Abstract
This study tested a structural model of cognitive-emotional explanatory variables to explain performance in mathematics. The predictor variables assessed were related to students’ level of development of early mathematical competencies (EMCs), specifically, relational and numerical competencies, predisposition toward mathematics, and the level of logical intelligence in a population of primary school Chilean students (n = 634). This longitudinal study also included the academic performance of the students during a period of 4 years as a variable. The sampled students were initially assessed by means of an Early Numeracy Test, and, subsequently, they were administered a Likert-type scale to measure their predisposition toward mathematics (EPMAT) and a basic test of logical intelligence. The results of these tests were used to analyse the interaction of all the aforementioned variables by means of a structural equations model. This combined interaction model was able to predict 64.3% of the variability of observed performance. Preschool students’ performance in EMCs was a strong predictor for achievement in mathematics for students between 8 and 11 years of age. Therefore, this paper highlights the importance of EMCs and the modulating role of predisposition toward mathematics. Also, this paper discusses the educational role of these findings, as well as possible ways to improve negative predispositions toward mathematical tasks in the school domain.
Highlights
Predictors of academic performance can be classified into two differentiated, but related categories: the first category contains domain-general predictor abilities and the second one contains domainspecific predictor abilities (Passolunghi and Lanfranchi, 2012)
Structural Equations Model of the Early Mathematical Competencies (EMCs) Variable Initially, a univariate descriptive statistical analysis of the variants examined in this study was developed
Considering the first objective of this study, we developed an explanatory model that took into account solely the effect of the latent early mathematical competencies (EMCs) variables on academic performance
Summary
Predictors of academic performance can be classified into two differentiated, but related categories: the first category contains domain-general predictor abilities and the second one contains domainspecific predictor abilities (Passolunghi and Lanfranchi, 2012). Among domain-general predictors, we can find cognitive and emotional abilities, which predict performance in the wide spectrum of school subjects and not just on a particular content domain, like, for example, general intelligence or motivation. Specific predictors concern abilities that predict future performance in School mathematics performance: longitudinal study particular fields, like number-sense or counting abilities in mathematics (De Smedt et al, 2009). The domain-general predictors to be examined are the role of logical intelligence and predisposition toward mathematics. As for domain-specific predictors, the role of logical and relational types of early mathematical competencies (EMCs) and numerical competencies will be examined
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