 countries use TIMSS trend data for monitoring the effectiveness of their education systems in a global…
Descriptors: Achievement Tests, International Assessment, Science Achievement, Mathematics Achievement
Stapleton, Laura M.; Kang, Yoonjeong – Sociological Methods & Research, 2018
This research empirically evaluates data sets from the National Center for Education Statistics (NCES) for design effects of ignoring the sampling design in weighted two-level analyses. Currently, researchers may ignore the sampling design beyond the levels that they model which might result in incorrect inferences regarding hypotheses due to…
Descriptors: Probability, Hierarchical Linear Modeling, Sampling, Inferences
Huang, Hung-Yu; Wang, Wen-Chung – Educational and Psychological Measurement, 2014
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
Descriptors: Item Response Theory, Hierarchical Linear Modeling, Computation, Test Reliability
