The Dutch gender gap in mathematics: Small for achievement, substantial for beliefs and attitudes

Meelissen, Martina R.M.; Luyten, Hans

doi:10.1016/j.stueduc.2008.04.004

Cited by 44 publications

(35 citation statements)

References 25 publications

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“…Concern to attitude toward mathematics, finding of this research was supported the previous studies that there is a positive relation between mathematics attitude and mathematics achievement (Ma & Kishor, 1997;Saha, 2007;Thomas, 2006;Meelissen & Luyten, 2008;Fardin, Alamolhodaei & Radmehr, 2011). In addition this study revealed that, the effects of students' attitude towards mathematics on different cognitive process and level o knowledge are different.…”

Section: Discussionsupporting

confidence: 87%

“…The attitudes of students towards lesson is not only effecting the success or interests but also effecting future field, lessons, jobs selection of students (Koca & Sen, 2006). According to literature, attitude can predict achievement and that achievement, in turn, can predict attitude (Meelissen & Luyten, 2008, Fardin, Alamolhodaei & Radmehr, 2011. Especially some students have quite negative opinions about math because of negative behaviors of teachers or wrong experiences.…”

Section: Mathematics Attitudementioning

confidence: 99%

See 1 more Smart Citation

A Psychological Model for Mathematical Problem Solving based on Revised Bloom Taxonomy for High School Girl Students

Hajibaba¹,

Radmehr²,

Ahadi³

2013

Research in Mathematical Education

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Section: Discussionsupporting

confidence: 87%

Section: Mathematics Attitudementioning

confidence: 99%

A Psychological Model for Mathematical Problem Solving based on Revised Bloom Taxonomy for High School Girl Students

Hajibaba¹,

Radmehr²,

Ahadi³

2013

Research in Mathematical Education

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“…These findings are surprising as the existing literature shows that men have higher self-confidence and report higher self-perceived ability on domainmasculine tasks, e.g. mathematics ( Meelissen & Luyten, 2008). Thus, the task seems to have affected both genders similarly, impacting on male and female self-perceptions and ability beliefs and causing both genders to reduce their post-task estimates.…”

Section: Resultsmentioning

confidence: 62%

“…Halpern et al, 2007), with females displaying more negative or self-handicapping math attitudes, having lower math self-confidence, stereotyping math as domain-masculine, underperforming on standardised math tests, and opting out of STEM careers (Crombie et al, 2005;Beyer, 1990Beyer, , 1998Hyde et al, 1990a,b;Linn & Hyde, 1989;Meelissen & Luyten, 2008;Sax & Harper, 2007;The College Board, 1998). On the other hand, males perceive math as a domain-masculine and are more self-confident about their math abilities (Meece et al, 2006;Meelissen & Luyten, 2008;van der Sluis et al, 2010). Thus, males were did better on the psychometric task and were more confident about their success.…”

Section: Resultsmentioning

confidence: 99%

The role of gender, task success probability estimation and scores as predictors of the domain-masculine intelligence type (DMIQ)

Storek

Furnham

2016

Learning and Individual Differences

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This paper reports two experimental studies aimed at understanding correlates of self-estimated intelligence. In both studies participants twice estimated their mathematical and spacial intelligence (called Domain Masculine Intelligence Type: DMIQ) on a normal distribution. They also completed a number of short numerical and logical ability tests after which they estimated their performance at a similar, more difficult task. Males gave higher estimates than females and did better on the tests. Their estimates of their DMIQ reduced on the second occasion after testing. Gender, task score and estimated performance were all significant predictors of both DMIQ scores. Task confidence was the best predictor of DMIQ1 and DMIQ2, over and above gender and test score, explaining 17% and 23% of variance respectively. Results are discussed in terms of the expanding literature on self-estimated intelligence 2

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“…The results of meta-analysis showed that females reported more negative attitudes than boys. Several studies give evidence that girls lack confidence in math and viewed mathematics as a male domain (Meelissen & Luyten, 2008;Odell & Schumacher, 1998;Hyde, Fennema, Ryan, Frost, & Hopp, 1990). This situation may stem from the fact that adolescent girls are more timid.…”

Section: Gender and Attitude Towards Mathematicsmentioning

confidence: 99%

Using Data Mining Techniques Examination of the Middle School Students’ Attitude towards Mathematics in the Context of Some Variables

Idil¹,

Narli²,

Aksoy³

2016

IJEMST

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The aim of this study is to examine middle school students" attitude towards mathematics in the context of their mathematic learning preferences using data mining which is data analysis methodology that has been successfully used in different areas including educational domains. "How do I actually learn?" questionnaire and attitude scale were applied to 702 middle school students studying in three different cities of Turkey. Demographic data (gender, grade level, parents" education level, pre-school education) were also gathered. Data mining techniques such as decision tree was implemented. Furthermore web graph was used for visualization of relationship between mathematic learning preference and attitude towards mathematics. Constructed decision tree models with C5.0 algorithm revealed that all of variables used in this study are related to the attitude towards mathematics but the most effective attribute is found as grade level. Using web graph, it was found that the strongest relationship was between reflective learning preference and positive level attitude towards mathematics.

show abstract

The Dutch gender gap in mathematics: Small for achievement, substantial for beliefs and attitudes

Cited by 44 publications

References 25 publications

A Psychological Model for Mathematical Problem Solving based on Revised Bloom Taxonomy for High School Girl Students

A Psychological Model for Mathematical Problem Solving based on Revised Bloom Taxonomy for High School Girl Students

The role of gender, task success probability estimation and scores as predictors of the domain-masculine intelligence type (DMIQ)

Using Data Mining Techniques Examination of the Middle School Students’ Attitude towards Mathematics in the Context of Some Variables

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