Analysis of causal configurations in mathematics academic performance: A study based on equifinality using fsQCA.

Abstract

In this study, we examine the configurations that lead to good results in the area of ​​Mathematics through Fuzzy Set Qualitative Comparative Analysis (fsQCA), a core competency in which extensive assessments such as ERCE 2019 and PISA-D, as well as the national assessment Ser Estudiante, have revealed significant discrepancies. This method, unlike traditional methods that seek net effects, focuses on individual cases and enables the identification of equifinality, the principle that indicates that various combinations of conditions can lead to a similar result. The analysis of necessary conditions revealed that study time is a necessary condition for good results, with high consistency, placing it as a necessary condition. Among the most relevant results, the combinations with the greatest explanatory power in the sufficiency analysis were satisfaction and study time (consistency = 0.878, coverage = 0.776) and family support and study time (consistency = 0.851, coverage = 0.787), demonstrating that high performance is achieved by combining dedication with socioemotional factors. Furthermore, the combined coverage of the model was 0.625, meaning that these causal configurations account for a large proportion of cases. Ultimately, success in mathematics is not determined by a single cause, but rather by the combination of individual and contextual factors, a result with implications for the design of multifactorial educational interventions.