Unraveling the role of math anxiety in students' math performance

被引:3
|
作者
Demedts, Febe [1 ,2 ]
Reynvoet, Bert [3 ]
Sasanguie, Delphine [4 ]
Depaepe, Fien [1 ,2 ]
机构
[1] Katholieke Univ Leuven, Ctr Instructional Psychol & Technol, Leuven, Belgium
[2] Katholieke Univ Leuven, IMEC Res Grp ITEC, Leuven, Belgium
[3] Katholieke Univ Leuven, Brain & Cognit, Leuven, Belgium
[4] HOGENT, Res Ctr Learning Divers, Ghent, Belgium
来源
FRONTIERS IN PSYCHOLOGY | 2022年 / 13卷
关键词
math anxiety; math performance; state math anxiety; trait math anxiety; domain-specificity; NATURAL NUMBER BIAS; MATHEMATICS ANXIETY; REACTION-TIME; FRACTION; ACHIEVEMENT;
D O I
10.3389/fpsyg.2022.979113
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
Math anxiety (MA; i.e., feelings of anxiety experienced when being confronted with mathematics) can have negative implications on the mental health and well-being of individuals and is moderately negatively correlated with math achievement. Nevertheless, ambiguity about some aspects related to MA may prevent a fathomed understanding of this systematically observed relationship. The current study set out to bring these aspects together in a comprehensive study. Our first focus of interest was the multi-component structure of MA, whereby we investigated the relationship between state- and trait-MA and math performance (MP) and whether this relation depends on the complexity of a math task. Second, the domain-specificity of MA was considered by examining the contribution of general anxiety (GA) and MA on MP and whether MA also influences the performance in non-math tasks. In this study, 181 secondary school students aged between 16 and 18 years old were randomly presented with four tasks (varying in topic [math/non-math] and complexity [easy/difficult]). The math task was a fraction comparison task and the non-math task was a color comparison task, in which specific indicators were manipulated to develop an easy and difficult version of the tasks. For the first research question, results showed a moderate correlation between state- and trait-MA, which is independent of the complexity of the math task. Regression analyses showed that while state-MA affects MP in the easy math task, it is trait-MA that affects MP in the difficult math task. For the second research question, a high correlation was observed between GA and MA, but regression analyses showed that GA is not related to MP and MA has no predictive value for performance in non-math tasks. Taken together, this study underscores the importance of distinguishing between state and trait-MA in further research and suggests that MA is domain-specific.
引用
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页数:9
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