This study aimed to determine the relations between fluid intelligence (Gf) and reading/mathematics and possible moderators. A meta-analysis of 680 studies involving 793 independent samples and more than 370,000 participants found that Gf was moderately related to reading, r = .38, 95% CI [.36, .39], and mathematics, r = .41, 95% CI [.39, 44]. Synthesis on the longitudinal correlations showed that Gf and reading/mathematics predicted each other in the development even after controlling for initial performance. Moderation analyses revealed the following findings: (a) Gf showed stronger relations to mathematics than to reading, (b) within reading or mathematics, Gf showed stronger relations to complex skills than to foundational skills, (c) the relations between Gf and reading/mathematics increased with age, and (d) family social economic status (SES) mostly affected the relations between Gf and reading/mathematics in the early development stage. These findings, taken together, are partially in line with the investment theory but are more in line with the intrinsic cognitive load theory, mutualism theory, and the gene–SES interaction hypothesis of cognition and learning. More importantly, these findings imply an integration model of these theories from an educational and developmental perspective: Children may rely on Gf to learn reading and mathematics early on, when high family SES can boost the effects of Gf on reading/mathematics performance. As children receive more formal schooling and gain more learning experiences, their reading and mathematics improvement may promote their Gf development. During development, the negative effects of low family SES on the relations between Gf and reading/mathematics may be offset by education/learning experiences.
The purpose of this meta-analysis was to examine the relation between mathematics anxiety (MA) and mathematics performance among school-aged students, and to identify potential moderators and underlying mechanisms of such relation, including grade level, temporal relations, difficulty of mathematical tasks, dimensions of MA measures, effects on student grades, and working memory. A meta-analysis of 131 studies with 478 effect sizes was conducted. The results indicated that a significant negative correlation exist between MA and mathematics performance, r = −.34. Moderation analyses indicated that dimensions of MA, difficulty of mathematical tasks, and effects on student grades differentially affected the relation between MA and mathematics performance. MA assessed with both cognitive and affective dimensions showed a stronger negative correlation with mathematics performance compared to MA assessed with either an affective dimension only or mixed/unspecified dimensions. Advanced mathematical tasks that require multistep processes showed a stronger negative correlation to MA compared to foundational mathematical tasks. Mathematics measures that affected/reflected student grades (e.g., final exam, students’ course grade, GPA) had a stronger negative correlation to MA than did other measures of mathematics performance that did not affect student grades (e.g., mathematics measures administered as part of research). Theoretical and practical implications of the findings are discussed.
This study presents a meta-analysis of the relation between language and mathematics. A moderate relation between language and mathematics was found in 344 studies with 393 independent samples and more than 360,000 participants, r = .42, 95% CI [.40, .44]. Moderation and partial correlation analyses revealed the following: (a) more complicated language and mathematics skills were associated with stronger relations between language and mathematics; after partialing out working memory and intelligence, rapid automatized naming showed the strongest relation to numerical knowledge; (b) the relation between language and mathematics was stronger among native language speakers than among second-language learners, but this difference was not found after partialing out working memory and intelligence; (c) working memory and intelligence together explained over 50% of the variance in the relation between language and mathematics and explained more variance in such relations involving complex mathematics skills; (d) language and mathematics predicted the development of one another even after controlling for initial performance. These findings suggest that we may use language as a medium to communicate, represent, and retrieve mathematics knowledge as well as to facilitate working memory and reasoning during mathematics performance and learning. With development, the use of language to retrieve mathematics knowledge may be more important for foundational mathematics skills, which in turn further strengthens linguistic thought processes for performing more advanced mathematics tasks. Such use of language may boost the mutual effects of cognition and mathematics across development.
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