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…

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…

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…