Differences in Cognitive and Learning Styles
and Aptitude Abstracts
G. W. Bracey, Sex and math, revisited
Two new studies suggest that there may be differences in how boys and
girls approach mathematical problems, which may explain why girls get
lower scores. In both studies boys were better able to tell whether
information provided in a problem was sufficient or relevant
C.D. Ennis and J.C. Lazurus, Cognitive style and gender differences in children's motor task performance
Memory storage capacity and system flexibility of 7 year-old children were examined through performance on a novel ball-intercepting task. Field dependence/independence served as the theoretical base for the study. The task required students in 56) to analyze the speed and direction of a bell rolling down a ramp and adjust their speed and angle of approach to intercept it within a limited space. Data were collected using video cameras positioned behind and to the side of the child's pathway. Data were reduced using a qualitative categorical system and analyzed using a MANOVA. Results indicated that field-independent children used a sharper initial angle of approach than did field-dependent children. Males used both a sharper angle of approach and a more developmentally advanced grasping pattern than did females. Discussion focused on the field-dependent children's modifications of the task to decrease demands on storage capacity and preclude the development of alternative motor pathways or systems.
M. Haghighi, M. Ghanavati, A. Rahimi,The Role of Gender Differences in the Cognitive Style of Impulsivity/Reflectivity and EFL Success
Styles are those general characteristics within a person that make him/her prefer something and has tendency toward doing it. Such characteristics are cognitive styles and when used in educational situations are referred to as learning styles. Impulsivity (I) and Reflectivity (R) are two characteristics of human beings in cognitive domain. Impulsivity is a sudden action undertaken without careful thought by “quick guessers” who while uttering their guesses, commit a greater number of errors whereas reflective people, referred to as “thoughtful”, are slow and accurate, weigh all the possibilities, take longer to respond, and consequently make fewer errors . This study was after finding I/R effects on EFL success, the relationship between gender differences and I/R, as well as the interaction between gender differences and I/R. Hence, 105 Iranian pre-university female and male students in Shiraz, were randomly selected to take part in this study, divided into two groups of I/R based on the results of Yando and Kagan's (1968) adult/adolescent version of Matching Familiar Figures Test (MFFT), an individually administrated visual discrimination matching-to-sample task, based on their response latency and response accuracy. Oxford Placement Test measured the participants’ degree of proficiency whose EFL success was assessed by the nation-wide pre-university English Achievement Test. Data analysis showed that I/R tendencies do not facilitate EFL success, since there was not a statistically significant relationship between the variables of the present study; therefore, teachers should not ignore impulsivity, though they should be taught to postpone their obviously incorrect answers
A. J. Kersey, E. J. Braham, Kelsey D. Csumitta, Melissa E. Libertus & Jessica F. Cantlon,No Intrinsic Gender Differences in Children’s Earliest Numerical Abilities
From the article: Recent public discussions have suggested that the under-representation of women in science and mathematics careers can be traced back to intrinsic differences in aptitude. However, true gender differences are difficult to assess because sociocultural influences enter at an early point in childhood. If these claims of intrinsic differences are true, then gender differences in quantitative and mathematical abilities should emerge early in human development. We examined cross-sectional gender differences in mathematical cognition from over 500 children aged 6 months to 8 years by compiling data from five published studies with unpublished data from longitudinal records. We targeted three key milestones of numerical development: numerosity perception, culturally trained counting, and formal and informal elementary mathematics concepts. In addition to testing for statistical differences between boys’ and girls’ mean performance and variability, we also tested for statistical equivalence between boys’ and girls’ performance. Across all stages of numerical development, analyses consistently revealed that boys and girls do not differ in early quantitative and mathematical ability. These findings indicate that boys and girls are equally equipped to reason about mathematics during early childhood.
Susan C. Levine, Janellen Huttenlocher, Amy Taylor, Adela Langrock, Early Sex Differences in Spatial Skill,
From the article: This study investigated sex differences in young children's spatial skill. The authors developed a spatial transformation task, which showed a substantial male advantage by age 4 years 6 months. The size of this advantage was no more robust for rotation items than for translation items. This finding contrasts with studies of older children and adults, which report that sex differences are largest on mental rotation tasks. Comparable performance of boys and girls on a vocabulary task indicated that the male advantage on the spatial task was not attributable to an overall intellectual advantage of boys in the sample.
B. A. Nosek et al., National differences in gender–science stereotypes predict national sex differences in science and math achievement
From the article: About 70% of more than half a million Implicit Association Tests completed by citizens of 34 countries revealed expected implicit stereotypes associating science with males more than with females. We discovered that nation-level implicit stereotypes predicted nation-level sex differences in 8th-grade science and mathematics achievement. Self-reported stereotypes did not provide additional predictive validity of the achievement gap. We suggest that implicit stereotypes and sex differences in science participation and performance are mutually reinforcing, contributing to the persistent gender gap in science engagement.
A. Pollina, Gender balance: lessons from girls in science
Educational efforts to open up mathematical, physics, engineering and
technology fields to women have failed because they have been aimed at
making women think and behave like men. A better approach would be to
allow the development of feminine approaches to the study of these
fields. Suggestions on how to develop such approaches to learning that
were gleaned from the experiences of girls' schools are presented.
S. E. Severiens and G. T. M. Ten Dam, Gender differences in learning styles: A narrative review and quantitative meta-analysis
This article reviews research on gender and learning styles of students, 18 and older, conducted after 1980. Curry’s onion model (1983) is used to classify definitions of learning styles and to reconstruct the theoretical frameworks used. The extent to which learning style is considered stable or variable in different learning contexts determines its position in the model. Most studies used theoretical frameworks that belonged in the middle or outer layers of the model. This location indicates the strong influence of learning context on women’s and men’s learning styles. While there were differences between learning styles, research designs rarely included learning contexts.
E. S. Spelke, Sex differences in intrinsic aptitude for mathematics and
science: A critical review
In addition to the narrative review, the authors performed a quantitative meta-analysis on two instruments (Kolb’s Learning Style Inventory and Entwistle’s Approaches to Studying Inventory) to determine the direction and magnitude of gender differences in various samples. A search for these two instruments resulted in 26 studies for which the necessary statistics were available. On Kolb’s instrument, the results showed that men were more likely than women to prefer the abstract conceptualisation mode of learning. On Entwistle’s ASI a difference was found on the affective components of approaches to studying.
This article considers 3 claims that cognitive sex differences
account for the differential representation of men
and women in high-level careers in mathematics and science:
(a) males are more focused on objects from the
beginning of life and therefore are predisposed to better
learning about mechanical systems; (b) males have a profile
of spatial and numerical abilities producing greater
aptitude for mathematics; and (c) males are more variable
in their cognitive abilities and therefore predominate at the
upper reaches of mathematical talent. Research on cognitive
development in human infants, preschool children, and
students at all levels fails to support these claims. Instead,
it provides evidence that mathematical and scientific reasoning
develop from a set of biologically based cognitive
capacities that males and females share. These capacities
lead men and women to develop equal talent for mathematics