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…

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…

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…

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…

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…

The purpose of the present study was to examine the validity of modeling science achievement in terms of 3 social psychological variables (school connectedness, science attitude, and active learning) and 2 self-perception variables (self-confidence and science value). Two models were tested: full mediation and partial mediation. In the…

Many scales contain both positively and negatively worded items. Reverse recoding of negatively worded items might not be enough for them to function as positively worded items do. In this study, we commented on the drawbacks of existing approaches to wording effect in mixed-format scales and used bi-factor item response theory (IRT) models to…

This study was designed with the overall goal of understanding how difficulties in reading comprehension are associated with early adolescents' performance in large-scale assessments in subject domains including science and civic-related social studies. The current study extended previous research by taking a cognition-centered approach based on…

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…

This report on Key Data on Learning and Innovation through ICT at School in Europe 2011 builds on the previous Eurydice publications on information and communication technology in schools in Europe. It also aims to extend the theoretical framework by looking not only at the teaching and learning of ICT but also at the use of ICT to promote…

The Secondary Analysis of TIMSS (Third International Mathematics and Science Study) Video Data study used TIMSS Videotape Classroom Study data and vPrism software to achieve methodological and substantive findings on teacher quality, instructional practices, and classroom interactions. It discussed methodological and technical issues arising…