A multi-level approach to exploring the associations between reading, spelling, and math skills

Abstract

In this study, we utilized network analysis to examine with standard clinical tests the predictions of the multi-level model of cognitive skill learning proposed by Zoccolotti et al. (2020b) on the relationships among different learning domains (Zoccolotti et al., 2021). To achieve this, we administered a series of reading, spelling, and math tasks to primary school children. The network analysis evidenced positive links within each area, consistent with the prediction that reading, spelling and math refer to three partially distinct domains calling for different core competences. Another expectation was that the associations among these learning domains would be mediated by tests that involve retrieving individual memories (instances). Supporting this prediction, the three tests measuring instance-based processing - Orthographic Judgment, Ambiguous Words, and Arithmetic Facts - were crucial in linking the three learning domains. Furthermore, the model posits that some associations among different learning areas may be influenced by format or response characteristics, referred to as "performance" factors. We identified two such cases in the observed network: a strong link between reading speed and calculation speed, which is closely related to speed requirements, and a robust connection between reading accuracy and context-sensitive words, interpreted as a need for careful orthographic analysis. Overall, the results largely confirm the model's predictions, highlighting specific and common factors contributing to performance in reading, spelling, and math.