Project Outline: The Impact of Different Education Systems on Social Mobility

Like

Share this post

Choose a social network to share with, or copy the URL to share elsewhere

This is a representation of how your post may appear on social media. The actual post will vary between social networks

The Impact of Different Education Systems on Social Mobility

Caroline Ho

University of Toronto

Research Advisor: Professor Mitchell McIvor

Abstract

Governments in many developed countries have seen a reduction in tax revenue and, subsequently, social spending on areas like education (OECD 2015; 2016). The result at the post-secondary level is rapidly growing tuition and student debt rates (OECD, 2016). The result at all education levels is higher teacher turnover, larger class sizes, and fewer extracurricular resources (Jackson et al., 2016). These developments come at a time when post-secondary credentials are more important than ever to employment and income, which ultimately affects socio-economic social mobility of citizens (Berger & Parkin, 2009). For these reasons, empirical cross-national evidence is needed that assesses (1) how different countries have approached education in a tight fiscal environment and (2) which approaches to this problem have resulted in the most sustainable social mobility rates. It is this gap in knowledge that my proposed research seeks to address.

Introduction

My interest in the intersection of education, policy, and equity stems from my exposure to a diverse range of communities and backgrounds in educational contexts. I am a double major in public policy and sociology with a minor in education and society at the University of Toronto. Growing up, I attended elementary school in Vancouver, Canada. Subsequently, I attended high school at a boarding school in Andover, USA. In addition, I have served as a volunteer tutor for youth in Vancouver, Toronto, and Hong Kong. These experiences have shaped my interest in exploring the complex issue of global inequality in education, and I am interested in how differing cultural contexts and education systems affect students' social mobility.

Methodology

To answer my research question, I will create a unique data set that aggregates data from cross-national and international sources into one analytical sample—this will include data from the World Bank, Organization for Economic Co-operation and Development, International Social Survey Program, World Values Survey, and national statistics agencies such as Statistics Canada. The countries that will be analyzed are Canada, the United States, and the United Kingdom.1 This data will include quantitative data on my focal independent variable of education systems and structures such as student-to-teacher ratios at different education levels, drop-out and fail rates, government funding, tuition, student debt rates, educator pay rates, and more. It will include qualitative data that seeks to operationalize (1) cross-cultural differences in views on education such as newspaper articles in leading national newspapers, and (2) cross-national differences in political approaches to education as shown in political speeches and government policy documents. Finally, it will include quantitative cross-national contextual data such as population demographics, inequality levels, tax rates, aggregate political views, and the dependent variable of social mobility rates. Ultimately, this dataset involves the collection of publicly available data but aggregates it into a novel and more comprehensive account, allowing for more nuanced analysis. 

Social mobility rates will serve as the dependent variable, with both education level mobility and income mobility being analyzed. The independent variables will be indicators of education systems and structures as well as contextual variables related to national cultural differences tied to views on education and political differences in approaches to education. Final analysis will be conducted using the statistics program R with final models including ordinary least squares and linear probability regression models. To get novel measures of educational cultural context in each country, newspaper articles on education from 2020-2023 from three leading national newspapers (as determined by readership) from each country will be analyzed. Articles focusing on education or education policy will be collected using the University of Toronto library’s newspaper database. The research program NVivo will then be used to code and analyze the articles to operationalize how education is perceived and discussed. Similarly, to derive measures of educational political context in each country, current educational policies serving as enacted legislation as well as political speeches on education from 2020-2023 from incumbent political parties and lead opposition parties will be analyzed with NVivo. This qualitative data will be used to create quantitative measures for regression analysis, and will also be used as qualitative content analysis to supplement the quantitative findings.

Interdisciplinary and international focus of research

My proposal is by nature international and interdisciplinary. The focus of my research is to gain a holistic perspective of education equity and social mobility, but is novel in that it considers cultural and political nuances in addition to education structure and other contextual variables like economic climate and demographic information. It therefore involves elements of Sociology, Anthropology, Political Science, Policy, Education, and Economics. In addition, by analyzing data from Canada, the US, and the UK, this research analyzes how national level differences affect important educational outcomes.

Ethics review

Ethics review will not be needed because my study involves secondary analysis of data that is publicly available.

Research advisor

My research advisor is Dr. Mitchell McIvor, Assistant Professor of Sociology at the University of Toronto. Dr. McIvor’s research focuses on social mobility in education and includes projects on how student debt affects new university graduates, and how course structure and content affect student’s perceptions of equity and performance gaps between students of different socio-economic backgrounds. Dr. McIvor’s research uses mixed-methodology, and he has taught undergraduate and graduate level statistics courses since 2014. Dr. McIvor will help direct and advise on the data aggregation process, and statistical analysis will be done in direct collaboration with Dr. McIvor. No other external organizations or offices will be involved.

Outcomes

The goal of my research is to provide insight into the extent to which varied education system structures and policies affect equity in a holistic manner, as reflected by levels of social mobility. By gaining a better understanding of factors in policies and systems that result in higher social mobility within a given country, the research will help inform governments, non-profit organizations, and educational institutions on how to create educational equity and improve economic inequality.

Please sign in

If you are a registered user on Laidlaw Scholars Network, please sign in