With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…

Traditional estimators of item response theory scale scores ignore uncertainty carried over from the item calibration process, which can lead to incorrect estimates of the standard errors of measurement (SEMs). Here, the authors review a variety of approaches that have been applied to this problem and compare them on the basis of their statistical…

This study reassessed the extent to which socio-economic background, gender, and region endure as sources of educational inequality in Canada. The analysis utilized the 28,000 student Canadian sample from the data set of the OECD's 2003 "Programme for International Student Assessment (PISA)". Results, consistent with previous findings,…