This study examines potential assessment bias based on students' primary language status in PISA 2018. Specifically, multilingual (MLs) and nonmultilingual (non-MLs) students in the United States are compared with regard to their response time as well as scored responses across three cognitive domains (reading, mathematics, and science).…

Well-being 2030 has become the latest rationale for the OECD's education work. This vision has given rise to new assessments of student well-being beginning with PISA 2015. The OECD, recognising the problems of PISA 2015, conceptualised a wider student well-being construct in PISA 2018, and attempted to measure 'students' feelings'. However,…

This article examines whether the way that PISA models item outcomes in mathematics affects the validity of its country rankings. As an alternative to PISA methodology, a two-parameter logistic model is applied to PISA mathematics item data from Italy and Spain for the year 2009. In the estimation procedure, item difficulty and dispersion…

Data analysis is a significant methodological component when conducting quantitative education studies. Guidelines for conducting data analyses in quantitative education studies are common but often underemphasize four important methodological components impacting the validity of inferences: quality of constructed measures, proper handling of…

Large-scale assessments (LSAs) use Mislevy's "plausible value" (PV) approach to relate student proficiency to noncognitive variables administered in a background questionnaire. This method requires background variables to be completely observed, a requirement that is seldom fulfilled. In this article, we evaluate and compare the…