Unveiling Causal Complexity in Mathematics Achievement: A Research Design Using Fuzzy-set Qualitative Comparative Analysis (fs/QCA)
Abstract
Mathematics achievement is a critical indicator of educational success and a key determinant for future STEM careers. However, national assessments in Indonesia reveal persistent learning gaps in student numeracy. Existing research predominantly relies on linear models (e.g., SEM) that estimate the 'net effect' of influencing factors, thereby overlooking complex causal configurations. This paper addresses this methodological gap. The primary result of this study is a comprehensive research design that employs fuzzy-set Qualitative Comparative Analysis (fs/QCA) to analyze secondary data from the Indonesian National Assessment. The proposed methodology is designed to identify multiple, distinct pathways—or 'causal recipes'—to success. The main contribution, therefore, is a robust framework that moves beyond linear analysis, offering a more nuanced foundation for developing targeted and context-specific educational policies
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