Conference Agenda

This symposium brings together four coordinated papers that leverage novel international longitudinal assessment data from TIMSS 2023 Longitudinal (von Davier et al., 2025) to examine one-year mathematics learning progress and its individual, teacher, and school-level determinants. While cross-sectional studies have substantially advanced knowledge about achievement differences between student groups and education systems, they are limited in addressing how learning progresses and inequalities develop over time. By focusing on learning gains rather than single-point achievement, the symposium highlights how longitudinal evidence can sharpen explanations of educational effectiveness and equity.

Across the four papers, the symposium addresses a common core question: Which student, teacher, instructional, and school conditions are associated with stronger learning growth, and to what extent do these conditions amplify or mitigate educational inequality? Methodologically, the papers employ multilevel longitudinal models that account for the nested structure of schooling and enable the examination of growth processes within students and classrooms. Conceptually, the symposium integrates perspectives from research on cumulative advantage, teacher quality, instructional quality, and school climate to build a more process-oriented understanding of learning and stratification.

The first paper investigates the role of student-level characteristics in shaping learning gains, with a particular focus on the Matthew effect (cumulative advantage), and examines whether growth differs by gender, socioeconomic status, and migration background. The second paper tests whether teacher qualifications and professional preparation predict students’ learning growth, contributing to long-standing debates about the extent to which formal training translates into improved student outcomes. Extending this, the third paper examines the contribution of instructional quality, operationalized through three basic dimensions of instructional quality—classroom management, cognitive activation, and supportive climate—and evaluates their association with learning progress. The fourth paper turns to the school as an organization, analyzing how school climate—including safety, bullying, and academic emphasis—relates to student growth and whether a positive climate perpetuates socioeconomic disparities by mediating the relationship between students’ backgrounds and their achievement development.

Taken together, the symposium provides a coherent and multi-level account of how learning progress unfolds over time and where leverage points for policy and practice may lie. By combining inequality-focused and effectiveness-focused perspectives within a longitudinal framework, the contributions aim to inform debates on who benefits most from schooling, which aspects of teaching matter for growth, and how school environments can support both higher achievement gains and more equal learning opportunities.

Longitudinal research in educational inequality aims to understand how earlier achievement and social background shape subsequent learning trajectories. While prior achievement is a strong predictor of later performance, theoretical perspectives diverge on whether it leads to cumulative advantage—where high-achieving students experience greater gains—or compensatory patterns, where lower-achieving students show relatively stronger growth. Empirical evidence from large-scale studies has often challenged strong cumulative advantage assumptions, instead pointing to modest or absent Matthew effects in reading and mathematics. These patterns are frequently attributed to regression-to-the-mean dynamics, instructional differentiation, or ceiling effects (Baumert et al., 2012; Nennstiel, 2023). Beyond prior achievement, social background characteristics like socioeconomic status (SES) play a key role in shaping outcomes. SES captures inequalities in access to material resources, cultural capital, and learning support. While SES differences in achievement levels are well-documented, longitudinal research suggests that growth gaps are often stable rather than widening over time once prior achievement is taken into account. Evidence from Germany, for example, indicates persistent SES differences in mathematics and language levels but little support for cumulative SES-related divergence in trajectories (Nennstiel, 2023). Examining SES effects net of prior achievement allows for a precise assessment of whether students with similar starting points diverge. Gender differences in mathematics achievement represent another longstanding topic. Cross-national evidence shows that gender gaps vary considerably across countries and grade levels. Longitudinal analyses suggest these differences tend to remain relatively stable over time, with only modest changes during secondary education. Recent evidence indicates that gender differences in mathematics development are generally small once prior achievement is controlled for, though persistent patterns may still be observed in specific systems or cohorts (Uunk & Blossfeld, 2025). Controlling for prior achievement provides a framework for assessing whether gender is associated with differential achievement outcomes beyond earlier performance. This study addresses these issues by drawing on the complete longitudinal dataset from the TIMSS Longitudinal Study. The analysis encompasses a primary cohort following students from Grade 4 to Grade 5 across nine countries, and a lower secondary cohort following students from Grade 8 to Grade 9 across three countries. Focusing on mathematics, the study employs two-level regression models with students nested within schools to examine achievement at the second measurement occasion while explicitly controlling for prior achievement. By investigating prior achievement, gender, and SES, this study provides a baseline individual-level model of achievement growth.

Baumert, J., Nagy, G., & Lehmann, R. (2012). Cumulative advantages and the emergence of social and ethnic inequality: Matthew effects in reading and mathematics development within elementary schools?. Child development, 83(4), 1347-1367. Nennstiel, R. (2023). No Matthew effects and stable SES gaps in math and language achievement growth throughout schooling: Evidence from Germany. European sociological review, 39(5), 724-740. Uunk, W., & Blossfeld, P. (2025). Gender-specific development of mathematics and language performance in lower secondary education in Germany. Zeitschrift für Bildungsforschung, 15(1), 95-119.

This study investigates which aspects of teaching quality (TQ) are related to progress in student learning outcomes and whether students have equal access to high-quality instruction. Evidence identifies TQ as a fundamental driver of student learning and a critical link to educational equity (e.g. Fauth et al., 2021; Darling-Hammond, 2000). However, it remains unclear which specific TQ dimensions matter most for learning progress, as findings vary across countries and cohorts (Blömeke et al., 2019). These inconsistencies are often attributed to varying conceptualizations of TQ and methodological limitations (Klieme & Nilsen, 2022). While qualitative studies offer deep insights, they lack generalizability. Conversely, quantitative research frequently relies on cross-sectional designs prone to omitted variable bias and reversed causality, hindering robust causal inferences. Consequently, there is an urgent need for longitudinal research using representative samples and validated frameworks that allow for comparisons across countries and cohorts. This study addresses these gaps by utilizing the complete longitudinal dataset from the TIMSS Longitudinal project and adopting the Three Basic Dimensions framework (Klieme et al., 2009). This framework, comprising classroom management, supportive climate, and cognitive activation, provides a validated, standardized basis for comparison (Praetorius et al., 2018; Klieme & Nilsen, 2022). The analysis encompasses all participating countries across both available cohorts: a primary cohort (Grade 4 to 5) across nine countries, and a lower secondary cohort (Grade 8 to 9) across three of these countries. Using two-level regression analyses (students nested within classes), the study investigates the impact of the three TQ dimensions on mathematics achievement gain. Additionally, it examines the relationship between student socioeconomic status and TQ to determine if high-quality teaching is equitably distributed. Missing data will be handled using robust maximum likelihood (RML) estimation to ensure the integrity of the longitudinal findings. The data will be available in February 2026. Based on previous research (e.g. Praetorius et al., 2018; Klieme & Nilsen, 2022), we hypothesize that classroom management and cognitive activation will demonstrate stronger impacts on cognitive outcomes than supportive climate. We further hypothesize that the equitable distribution of high-quality teaching will vary according to the broader educational equity profiles of the participating countries. These findings will contribute to the global debate regarding the role of teaching quality in fostering both academic excellence and social equality.

Blömeke, S., & Olsen, R. V. (2019). Consistency of results regarding teacher effects across subjects, school levels, outcomes and countries. Teaching and teacher education, 77, 170-182. Darling-Hammond, L. (2000). Teacher quality and student achievement. education policy analysis archives, 8. Fauth, B., Atlay, C., Dumont, H., & Decristan, J. (2021). Does what you get depend on who you are with? Effects of student composition on teaching quality. Learning and Instruction, 71, 101355. Klieme, E., Pauli, C., & Reusser, K. (2009). The pythagoras study: Investigating effects of teaching and learning in Swiss and German mathematics classrooms. The power of video studies in investigating teaching and learning in the classroom, 137-160. Klieme, E., & Nilsen, T. (2022). Teaching Quality and Student Outcomes in TIMSS and PISA. In T. Nilsen, A. Stancel-Piątak, & J. E. Gustafsson (Eds.), International Handbook of Comparative Large-Scale Studies in Education (Vol. 2). Springer International Handbooks of Education. Springer, Cham. Praetorius, A.-K., Klieme, E., Herbert, B., & Pinger, P. (2018). Generic dimensions of teaching quality: The German framework of three basic dimensions. ZDM, 50(3), 407-426.

There is growing evidence that knowledge and skills acquired in compulsory school have lasting effects into adulthood (Gustafsson, 2016), and that the first years of schooling are particularly important for students’ later educational trajectories. This raises the question of which early school determinants are most influential for student achievement. Among school resources, class size has been shown to affect achievement (Fredriksson et al., 2013), although effect sizes are modest. In contrast, several syntheses conclude that teaching and teachers are of greater importance (Hattie, 2009). Longitudinal studies consistently demonstrate substantial differences in student outcomes across teachers (e.g., Nye et al., 2004), with teacher-level variation accounting for approximately 10 percent of the variance in achievement. At the same time, evidence linking observed teacher characteristics such as education and experience to student outcomes has been mixed, partly due to methodological limitations and imprecise definitions of teacher qualifications (Blömeke & Olsen, 2019). Nevertheless, several studies report positive associations between teacher quality indicators and student achievement (Wayne & Youngs, 2003; Johansson et al., 2023). There is, moreover, a need for robust evidence, as much previous research relies on single-country studies or cross-sectional data. Building on this literature, the present study examines variation in teacher effectiveness within schools and tests the hypothesis that teachers with relevant teacher education and longer experience have a greater impact on student learning than teachers without such qualifications. This study addresses these gaps by utilizing the complete longitudinal dataset from the TIMSS Longitudinal project. The analysis encompasses all participating countries across two cohorts: a primary cohort (Grade 4 to 5) across nine countries, and a lower secondary cohort (Grade 8 to 9) across three of these countries. Using two-level regression analyses (students nested within classes), the study investigates the impact of teacher quality indicators, such as teacher education and experience, on mathematics achievement gains. In addition, the study examines the relationship between student socioeconomic status and teacher quality to assess whether teacher quality is equitably distributed. We hypothesize that the distribution of teacher quality varies across countries as a function of the compensatory mechanisms of the school system. These findings provide evidence on the role of teacher quality in promoting student achievement and shed light on social selection effects.

Blömeke, S., & Olsen, R. V. (2019). Consistency of results regarding teacher effects across subjects, school levels, outcomes and countries. Teaching and Teacher Education, 77, 170-182. Fredriksson, P., Öckert, B., & Oosterbeek H. (2013). Long-Term Effects of Class Size, Quarterly Journal of Economics, 128(1), 249-285 Gustafsson, J.-E. (2016). Lasting effects of quality of schooling: Evidence from PISA and PIAAC. Intelligence, 57, 66–72. Hattie, J. (2009). Visible learning. A synthesis of over 800 meta-analyses relating to achievement. New York: Routledge. Johansson, S., Gustafsson, J.-E., Hansson, Å., & Alatalo, T. (2023). Estimating effects of teacher characteristics on student achievement in reading and mathematics: evidence from Swedish census data. Scandinavian Journal of Educational Research, 1-18. Nye, B., Konstantopoulos, S., & Hedges, L. V. (2004). How large are teacher effects? Educational Evaluation and Policy Analysis, 26, 237-57. Wayne, A.J. & Youngs, P. (2003). Teacher characteristics and student achievement gains: A review, Review of Educational Research, 73, 89–122.

This study investigates which aspects of school climate relate to progress in student learning outcomes and whether students have equitable access to a positive school climate. School climate is a multifaceted concept; systematic reviews identify four key dimensions: academic (promotion of learning), community (interpersonal relationships), safety (environmental security and absence of bullying), and institutional (organizational structure and resources) (Wang & Degol, 2016; Thapa et al., 2013). While these dimensions are critical to cognitive and affective outcomes (Cohen et al., 2009), it remains unclear which specific dimensions most significantly drive learning progress and educational equality (Berkowitz et al., 2017). Current research often focuses on single dimensions, and findings remain inconsistent due to varying conceptualizations and methodological limitations (Nilsen & Teig, 2022). Furthermore, most studies rely on cross-sectional designs prone to omitted variable bias and reversed causality, hindering robust causal inferences. Consequently, there is an urgent need for longitudinal research using representative samples and validated frameworks that allow for cross-national comparisons. This study addresses these gaps by utilizing the complete longitudinal dataset from the TIMSS Longitudinal project and adopting the framework by Wang and Degol (2016). The analysis encompasses all participating countries across two cohorts: a primary cohort (Grade 4 to 5) across nine countries, and a lower secondary cohort (Grade 8 to 9) across three of these countries. Using two-level regression analyses (students nested within classes), the study investigates the impact of the four school climate dimensions on mathematics achievement gain. Additionally, it examines the relationship between student socioeconomic status and school climate to determine if positive school climates are equitably distributed. Missing data will be handled using robust maximum likelihood (RML) estimation to ensure the integrity of the longitudinal findings. The data will be available in February 2026. Based on previous research synthesis (e.g. Nilsen and Teig, 2022; Wang and Degol, 2016), we hypothesize that absence of bullying (safety dimension) and academic emphasis (academic dimension), alongside student sense of belonging (community dimension), will demonstrate stronger impacts on cognitive outcomes than physical resources (institutional dimension). However, we expect results to vary across countries and grades. We further hypothesize that the equitable distribution of a positive school climate will vary according to the broader educational equity profiles of the participating countries (Berkowitz et al., 2017). These findings will offer evidence-based insights for school leaders and policymakers regarding the role of school climate in fostering both academic excellence and social equality.

Berkowitz, R., Moore, H., Astor, R. A., & Benbenishty, R. (2017). A research synthesis of the associations between socioeconomic background, inequality, school climate, and academic achievement. Review of Educational Research, 87(2), 425-469 Cohen, J., McCabe, E. M., Michelli, N. M., & Pickeral, T. (2009). School climate: Research, policy, practice, and teacher education. Teachers college record, 111(1), 180-213. Nilsen, T., & Teig, N. (2022). A systematic review of studies investigating the relationships between school climate and student outcomes in TIMSS, PISA, and PIRLS. International Handbook of Comparative Large-Scale Studies in Education: Perspectives, Methods and Findings, 1-34. Thapa, A., Cohen, J., Guffey, S., & Higgins-D’Alessandro, A. (2013). A review of school climate research. Review of Educational Research, 83(3), 357-385. Wang, M.-T., & Degol, J. L. (2016). School climate: A review of the construct, measurement, and impact on student outcomes. Educational Psychology Review, 28(2), 315-352.