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Understanding the drivers of academic achievement: A multi-method approach
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Resumo(s)
Education is a fundamental driver of social mobility, sustainable development, and economic growth. Yet, despite its importance, the determinants of academic achievement (AA) remain contested, with fragmented findings often based on limited sample data. This work addresses this gap by leveraging administrative records from virtually all Portuguese public high school students, complemented by a targeted survey, to provide a comprehensive and context-sensitive analysis of AA. Rather than relying on isolated case studies, this thesis follows a multi-phase design that progressively deepens our understanding of AA. It begins by mapping global evidence on AA drivers, then examines virtually every student in the Portuguese high school system to assess how unprecedented eventssuch as the COVID-19 pandemic and regional disparities shape student outcomes. Finally, it integrates primary data to uncover how family environments, in particular parental involvement, interact with socioeconomic conditions during the transition to higher education. Several consistent findings emerged across the studies. Among those, socioeconomic status proved to be one of the strongest predictors of AA. The COVID-19 pandemic deepened existing inequities and altered the relative importance of different success factors. Regional disparities also became evident, with rural and urban students demonstrating distinct needs linked to unequal access to resources. Finally, parental involvement played a crucial role, not only exerting a direct influence on student outcomes but also moderating the effects of socioeconomic conditions. This thesis delivers a unique, comprehensive, large-scale analysis of AA in Portugal using the entire public secondary school population. It demonstrates the added value of machine learning over traditional methods in handling large-scale educational data. It generates actionable insights aligned with international policy frameworks such as the United Nations’ fourth Sustainable Development Goal. These contributions advance theoretical understanding while offering practical guidance for the design of more inclusive and equitable education systems.
Descrição
A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management
Palavras-chave
Education Academic achievement High school Data science Machine learning