Conference Agenda

Topic and Rationale

How can improvements in education be adequately assessed if educational quality is considered not only in terms of performance levels, but also with respect to institutional conditions, development processes, and the fair distribution of educational opportunities?The four empirical studies from Finland, Norway, Sweden, and Hungary, presented at the symposium, make complementary contributions to this topic by analyzing different levels of educational quality and inequality in European education systems.
The symposium aims to bring these studies together and to highlight how educational quality is established, stabilized, or differentiated at class, school, and system levels. The planned contributions address key dimensions of quality assurance, such as class composition, socioeconomic resources, individual developmental conditions, and early and persistent selection mechanisms.

Analytical Framework

The questions will be discussed from a macro-, meso-, as well as from a micro-perspective. Educational quality results from interactions between institutional system characteristics and individual developmental processes (Gross et al., 2016). This perspective serves as an organizing framework to facilitate the comparison of the different empirical approaches presented in the four papers.

• The macro level refers to differences in the stratification and control of education systems.
• The meso level focuses on schools and classrooms as key sources for quality assurance.
• The micro level considers the individual resources, life situations, and developmental trajectories of students.

Findings of the four papers:

Paper 1 (Finland) examines the relationship between non-random class assignments and the development of mathematical performance. The study shows that performance differences arise more frequently within schools than between them. This demonstrates that quality assurance cannot be applied solely at the system or school level; class-related decision-making processes also play a central role in educational equity. Thus, the paper makes an important contribution to meso-level quality assurance in less stratified systems.

Paper 2 (Norway) analyses how changes in family income correlate with performance development between grades 5 and 8. Despite Norway´s egalitarian education system, the paper reveals persistent socioeconomic effects on individual performance. It becomes clear that quality assurance at the system level does not automatically lead to equal opportunities, and that social dynamics at the micro level remain relevant, even in comprehensive welfare states.

Paper 3 (Sweden) broadens the view of educational quality by considering leisure activities and well-being as key factors for development. The longitudinal analysis shows that educational outcomes cannot be understood in isolation and that extracurricular context needs to be taken into account. Thus, the paper contributes to a broader understanding of educational quality, considering not only performance, but also development and life experiences. It opens up important perspectives for more comprehensive quality assurance.

Paper 4 (Hungary) analyses early and ongoing selection processes at the school and class levels throughout primary education. The results demonstrate that selection results in homogenization within classes and schools, as well as growing differences between them. The paper illustrates how highly stratified systems perpetuate educational inequalities and limit individual developmental potential, thereby addressing key challenges for improving education at the system level.

Objectives of the Symposium

To analyze educational quality and inequality within different education systems, a multi-level perspective is needed. This includes classroom-related decision-making processes in Finland, the socioeconomic dynamics of individual life situations in Norway, broader developmental conditions beyond the classroom in Sweden, and structural selection at system and school levels in Hungary.
The symposium outlines that educational improvement cannot be considered in isolation. Adopting a multi-level perspective is necessary. Educational quality is conceptualised as the outcome of interactions between these levels, based on testing at each level . In this way, the symposium substantially contributes to the goals of Network 9: Assessment, Evaluation, Testing and Measurement.

The aim of this study is first to investigate what kind of class profiles can be identified in Finnish schools in terms of student background and then examine how students’ mathematical reasoning develops in different types of classes from grade 4 to grade 6. In Finland, differences in student performance are found between classes rather than between schools. Students are not randomly assigned to classes, and for example, students special educational needs or their previous academic performance can affect the placement decisions (Paufler & Amrein-Beardsley, 2013). When student allocation is not random, it can be expected that students’ performance develops differently depending on the class they are assigned to (Hienonen, 2020). Data for the present study will be drawn from a longitudinal study with a nationally representative sample. Data were collected in 2022–2024, following the same students from grade 4 to grade 6 (2000 students from 110 classes and 75 schools). The research questions are: 1. What kind of class-level profiles can be identified based on different student background factors? 2. How does students’ mathematical reasoning develop in classes with different profiles? For the research questions 1 multilevel latent class analysis will be used to estimate different subgroups. For the research question 2, multilevel latent growth curve modelling will be utilized to investigate the developmental trajectories of mathematical reasoning in classes with different profiles. All analyses will be conducted in MPlus. Student’s background variables are mainly derived from student information forms completed by teachers and from the student questionnaire. Information on students’ class placement is derived from principals.  Student performance is measured with adaptive mathematical reasoning task. For the student-level and class-level profiles, also cognitive tasks in inductive reasoning, verbal reasoning and problem solving will be used.

Hienonen, N. (2020). Does a class placement matter? Students with special educational needs in regular or special classes. University of Helsinki. http://urn.fi/URN:ISBN:978-951-51-6392-9 Paufler, N. A., & Amrein-Beardsley, A. (2013). The random assignment of students into elementary classrooms: Implications for value-added analyses and interpretations. American Educational Research Journal, 51, 328–362. doi.org/10.3102/ 0002831213508299.

The Norwegian educational system is largely governed by egalitarian principles. It features a comprehensive public school system that is free of charge, employs a common curriculum, and does not use tracking or grade promotion/retention. Additionally, Norway provides universal healthcare, early education, and social support services. Despite these characteristics, recent evidence suggests a widening achievement gap between students whose parents have the highest and lowest levels of income and education (Sandsor et al., 2023). Furthermore, the proportion of children growing up in poverty has increased over the last decade. Internationally, research points to reduced access among lower-income students to supportive home environments (Davis-Kean et al., 2021), high-quality early childhood education (Cloney et al., 2016), and experienced teachers (Borman & Dowling, 2008). These factors are critical for long-term educational success (Dearing et al., 2024). However, most of these findings originate in more segregated societies and little is known regarding the mechanisms driven the SES achievement gap in the Norwegian context. Against this background, we analyzed population-level data to test how changes in family socio-economic status are associated with students’ academic achievement. Our study uses a random-intercept cross-lagged panel model to examine (1) whether within-student increases in family income are associated with changes in academic performance between 5th-, 8th-, and 9th-grade, and (2) the extent to which these relations vary across gender. By examining these questions within a welfare-rich and egalitarian society, this study contributes to understanding how longitudinal associations between family income fluctuations and children’s academic trajectories manifest in contexts with extensive social support systems and universal educational provision.

Borman, G. D., & Dowling, N. M. (2008). Teacher Attrition and Retention: A Meta-Analytic and Narrative Review of the Research. Review of Educational Research, 78(3), 367–409. https://doi.org/10.3102/0034654308321455 Cloney, D., Cleveland, G., Hattie, J., & Tayler, C. (2016). Variations in the Availability and Quality of Early Childhood Education and Care by Socioeconomic Status of Neighborhoods. Early Education and Development, 27(3), 384–401. https://doi.org/10.1080/10409289.2015.1076674 Davis-Kean, P. E., Tighe, L. A., & Waters, N. E. (2021). The Role of Parent Educational Attainment in Parenting and Children’s Development. Current Directions in Psychological Science, 30(2), 186–192. https://doi.org/10.1177/0963721421993116 Dearing, E., Bustamante, A. S., Zachrisson, H. D., & Vandell, D. L. (2024). Accumulation of Opportunities Predicts the Educational Attainment and Adulthood Earnings of Children Born Into Low- Versus Higher-Income Households. Educational Researcher, 53(9), 496–507. https://doi.org/10.3102/0013189X241283456 Sandsor, A. M. J., Zachrisson, H. D., Karoly, L. A., & Dearing, E. (2023). The Widening Achievement Gap between Rich and Poor in a Nordic Country. Educational Researcher, 52(4), 195–205.

Leisure engagement has been found to enhance various aspects of children’s well-being (e.g., Kuykendall et al., 2015; Savahl et al., 2020; Thornton t al., 2024). However, the mechanisms linking these constructs to children’s school outcomes remain underexplored. Specifically, little attention has been paid to how changes in children’s leisure engagement affect the development of well-being, and in turn, influence their school performance. Very often educational research relies on cross-sectional data and repeated measures are seldom available. Longitudinal data from the Evaluation through Follow-up (UGU) database, which includes of 11 different cohorts of children with repeated measurement across three time points and integrates sociodemographic information from register data, provides a unique opportunity to address this gap. The present study examines the following research questions based on data from the 2004 cohort: 1. How do leisure engagement, well-being, and school outcomes change over time, from grade 6 to grade 9? 2. What are the within-time relationships among leisure engagement, well-being, and school outcomes? 3. What are the cross-time mechanisms linking leisure engagement, well-being, and school outcomes? 4. How do sociodemographic characteristics such as gender, social background, migration status, and cognitive ability influence these mechanisms? The study sampled a total of 9,775 students. Key covariates included parental educational level and migration background. Students' cognitive abilities also served as time-invariant covariates in the model. To indicate engagement in leisure activities students reported the average time they spent per week on various activities, with responses captured using a six-point scale ranging from 0 hours per week to more than 41 hours per week. Well-being was assessed through student responses about the frequency of specific physical experiences over the past six months, recorded on a five-point scale ranging from "Always" to "Never" . Both Leisure engagement and well-being variables were administered in grades 6 and 9. School outcomes were measured by students' grade point averages in Grades 6 and 9. Factor scores were estimated for leisure engagement and well-being to provide composite measures for analysis. An autoregressive cross-lagged longitudinal model was applied to examine the longitudinal relationships among leisure engagement, well-being, and school outcomes. Findings from this study provide valuable insights into the role of leisure activities in shaping children’s well-being and school performance. These insights have significant potential for informing interventions in both family and school practices, ultimately contributing to improved educational and developmental outcomes for children.

Kuykendall, L., Tay, L., & Ng, V. (2015). Leisure engagement and subjective well-being: A meta-analysis. Psychological Bulletin, 141(2), 364-403. https://doi.org/10.1037/a0038508 Savahl, S., Adams, S., Florence, M. et al. (2020). The Relation Between Children’s Participation in Daily Activities, Their Engagement with Family and Friends, and Subjective Well-Being. Child Ind Res 13, 1283–1312. https://doi-org.ezproxy.ub.gu.se/10.1007/s12187-019-09699-3 Thornton, E., Petersen, K., Marquez, J. et al. (2024). Do Patterns of Adolescent Participation in Arts, Culture and Entertainment Activities Predict Later Wellbeing? A Latent Class Analysis. J. Youth Adolescence 53, 1396–1414. https://doi-org.ezproxy.ub.gu.se/10.1007/s10964-024-01950-7

Understanding how schooling structures can mitigate or amplify achievement gaps is a central issue in education from both an equity and an efficiency perspective (Hanushek & Woessmann, 2008; Van de Werfhorst & Mijs, 2010). Highly selective and tracked systems provide an analytically powerful setting for studying these processes (Van de Werfhorst & Mijs, 2010), and Hungary is a particularly informative case because international assessments place it among the most highly stratified OECD systems (OECD, 2023). Subsequent analyses have also shown that the Hungarian education system is distinctive in that it selects students not only between schools, but also between classes within schools (Csapó, Molnár, & Kinyó, 2009). Existing analyses are mostly based on cross-sectional data collections, and do not cover the eight years (ISCED 1 and 2) of primary education in Hungary. The present analyses fill this niche and analyzes how performance gaps between schools and classrooms evolve from Grades 2 to 8 (ISCED 1-2) using data from the Hungarian Educational Longitudinal Program (N=6,231; 155 schools, 287 classes; Csapó, 2014). Reading comprehension was measured via the eDia online assessment system (Csapó & Molnár, 2019) using anchored tests with increasing proportions of inferential and evaluative items at higher grade levels. A Rasch model was used to place scores on a common developmental scale (EAP/PV reliability=0.88). Missing data were handled following established methodological recommendations (e.g. Wijesuriya et al., 2025) and implemented multiple imputation with 100 datasets generated via a random-forest chained-equations algorithm. Between-school differences were statistically significant at all four measurement points and showed a steady increase over time (Grade 3: F=9.58; Grade 4: F=12.41; Grade 6: F=14.53; Grade 8: F=15.44; p<.001). Class-level disparities across schools were likewise significant and grew across the school years as well (Grade 3: F=7.36; Grade 4: F=8.72; Grade 6: F=9.97; Grade 8: F=10.43; p<.001). However, class-level differences within schools remained largely stable (Grade 3: F=4.04; Grade 4: F=3.58; Grade 6: F=3.65; Grade 8: F=3.53; p<.001), indicating persistent within-school stratification from early primary grades onward. The findings demonstrate that substantial performance stratification is already present by Grade 3 at both school and classroom levels. These achievement gaps increase between schools and stay stable between classes within schools throughout primary education. This poses a serious challenge to equity objectives in Hungary and in countries with similarly selective systems, and should draw attention to the relevance of policy interventions aimed at mitigating educational selection.

Csapó, B., Molnár, G., & Kinyó, L. (2009). A magyar oktatási rendszer szelektivitása a nemzetközi összehasonlító vizsgálatok eredményeinek tükrében [The selectivity of the Hungarian education system in light of the results of international comparative studies]. Iskolakultúra, 19(3-4), 3–13. https://www.iskolakultura.hu/index.php/iskolakultura/article/view/20829 Csapó, B. (2014). A szegedi iskolai longitudinális program [The Hungarian educational longitudinal program]. In J. Pál & Z. Vajda (Eds.), Szegedi Egyetemi Tudástár 7: Bölcsészet- és társadalomtudományok (pp. 117–166). Szegedi Egyetemi Kiadó. Csapó, B., & Molnár, G. (2019). Online diagnostic assessment in support of personalized teaching and learning: The eDia system. Frontiers in Psychology, 10, Article 1522. https://doi.org/10.3389/fpsyg.2019.01522 Hanushek, E. A., Woessmann, L. (2008). The role of cognitive skills in economic development. Journal of Economic Literature 46(3), 607–68. https://doi.org/10.1257/jel.46.3.607 OECD (2023). PISA 2022 Results (Volume I): The State of Learning and Equity in Education. OECD Publishing. https://doi.org/10.1787/53f23881-en Van de Werfhorst, H. G., & Mijs, J. J.B. (2010). Achievement inequality and the institutional structure of educational systems: A comparative perspective. Annual Review of Sociology, 36, 407–428. https://doi.org/10.1146/annurev.soc.012809.102538 Wijesuriya, R., Moreno-Betancur, M., Carlin, J. B., White, I. R., Quartagno, M., & Lee, K. J. (2025). Multiple imputation for longitudinal data: A tutorial. Statistics in Medicine, 44(3–4), e10274. https://doi.org/10.1002/sim.10274