Cognitive and emotional math problems largely dissociate: Prevalence of developmental dyscalculia and mathematics anxiety.

Devine, Amy; Hill, Francesca; Carey, Emma; Szűcs, Dénes

doi:10.1037/edu0000222

Cited by 134 publications

(131 citation statements)

References 98 publications

(211 reference statements)

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“…In line with contemporary research (Devine, Hill, Carey, & Szűcs, 2018;Dowker, Sarkar, & Looi, 2016;Ramirez et al, 2013), the present survey considers state-and trait-MA as a continuum. The statistical analyses were computed with the entire distribution of MA scores.…”

Section: Grouping Of Childrenmentioning

confidence: 94%

Relation of state- and trait-math anxiety to intelligence, math achievement and learning motivation

2019

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This study investigates math anxiety (MA) by comparing trait-components of MA with real-time assessments of situational anxiety responses (state-components) in children. The research to date on MA in children is somewhat disparate in regard to methodology, and firm conclusions regarding the relation of MA to intelligence, math achievement and learning motivation are not readily drawn. Typically, the measures used in the MA research have differed by operationalizing either trait-MA and/or state- (or statelike)-MA, but have failed to compare the implications of their respective assumptions and the significance of their findings. Trait-MA and state-MA, self-ratings of math skills, attitudes towards mathematics, math achievement, the social anxiety, test anxiety, learning motivation and intelligence of 1,179 students (48.1% girls) from grades 4 and 5, were assessed. The findings yield evidence of a pronounced state-trait discrepancy. A negative correlation between state-MA and math achievement was observed for all intelligence levels, even when controlling for test- and social-anxiety traits, while there was no negative relation between trait-MA and achievement. State-MA was associated with lower intelligence, lower self-ratings, more negative attitudes, higher performance avoidance and work avoidance goals. In contrast, trait-MA was slightly related to higher mastery approach goals. The failure to adequately differentiate between state- and trait-based research into MA appears to be one reason for key inconsistencies between research findings and warrants further investigations.

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Section: Grouping Of Childrenmentioning

confidence: 94%

Relation of state- and trait-math anxiety to intelligence, math achievement and learning motivation

2019

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“…Therefore, understanding the factors related to strong mathematical abilities is extremely important. Research has primarily focused on the influences of many individual factors, both cognitive and non-cognitive ones [1][2][3], and recent studies highlight the complexity of the interaction between them [4][5][6]. More recent contributions have expanded the focus beyond the individual level, and have targeted factors allocated on the broader environmental level, such as the classroom, the relationship with the teachers and the family context [7][8][9][10][11].…”

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confidence: 99%

The role of cognitive and non-cognitive factors in mathematics achievement: The importance of the quality of the student-teacher relationship in middle school

et al. 2020

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There is increasing evidence that several factors, including both cognitive and non-cognitive ones, play an important role in mathematics achievement. Relatively little is known about how socio-emotional features and the quality of the student-teacher relationship correlate with mathematics achievement among adolescents in transition to middle school. The aim of the present study is to examine the role of cognitive factors (general cognitive abilities), non-cognitive factors (math anxiety and self-esteem), and the quality of the student-teacher relationship on mathematics achievement. A large sample of Italian sixth graders was evaluated upon entering middle school. The results showed that general cognitive ability was the best predictor of mathematics achievement. As regards non-cognitive factors, the level of math anxiety was effective in predicting mathematics achievement, after controlling for other measures including self-esteem and the quality of the student-teacher relationship. In particular, we found that the quality of the student-teacher relationship had an indirect influence on mathematics achievement through the mediation of math anxiety. Our findings seem to indicate that the quality of the student-teacher relationship may be related to mathematics achievement, through its effects on math anxiety. This may have important implications for practitioners and educators, as we can suggest that interventions devoted to improving the quality of the student-teacher relationship may play a positive role in both preventing math anxiety and promoting mathematics learning.

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“…Among other benefits that we discuss below, teaching the bar technique could help students take the critical step of applying Bayesian reasoning outside of the classroom. Many people experience math anxiety, including people who have no objective deficit in math ability (e.g., Devine, Hill, Carey, & Szűcs, ). We think it is likely that these people would be more willing to jot down a bar doodle than to write out and solve a mathematical equation.…”

Section: Discussionmentioning

confidence: 99%

A visualization technique for Bayesian reasoning

Starns

Cohen

Bosco

et al. 2018

Applied Cognitive Psychology

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We tested a method for solving Bayesian reasoning problems in terms of spatial relations as opposed to mathematical equations. Participants completed Bayesian problems in which they were given a prior probability and two conditional probabilities and were asked to report the posterior odds. After a pretraining phase in which participants completed problems with no instruction or external support, participants watched a video describing a visualization technique that used the length of bars to represent the probabilities provided in the problem. Participants then completed more problems with a chance to implement the technique by clicking interactive bars on the computer screen. Performance improved dramatically from the pretraining phase to the interactive-bar phase. Participants maintained improved performance in transfer phases in which they were required to implement the visualization technique with either pencil-and-paper or no external medium. Accuracy levels for participants using the visualization technique were very similar to participants trained to solve the Bayes theorem equation. The results showed no evidence of learning across problems in the pretraining phase or for control participants who did not receive training, so the improved performance of participants using the visualization method could be uniquely attributed to the method itself. A classroom sample demonstrated that these benefits extend to instructional settings. The results show that people can quickly learn to perform Bayesian reasoning without using mathematical equations.We discuss ways that a spatial solution method can enhance classroom instruction on Bayesian inference and help students apply Bayesian reasoning in everyday settings.

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Cognitive and emotional math problems largely dissociate: Prevalence of developmental dyscalculia and mathematics anxiety.

Cited by 134 publications

References 98 publications

Relation of state- and trait-math anxiety to intelligence, math achievement and learning motivation

Relation of state- and trait-math anxiety to intelligence, math achievement and learning motivation

The role of cognitive and non-cognitive factors in mathematics achievement: The importance of the quality of the student-teacher relationship in middle school

A visualization technique for Bayesian reasoning

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