Reframing Knowledge Capital Theory: A Critical Realist Approach Using Rosetta Stone and Harmonized Learning Outcomes Datasets - A Comparative Analysis

Abstract

Knowledge Capital Theory (KCT) posits a causal link between educational outcomes and economic growth. This study critically examines KCT through a Critical Realist (CR) lens, leveraging two novel datasets: Rosetta Stone and Harmonized Learning Outcomes (HLO). These datasets offer a more comprehensive view of educational performance across diverse global contexts, addressing limitations in data and methods currently used in International Large-Scale Assessments (ILSAs). The study employs an updated Abductive Theory of Science Method (ATOM) framework within a CR perspective, combining quantitative analysis with qualitative inquiry to discuss underlying mechanisms and contextual factors influencing the education-economy relationship. Analysis reveals a complex picture of KCT's empirical and theoretical status. Regression models with the conditioned Rosetta and HLO data produced R² values of 0.43 and 0.21 respectively, indicating a significant relationship between cognitive skills and economic growth. However, a logarithmic model for the HLO data yielded a higher R² of 0.389 compared to 0.211 using linear conditioning, challenging KCT's linear assumptions. The study identified several atypical countries, suggesting the influence of factors such as resource-dependent economies, industry concentration, and economic instability. While providing support for KCT's core claims across a broader range of countries than previous research, these findings highlight the need for more nuanced interpretations. This research raises fundamental questions about applying Lakatosian concepts in social sciences, suggesting a reinterpretation of Lakatos' framework as a heuristic tool rather than a strict evaluative criterion in open social systems. It proposes a dual approach in educational economics: pursuing empirical progressiveness while developing more sophisticated theoretical models that accommodate open systems' complexities. By incorporating CR and ATOM, the study provides a methodological framework for future ILSA research that better accounts for the multifaceted nature of educational outcomes and their economic impacts. This approach offers policymakers contextually relevant insights for developing effective educational policy, while giving researchers tools for more comprehensive analyses of the education-economy relationship. The findings have implications for educational policy, particularly regarding Sustainable Development Goal 4, highlighting the need for context-sensitive approaches to education reform that consider the complex interplay of factors influencing the education-economy relationship.