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The Role of Cognitive and Non-Cognitive Factors in Mathematics Achievement: a Three-Wave Longitudinal Study

Fri, April 9, 11:45am to 12:45pm EDT (11:45am to 12:45pm EDT), Virtual

Abstract

Adequate mathematics abilities are essential in everyday life and these become more and more relevant with development (Geary, Hoard, Nugent, & Bailey, 2013). Several studies have analysed the relation between mathematics abilities and professional status, emphasizing that higher job profiles are frequently associated with higher mathematical skills (i.e. Shalev, Manor, & Gross-Tsur, 2005). Therefore, understanding the factors that can predict good mathematics abilities is extremely relevant. According to latest conceptualizations, we analysed the roles of cognitive factors (i.e. fluid intelligence Gf) and non-cognitive factors (i.e. math anxiety -MA- and student-teacher relationship and school bonding -STR-SB) that have been shown to influence various aspects of mathematics achievement (Chang & Beilock, 2018; Semeraro et al., 2020). To date, no study has investigated the joint contribution of these two domains in a longitudinal perspective. This contribution intends to fill this gap by exploring the associations of cognitive and non-cognitive factors on mathematical achievement in preadolescents in the school context. A total number of 219 students from 9 classes of a middle school in an urban area of Puglia in southern Italy participated in the study. The students were followed from Grade 6 to Grade 7. The mean age of the children in our study was 11.12 years (SD = .31) at Time 1, and 47.7% were girls (N = 90). At each time, in three different sessions, suitably organized in individual or collective form, the following instruments were administered: Cattell Culture Fair Intelligence Test for Gf; the Student-Teacher Relationship Questionnaire for the evaluation the STR-SB; the Mema for MA and the Evaluation Test of Calculation Skills, for the evaluation of mathematical achievement. The relationships between Gf, STR-SB, MA and mathematical achievement were tested using a cross-lagged model. The final model showed a good adaptation to the data CFI = .951, RMSEA = .052, SRMR = .079, X 2 (113) = 178.90, p < .001., Regarding the cross-lagged paths between measures, fluid intelligence at T1 and T2 positively predicted mathematics achievement at T2 and T3 respectively; the quality of the student-teacher relationship and school bonding at T1 and T2, but not math anxiety, positively predicted mathematics achievement at T2 and T3 respectively; the quality of the student-teacher relationship and school bonding at T1 and T2 also predicted math anxiety at T2 and T3 (negatively). Again, the quality of the student-teacher relationship and school bonding at T2 predicted fluid intelligence at T3. Males showed higher mathematics achievement at T1 and lower math anxiety levels at T2 and T3. Our results showed that in addition to cognitive factors, non-cognitive factors also played a crucial role in predicting mathematics achievement in middle school. In particular, among the non-cognitive predictors, the quality of the student-teacher relationship and school bonding played an extremely important role in predicting mathematics achievement across the years of schooling. This result is extremely comforting because it allows us to reflect on the type of emotions conveyed in the report and on the impact of these on student learning.

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