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Objective Math and reading are related at the disability level and along the continuum of skill (Cirino, 2022). Cognitive correlates of math and reading in children are well-known separately, with a recent focus on the reason for their overlap. However, less is known about these issues in community college (CC) students despite more than half of post-secondary education occurring at this level. Here we assess cognitive predictors of math and reading (language, working memory, processing speed, nonverbal reasoning, attention) in CC students, outcome overlap, and the extent that predictors account for overlap. We expect all predictors to relate to achievement, with language and working memory as the strongest predictors, and accounting for the most overlap. We also expect more overlap and stronger prediction for complex outcomes (reading comprehension and math applications) relative to foundational skills (word reading and computations). Participants and Methods Participants were 94 CC students enrolled in their first math class. Approximately half the students were taking developmental coursework. Participants were administered four KTEA-3 measures: Letter-Word Reading, Reading Comprehension, Math Computation, and Math Concepts and Application. Language consisted of Vocabulary (K-BIT-2), and Elision and Rapid Naming subtests of the CTOPP-2. Working memory was assessed with two complex span measures (Symmetry Span and Reading Span). Processing speed was measured with the WAIS-IV, and nonverbal reasoning with the K-BIT-2. Attention was assessed via a researcher-designed continuous performance task and a self-rating scale. Multiple regression assessed cognitive prediction for each achievement measure; and partial correlation evaluated overlap. Results For computations, all predictors accounted for R2=53% variance; nonverbal reasoning and elision were unique predictors (p<.05). For math applications, R2=58%, with unique prediction for nonverbal reasoning, vocabulary, elision, and symmetry span. For word reading, R2=50%, with unique prediction for vocabulary, elision, and reading span. Finally, for reading comprehension, R2=47%, with unique prediction for vocabulary and nonverbal reasoning. Regarding overlap, computations and word reading correlated r=.50, and math applications and reading comprehension r=.57, which is higher than a recent meta-analysis (Unal et al., 2023). Language was the strongest contributor of overlap; these variables reduced the correlation for foundational achievement by 50%, and for complex achievement, by 32%. Other domains accounted for little overlap, despite significant zero-order correlations. Substantive results were generally similar when covariates were considered. Conclusions Individual prediction was dominated by language, nonverbal reasoning, and working memory variables. Math and reading performances were strongly related, and language was the strongest predictor of this overlap, which is only partially consistent with extant literature but adds context and generalization for CC students. Attention and processing speed were only weakly related to performance, which may reflect the overlearned nature of these skills at this level. Future work might need to include more malleable factors (e.g., motivation), as well as broader views of achievement (e.g., course grades).
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This content will become publicly available on February 6, 2026
Math and health and financial numeracy in college students
Objective There are many measures of health and/or financial literacy and/or numeracy, which vary widely in terms of length, content, and the extent to which numbers or math operations are involved. Although the literature is large, there is less considers what is known about math prediction and development, perhaps because the bulk of this literature is with adults. This is important because the literature on how math develops, what predicts it, and how to intervene with it, is very large (Cirino, 2022). To the extent that performance and prediction are similar, then information from the developmental literature of mathematics can be brought to bear with regard to health and financial numeracy. Here we assess math cognition variables (arithmetic concepts and number line estimation) alongside working memory, likely the most robust cognitive predictor of math, as well as sociodemographic covariates. We expect all predictors to relate to each type of outcome, though we expect reading to be more related to health and financial numeracy relative to symbolic math. Participants and Methods Participants were 238 young adults, diverse in language and race/ethnicity, enrolled in their first and entry-level college math class at either community college or university; approximately 30% were taking developmental coursework. For this study, participants were given three sets of analogous math problems: (a) pure symbolic; (b) health numeracy context; (c) financial numeracy context. Additional measures were of reading (KTEA-3 Reading Comprehension), math cognition (Arithmetic Concepts and Number Line Estimation), and complex span working memory (Symmetry Span and Reading Span). Correlations assessed relations, and multiple regression assessed prediction. Results All measures involving math correlated, though symbolic math less well than health and financial numeracy with one another. For symbolic math, math cognition and working memory together accounted for R2=56% variance, and all were unique predictors, with arithmetic concepts strongest (ηp2 = .19). For health numeracy, all predictors also accounted for R2=56% variance. Beyond symbolic math, math cognition and working memory were unique predictors (all p < .05); reading comprehension was not. The clearly strongest unique predictor was number line estimation (ηp2 = .06). For financial numeracy, all predictors accounted for R2=61% variance. Beyond symbolic math and reading comprehension, again math cognition and working memory were unique predictors (all p < .05), and again number line estimation was the strongest (ηp2 = .08). Results held with covariate control. Conclusions Math cognition and working memory are known important contributors to math skill. This study shows these to be equally important whether math is in a pure symbolic context, or a health and or financial context. This suggests that the utility of health and financial numeracy measures (and potentially the constructs themselves) needs to consider the underlying concomitants of math skill more generally, particularly as the extent to which numbers and/or specific math operations are used in such measures varies widely. Context is likely important, however, and future work will need to consider practical outcomes (e.g., risky health or financial behaviors and management) across a range of populations.
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- Award ID(s):
- 1760760
- PAR ID:
- 10650726
- Publisher / Repository:
- International Neuropsychological Society
- Date Published:
- Format(s):
- Medium: X
- Location:
- New Orleans, LA
- Sponsoring Org:
- National Science Foundation
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Objective Historically, numerous studies have supported a male advantage in math. While more recent literature has shown that the gender gap is either decreasing or non-significant, a gender difference remains for higher level math (high school and college) (Hyde et. al. 1990; Casey et. al. 1995). It is known that both cognitive and non-cognitive factors influence math performance. There is little evidence for gender differences in working memory (Miller & Bichsel, 2004), which is a key predictor for mathematics. There is, however, evidence for gender differences in the non-cognitive domain, including math anxiety, with females having higher levels (Miller & Bichsel, 2004; Goetz, et. al. 2013). This study evaluates gender differences in both standardized and everyday math performances, and the way that cognitive and non-cognitive factors impact math. The study is focused on a very understudied group with high levels of math difficulty, namely community college students. We expected to find gender differences in math, and expect these to be in part accounted for by gender differences in strong mathematical predictors, particularly non-cognitive factors. Participants and Methods Participants included 94 community college students enrolled in their first math class (60 female; 34 male). Participants were administered the Kaufman Test of Educational Achievement – 3rd edition (KTEA3): Math Computation (MC) and Math Concepts Application (MCA) subtests, as well as an original Everyday Math (EM) measure which assessed their math ability in the context of common uses for math (e.g., financial and health numeracy). Additional measures included math anxiety, self-efficacy, and confidence. Finally, measures of complex span working memory tasks were administered to assess verbal and spatial working memory. Analyses were performed using correlation and regression to examine relationships between the cognitive and non-cognitive variables and standardized and everyday math measures. Results Correlations showed that all cognitive and non-cognitive variables are significantly correlated with all three math measures (all p < .05). There were no significant gender differences for any of the math measures, nor the working memory, or non-cognitive measures. Regression showed that across all three math outcomes, math anxiety and verbal working memory are significantly predictive of math performance. Overall R2 values were significant (range 27% to 37%, all p < .001). Working memory and math anxiety were unique predictors in all three regressions (all p < .05), but other non-cognitive variables such as self-efficacy did not show unique prediction (all p > .05). Conclusions There was no evidence for gender differences on any studied variable. This stands in contrast to prior studies, although few studies have included community college students. On the other hand, both cognitive and non-cognitive factors were complimentary in the prediction of math outcomes, which is consistent with prior work. Among non-cognitive predictors, math anxiety was particularly prominent. This study clarifies prior conflicting work regarding gender differences, and highlights the role of both math anxiety and working memory as relevant for multiple math outcomes.more » « less
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Park and Brannon (2013, https://doi.org/10.1177/0956797613482944) found that practicing non-symbolic approximate arithmetic increased performance on an objective numeracy task, specifically symbolic arithmetic. Manipulating objective numeracy would be useful for many researchers, particularly those who wish to investigate causal effects of objective numeracy on performance. Objective numeracy has been linked to performance in multiple areas, such as judgment-and-decision-making (JDM) competence, but most existing studies are correlational. Here, we expanded upon Park and Brannon’s method to experimentally manipulate objective numeracy and we investigated whether numeracy’s link with JDM performance was causal. Experimental participants drawn from a diverse internet sample trained on approximate-arithmetic tasks whereas active control participants trained on a spatial working-memory task. Numeracy training followed a 2 × 2 design: Experimental participants quickly estimated the sum of OR difference between presented numeric stimuli, using symbolic numbers (i.e., Arabic numbers) OR non-symbolic numeric stimuli (i.e., dot arrays). We partially replicated Park and Brannon’s findings: The numeracy training improved objective-numeracy performance more than control training, but this improvement was evidenced by performance on the Objective Numeracy Scale, not the symbolic arithmetic task. Subsequently, we found that experimental participants also perceived risks more consistently than active control participants, and this risk-consistency benefit was mediated by objective numeracy. These results provide the first known experimental evidence of a causal link between objective numeracy and the consistency of risk judgments.more » « less
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