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.
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Attention check questions in self-report measurement of math and its non-cognitive factors in college students
Objective Online surveys are a common method of data collection. The use of “attention-check” questions are an effective method of identifying careless responding in surveys (Liu & Wronski, 2018; Meade & Craig 2012; Ward & Meade, 2023), which occurs in 10-12% of undergraduate samples (Meade & Craig, 2012). Instructed response type attention checks are straightforward and the most recommended (Meade & Craig, 2012; Ward & Meade, 2023). This study evaluated the effect of instructed response attention check questions on the measurement of math ability and non-cognitive factors commonly related to math (self-efficacy and math anxiety). We evaluated both level differences as well as whether check questions alter the relationship of non-cognitive factors to math. We expected that incorrect responding to check questions would lower math performance but were unable to make hypotheses about level of self-report non-cognitive factors. We predicted that incorrect responding to check questions would moderate the relationship between both math anxiety and self-efficacy to math performance. Participants and Methods Participants were 424 undergraduates (age 20.4, SD=2.7) at a large southwestern university. The sample was majority female (74%) but diverse socioeconomically and in race/ethnicity. The non-cognitive measures were researcher developed Math Anxiety (MA) and Math Self-Efficacy (MSE; Betz & Hackett, 1993) scales, with items selected directly targeting the use/manipulation of math in everyday life; both showed good reliability (α=.95). The two math scales were also researcher developed; one was a pure symbolic computational measure (EM-A) and the other consisted of word problems in an everyday context (EM-B). These measures had good reliability (α=.80 and α=.73). The four check questions were embedded in the surveys and two groupings were formed – one consisting of those who provided the correct answer for all items versus those who did not, and a second consisting of those who got all correct or only one answer incorrect versus those with more items incorrect. Correlational, ANOVA, and ANCOVA models were utilized. Results Descriptively, check questions were skewed – 75% participants answered all check questions correctly, and 8% missed only one. Relations of both MA and MSE with EM-A and EM-B were modest though significant (|r|=.22 to .37) and in the expected directions (all p<.001). Check questions were related to level of all tasks (p<.001), with incorrect responses resulting in lower math performance, lower MSE, and higher MA. Check questions did not moderate the relation of MA or MSE to either math performance, with some suggestion that MA was more strongly related to EM-B in those who missed check questions, though only when failing several. Conclusions Check questions showed a clear relation to both self-report and math performance measures. However, check questions did not alter the relation of MA or MSE to math performance in general. These results affirm extant relations of key self-perceptions to math using novel measures and highlight the need to evaluate the validity of self-report measures, even outside of objective performance indicators. Future work could examine the effect of attention checks in domains other than math and investigate other types of attention checks.
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- Award ID(s):
- 1760760
- PAR ID:
- 10514616
- Publisher / Repository:
- Poster presented at the 52nd annual meeting of the International Neuropsychological Society, New York, NY.
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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