School-level inequality and learning achievement: measurement, theory, and analysis based on the Programme for International Student Assessment (PISA)

Sempe, Lucas (2022) School-level inequality and learning achievement: measurement, theory, and analysis based on the Programme for International Student Assessment (PISA). Doctoral thesis, University of East Anglia.

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Abstract

Exogenous socioeconomic characteristics in schools, or school socioeconomic compositional effects (SCE), heavily influence students’ cognitive and noncognitive outcomes. The influence of SCE on learning achievements varies across individuals, schools, and wider contexts. SCE reflect structural individual and societal conditions that affect people’s future lives and development. In this respect, understanding their complexity provides a greater opportunity to address disparities and enable people and societies to reach their potential.

The most common aspects studied in the academic literature are the student’s socioeconomic status (SES) and the school socioeconomic status. This thesis focuses on a less studied SCE dimension, namely within-school economic inequality (hereafter school inequality). This aggregated measure of inequality reflects the distribution of students’ household wealth in each school and provides an understanding beyond the usual SCE aspects. The presence of school inequality matters to educational and development studies and practice because it sheds further light on the role of SCE inside schools. Studying school inequality across a range of contexts enables the development of appropriate policies to address its potential influence on students’ learning outcomes.

I use data from the Programme for International Student Assessment (PISA), which measures learning outcomes as the Reading, Mathematics and Science skills of 15-year-old students across the world. I use waves 5, 6 and 7 corresponding to years 2012, 2015 and 2018.

I focus on four aspects related to the phenomenon of school inequality: i) its measurement based on categorical data using tools provided by Item Response Theory models, which is axiomatised and validated with other inequality measurements; ii) a review of how socioeconomic inequalities affect schooling outcomes identifying four distinct academic bodies of literature, namely, difficulties in terms of access to education; the corrosive effect of inequality in the social fabric; relative deprivation and interpersonal comparisons; and, finally, social reproduction theory. Based on that, I develop a set of inferential analysis models to study the relationship between both school inequality and learning scores. I consistently find negative associations between them across the different PISA waves, model specifications and inequality measurements. I also find that school wealth interacts differently with school inequality, finding that students in wealthier schools tend to be more negatively influenced by inequality.

iii) I theorise potential channels of how school inequality affects schooling outcomes suggesting mechanisms such as social isolation, interpersonal comparisons and anomie. By understanding schools as socialising spaces and based on a social cohesion framework, I study how certain attitudes operate as mitigating resources – in terms of compensation, moderation and mitigation – of the negative consequences of inequality on learning scores. However, the negative effects remain in place after the inclusion of those explanatory variables.

iv) Finally, I develop an exploratory study addressing a theoretical and empirical trade-off between school inequality and country school segregation, showing how both factors coexist and negatively affect learning scores. Learning scores are used as a synthetic measurement of school achievement, and at the same time, are a relevant predictor of further academic advancement and economic development.

Item Type:	Thesis (Doctoral)
Faculty \ School:	Faculty of Social Sciences > School of Global Development (formerly School of International Development)
Depositing User:	Chris White
Date Deposited:	17 Oct 2022 13:10
Last Modified:	17 Oct 2022 13:10
URI:	https://ueaeprints.uea.ac.uk/id/eprint/89118
DOI:

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