The purpose of this study is to examine the effect of missing data imputation methods, namely regression imputation (RI), multiple imputation (MI) and k-nearest neighbor (kNN) on differential item functioning (DIF). In this regard, the datasets used in the research were created by deleting some of the data via the missing completely at random…

Background: Large-scale cross-national studies designed to measure student achievement use different social, cultural, economic and other background variables to explain observed differences in that achievement. Prior to their inclusion into a prediction model, these variables are commonly scaled into latent background indices. To allow…

Background: The present study investigates what factors related to the school context influence student achievement on TIMSS mathematics tests across countries. A systematic review of the literature on PIRLS, TIMSS, and ICCS was conducted upstream to identify those school, teacher, and classroom factors shown to be useful predictors of student…

Large-scale studies, such as the Trends in International Mathematics and Science Study (TIMSS), provide data to understand cross-national differences and similarities. In this study, we aimed to identify factors predicting mathematics achievement of Turkish students by comparing to Australian students. First, construct equivalence and item bias…

Twelve articles present excerpts from several national reports of countries participating on the Second International Science Study (SISS) of the International Association for the Evaluation of Educational Achievement. The SISS examined science achievement and its correlates in participating countries and studied trends from 1970 through the…