Leveraging large-scale assessments for effective and equitable school practices: the case of the nordic countries.

One of the primary goals of educational research is to identify effective and equitable school practices that aim to promote desired educational outcomes for all students, regardless of their background. This pursuit raises the question of why certain countries or schools demonstrate more favourable outcomes than others. To shed light on this question, this special issue delves into the Nordic countries (Denmark, Finland, Iceland, Norway, and Sweden) as a showcase. Despite their similar historical, cultural, and economic characteristics, these countries show vastly different levels of student outcomes. This special issue comprises seven studies that utilize data from the international large-scale assessments (PIRLS, TIMSS, and PISA), leveraging their international comparative design and nationally representative student samples. The present article provides an overview of the seven included studies by underlining the key themes that transcend them as well as their contributions and implications. These themes include the measurement of educational effectiveness with international large-scale assessments, the central role of teachers, and the importance of both cognitive and non-cognitive student outcomes in studying different perspectives on effective and equitable school practices.

A constrained factor mixture analysis model for consistent and inconsistent respondents to mixed-worded scales.

Mixed-worded scales require a more careful reading and answering process than scales with only one type of wording. The present study is about the unintended consequences of using such scales, because typically, not all respondents answer positively and negatively worded items consistently. This population heterogeneity-meaning that there are distinct groups of consistently and inconsistently answering respondents-may arguably underlie wording-related effects in mixed-worded scales. We formulated a constrained factor mixture analysis model that operationalized these two assumed classes of respondents. We investigated five data sets that contained four mixed-worded attitude scales, large-scale samples from three countries (Germany, Australia, and the U.S.), and two age groups (children and adolescents). The constrained factor mixture analysis model showed estimated parameter patterns in line with theoretical expectations and consistently outperformed its more traditional competitor, confirmatory factor analysis with one global and one orthogonal method factor across all used data sets. We found proportions of between 7% and 20% of respondents belonging to the inconsistent classes. To further substantiate and validate the interpretation of the proposed model, we related class membership to theoretically relevant respondent characteristics such as reading achievement, cognitive skills, or conscientiousness. Further, we undertook an initial exploration of the overlap in inconsistent respondents' class membership across time and across scales within a survey. The article discusses implications for future research as well as for the use of mixed-worded scales. (PsycInfo Database Record (c) 2022 APA, all rights reserved).