Title of thesis

School achievement - factors which are related to school results at the lower-secondary level

Opponent

Monica Rosén, Professor, Department of Education and Special Education, University of Gothenburg

Examining Committee Members 

Christina Wikström, Associate Professor, Department of Applied Educational Science, Umeå University
Alli Klapp, Associate Professor, Department of Education and Special Education, University of Gothenburg
Cormac McGrath, Associate Professor, Department of Education, Stockholm University

Suppleant 

Mara Westling Allodi, Professor, Department of Special Education, Stockholm University

Chair of the defence

Klara Bolander Laksov, Professor, Department of Education, Stockholm University

Supervisor 

Stefan Ekecrantz, Associate Professor, Department of Education, Stockholm University

Assistant Supervisor 

Ulf Fredriksson, Associate Professor, Department of Education, Stockholm University
Astrid Pettersson, Professor, Department of Teaching and Learning, Stockholm University
 

Abstract

The dissertation aims to examine the factors which are the most strongly associated with school results at the lower-secondary level, particularly Grade 9. What is being meant by school results are primarily grade point averages, national test results, and results in international large-scale assessments such as PISA (Programme for International Student Assessment). The research that underlies the dissertation is quantitative and mostly based on standard methods such as linear multiple regression analysis. The data consists of aggregated data from the Swedish National Agency for Education (Skolverket),  the Evaluation through Follow-up database, and PISA. Data points are from the years 2013, 2018, and 2019. The theoretical framework is primarily based on Urie Bronfenbrenner's ecological systems theory, specifically micro (e.g., individual and families), meso (schools), and macro systems (e.g., national curricula, cultural beliefs). The following six variables were highlighted in the analyses: socioeconomic status (SES), migration background, teacher competence, cognitive ability, non-cognitive abilites (e.g., academic self-concept, growth mindset), and geographical position. Among these factors, cognitive ability has the strongest relationship with school results, followed by non-cognitive abilities, SES, teacher comptence, migration background, and geographical position. The individual level data analyses did largely confirm the aggregated data. However, a problem with aggregated data and PISA data is that they lack cognitive ability variables. This may lead to omitted variables bias and larger effects for SES and migration background than which are actually the case. Geographical position is important in the sense that the highest school results are found in the Stockholm region, which also leads to a correlation between geographical position and SES.