Differences In Mathematical Ability Research Articles

Gender Segregation in Education and its Implications for Labour Market Outcomes: Evidence from India

This paper investigates gender-based segregation across different fields of study at the post-secondary level of schooling, and how that affects subsequent labour market outcomes of men and women. Using a nationally representative longitudinal data-set from India, we provide evidence that there is substantial intra-household gender disparity in the choice of study stream at the higher-secondary level of education. A household fixed effects regression shows that girls are 20 percentage points less likely than boys to study in technical streams, namely science (STEM) and commerce, vis-a-vis arts or humanities.This gender disparity is not driven by gender specific differences in mathematical ability, as the gap remains large and significant even after controlling for individuals' past test scores. Our further analysis on working-age individuals suggests that technical stream choice at higher-secondary level significantly affects the gender gap in labour market outcomes in adult life, including labour force participation, nature of employment, and earnings. Thus our findings reveal how gender disparity in economic outcomes at a later stage in the life-course is affected by gendered trajectories set earlier in life, especially at the school level.

Reasoning Processes of Prospective Teachers in Proving Theorem Regarding Differences in Mathematical Ability

Reasoning Processes of Prospective Teachers in Proving Theorem Regarding Differences in Mathematical Ability

Mathematical Ability and Socio-Economic Background: IRT Modeling to Estimate Genotype by Environment Interaction.

Genotype by environment interaction in behavioral traits may be assessed by estimating the proportion of variance that is explained by genetic and environmental influences conditional on a measured moderating variable, such as a known environmental exposure. Behavioral traits of interest are often measured by questionnaires and analyzed as sum scores on the items. However, statistical results on genotype by environment interaction based on sum scores can be biased due to the properties of a scale. This article presents a method that makes it possible to analyze the actually observed (phenotypic) item data rather than a sum score by simultaneously estimating the genetic model and an item response theory (IRT) model. In the proposed model, the estimation of genotype by environment interaction is based on an alternative parametrization that is uniquely identified and therefore to be preferred over standard parametrizations. A simulation study shows good performance of our method compared to analyzing sum scores in terms of bias. Next, we analyzed data of 2,110 12-year-old Dutch twin pairs on mathematical ability. Genetic models were evaluated and genetic and environmental variance components estimated as a function of a family's socio-economic status (SES). Results suggested that common environmental influences are less important in creating individual differences in mathematical ability in families with a high SES than in creating individual differences in mathematical ability in twin pairs with a low or average SES.

Gender streaming and prior achievement in high school science and mathematics

Girls choose advanced matriculation electives in science and mathematics almost as frequently as boys, in Israel, but are very much under-represented in physics and computer science, and over-represented in biology and chemistry. We test the hypothesis that these patterns stem from differences in mathematical ability. Administrative data on two half-cohorts of Israeli eighth-grade students in Hebrew-language schools links standardized test scores in mathematics, science, Hebrew and English to their subsequent choice of matriculation electives. It shows that the gendered choices they make remain largely intact after conditioning on prior test scores, indicating that these choices are not driven by differences in perceived mathematical ability, or by boys’ comparative advantage in mathematics. Moreover, girls who choose matriculation electives in physics and computer science score higher than boys, on average. Girls and boys react differently to early signals of mathematical and verbal ability; and girls are less adversely affected by socioeconomic disadvantage.

Karakteristik Metakognisi Mahasiswa Dalam Menyelesaikan Masalah Matematika Berdasarkan Langkah-Langkah Polya Dan De Corte

This research describes the student metacognition profile Tadris Department of Mathematics State Islamic Institute Tulungagung based differences in mathematical ability that is highly capable student, medium, and low. Collecting data in this exploratory study done by solving mathematical problem solving and in-depth interviews. To get the process used metacognitive interview leads to the question steps to resolve the matter by the steps Polya and De Corte. Results of a study of college students show that students are capable of moderate or low it did not do a good metakognisis process in the last three stages of problem-solving by step Polya and De Corte. Students with moderate and low level of capability are only looking do metakognisis at the stage of understanding the problem, whereas high-ability students perform well metacognitive processes.

PENGARUH PEMBELAJARAN KOOPERTIF TIPE STAD TERHADAP KEMAMPUAN PEMAHAMAN DAN KOMUNIKASI MATEMATIS SISWA SEKOLAH DASAR

Examined the differences in mathematical ability of understanding and communication between students and Cooperative Learning STAD and students in hands-on learning. The subjects were students of class IV SDN Sarimulya II Cikampek. The study concluded: 1) The ability of the final mathematical understanding of students who received different STAD cooperative learning with the ability of students who received direct instruction. 2) The ability of mathematical communications students getting the same STAD cooperative learning with students getting hands-on learning. 3) Increased understanding of the mathematical ability of students who received STAD cooperative learning does not differ greatly from the ability of the students who received direct instruction. 4) Improving students' mathematical communication skills that got STAD cooperative learning significantly better than students who received direct instruction.

Explaining individual differences in mathematical ability: Genes, cultures, personality, and cognition

Despite a growing body of educational, psychological, and genetic research into individual differences in mathematical ability, motivation, and achievement, many issues remain unresolved. This symposium presents different approaches to the study of variation in mathematics, addressing issues of genetic and cross-cultural differences (Talks 1 and 3); developmental issues (Talk 3); contribution of non-cognitive factors, such as emotional regulation and other regulatory processes, such as goal planning and modeling of goal achievement (Talks 2 and 4); and dimensional issues, such as whether factors underlying mathematical giftedness are qualitatively different from those driving mathematical variation in the normal range. We present findings from Russia, Kyrgyzia, and the UK, and discuss them in the context of existing literature and educational implications.

PERSPEKTIF GENDER DALAM PEMBELAJARAN MATEMATIKA

Math is taughtwith the aimto prepare students to be able to usemathematics andmathematicalmindset in everyday life. In studying mathematics,many students bothmen and women considermathematics as a boring subject. Based on this, the gender aspect in learning mathematics become educators concern. Gender differences not only result in differences in mathematical ability, but also a way of gaining knowledge of mathematics. Some of the notion that women are not quite managed to learn math than men. In addition, women almost never have a thorough interest in theoretical questions such as the male. Women are more interested in practical matters than the theoretical. But on the other hand, not a few female students who have success in math skills. Writing this article aims to analyze some of the results of research on gender differences in mathematics learning. The methodology used is a literature study. This study found evidence of differences in the strategies used boys and girls, even to solve the spatial.

Executive Functions as Predictors of Math Learning Disabilities

In the past years, an increasing number of studies have investigated executive functions as predictors of individual differences in mathematical abilities. The present longitudinal study was designed to investigate whether the executive functions shifting, inhibition, and working memory differ between low achieving and typically achieving children and whether these executive functions can be seen as precursors to math learning disabilities in children. Furthermore, the predictive value of working memory ability compared to preparatory mathematical abilities was examined. Two classifications were made based on (persistent) mathematical ability in first and second grade. Repeated measures analyses and discriminant analyses were used to investigate which functions predicted group membership best. Group differences in performance were found on one inhibition and three working memory tasks. The working memory tasks predicted math learning disabilities, even over and above the predictive value of preparatory mathematical abilities.

Mathematics and the Flight from the Feminine: The Discursive Construction of Gendered Subjectivity in Mathematics Textbooks

There is a widespread awareness in our culture that women do not pursue careers in mathematics-related fields in equal numbers to men. Efforts to address this disparity by reforming mathematics education have met with some success; recent research shows that girls’ achievements in mathematics stay on par with those of boys through secondary school. There still remains, however, a significant disparity between young men and young women’s participation and success in mathematics at the postsecondary level, leading to what many now call the leaky mathematics pipeline (Oakes; Watt, Eccles, and Durik). While some still argue that women and men have different aptitudes for mathematics, many researchers have concluded that sex differences in aptitude and achievement in mathematics are minimal. In a 2005 critical review of such studies, Jeremy Caplan and Paula Caplan argue that meaningful sex differences in mathematical ability have never been found, and that when such differences are found they are “massively confounded with factors related to individual experience” (Caplan and Caplan 42). If differences in aptitude and ability do not necessarily force women out of mathematics, then what experiences do young women have within the field that cause them to leave mathematics at the undergraduate, graduate, and professional levels? Researchers have examined women’s experiences within the classroom and in professional settings in an effort to understand why and how young women become alienated from mathematics. The most recent manifestation of this work looks specifically at how our culture constructs both gender and mathematics in ways that ensure that girls and women have a difficult time understanding themselves as mathematicians (Walkerdine; Mendick, “Beautiful”; Mendick, “Mathematical”; Rodd and Bartholomew). Valerie Walkerdine, one of the first to make this argument, states:

Brain Correlates of Non-Symbolic Numerosity Estimation in Low and High Mathematical Ability Children

Previous studies have implicated several brain areas as subserving numerical approximation. Most studies have examined brain correlates of adult numerical approximation and have not considered individual differences in mathematical ability. The present study examined non-symbolic numerical approximation in two groups of 10-year-olds: Children with low and high mathematical ability. The aims of this study were to investigate the brain mechanisms associated with approximate numerosity in children and to assess whether individual differences in mathematical ability are associated with differential brain correlates during the approximation task. The results suggest that, similarly to adults, multiple and distributed brain areas are involved in approximation in children. Despite equal behavioral performance, there were differences in the brain activation patterns between low and high mathematical ability groups during the approximation task. This suggests that individual differences in mathematical ability are reflected in differential brain response during approximation.

Gender differences in mathematics: Does the story need to be rewritten?

Empirical studies of high school mathematics typically report small gender differences in favor of boys. The present article challenges this established finding by comparing two competing structural conceptions of mathematical ability. The standard model assumes mathematical ability alone to account for the interindividual differences observed on the corresponding measures. The nested-factor model assumes interindividual differences in mathematical ability to be explained by two mutually independent factors, namely general cognitive ability and specific mathematical ability. The two models were examined using data from 29,171 ninth-graders. Results from the standard model replicated the typical finding of small gender differences in mathematical ability in favor of boys. However, results from the nested-factor model indicated large to very large gender differences in specific mathematical ability in favor of boys. Implications for research on gender differences in cognitive abilities are discussed.

Individual differences in mathematical competence predict parietal brain activation during mental calculation

Functional neuroimaging studies have revealed that parietal brain circuits subserve arithmetic problem solving and that their recruitment dynamically changes as a function of training and development. The present study investigated whether the brain activation during mental calculation is also modulated by individual differences in mathematical competence. Twenty-five adult students were selected from a larger pool based on their performance on standardized tests of intelligence and arithmetic and divided into groups of individuals with relatively lower and higher mathematical competence. These groups did not differ in their non-numerical intelligence or age. In an fMRI block-design, participants had to verify the correctness of single-digit and multi-digit multiplication problems. Analyses revealed that the individuals with higher mathematical competence displayed stronger activation of the left angular gyrus while solving both types of arithmetic problems. Additional correlational analyses corroborated the association between individual differences in mathematical competence and angular gyrus activation, even when variability in task performance was controlled for. These findings demonstrate that the recruitment of the left angular gyrus during arithmetic problem solving underlies individual differences in mathematical ability and suggests a stronger reliance on automatic, language-mediated processes in more competent individuals.

Individual differences in mathematical ability: genetic, cognitive and behavioural factors

Identifying individuals with mathematical difficulties (MD) is becoming increasingly important in our education system. However, recognising MD is only the first stage in the provision of special educational needs (SEN). Although planning the effective remedial support is vital, there is little consensus on the interventions that are appropriate. There are two main reasons for this: first, MD has a variety of manifestations which appear to change with age; and second, there are many potential causes for the difficulties individuals experience. This paper addresses these issues by reviewing research evidence from three ‘domains’ of psychological research (genetic, cognitive, behavioural), all of which appear to offer insights into potential influences on mathematical ability.

Working memory and literacy as predictors of performance on algebraic word problems

Previous studies on individual differences in mathematical abilities have shown that working memory contributes to early arithmetic performance. In this study, we extended the investigation to algebraic word problem solving. A total of 151 10-year-olds were administered algebraic word problems and measures of working memory, intelligence quotient (IQ), and reading ability. Regression results were consistent with findings from the arithmetic literature showing that a literacy composite measure provided greater contribution than did executive function capacity. However, a series of path analyses showed that the overall contribution of executive function was comparable to that of literacy; the effect of executive function was mediated by that of literacy. Both the phonological loop and the visual spatial sketchpad failed to contribute directly; they contributed only indirectly by way of literacy and performance IQ, respectively.

Gender Equity in Mathematics: Beliefs of Students, Parents, and Teachers

The attitudes about mathematics held by girls and boys participating in a regional mathematics contest, their parents, teachers, and mathematics coaches were investigated. Quantitative data regarding mathematics as a male domain, perception of importance of mathematics, confidence in learning mathematics, effectance motivation, and usefulness of mathematics were obtained. It was found that the traditional gender‐based differences in the beliefs regarding mathematics persist even in these mathematically talented students. Furthermore, parents' responses to the questions regarding the role of mathematics revealed that mothers, more than fathers, focused on the computational aspects of mathematics, while fathers more than mothers mentioned the role of mathematics in science or as a language. Boys, fathers, and certain mathematics teachers admitted to a low level of gender stereotyping, as evidenced by their scores on the Mathematics as a Male Domain subscale. However, the girls, mothers, and mathematics coaches did not endorse this stereotyping. Unsolicited responses of girls and mothers, in fact, emphatically denied that gender stereotyping exists. These findings are discussed in terms of the need to resolve the essential conflicts between students', parents', and teachers' deeply held beliefs regarding the nature of mathematics, gender differences in mathematical abilities, and the desire for equity within mathematics education.

Gender Differences in Advanced Mathematical Problem Solving

Strategy flexibility in mathematical problem solving was investigated. In Studies 1 and 2, high school juniors and seniors solved Scholastic Assessment Test–Mathematics (SAT-M) problems classified as conventional or unconventional. Algorithmic solution strategies were students' default choice for both types of problems across conditions that manipulated item format and solution time. Use of intuitive strategies on unconventional problems was evident only for high-ability students. Male students were more likely than female students to successfully match strategies to problem characteristics. In Study 3, a revised taxonomy of problems based on cognitive solution demands was predictive of gender differences on Graduate Record Examination–Quantitative (GRE-Q) items. Men outperformed women overall, but the difference was greater on items requiring spatial skills, shortcuts, or multiple solution paths than on problems requiring verbal skills or mastery of classroom-based content. Results suggest that strategy flexibility is a source of gender differences in mathematical ability assessed by SAT-M and GRE-Q problem solving.

Sexual selection and sex differences in mathematical abilities

AbstractThe principles of sexual selection were used as an organizing framework for interpreting cross-national patterns of sex differences in mathematical abilities. Cross-national studies suggest that there are no sex differences in biologically primary mathematical abilities, that is, for those mathematical abilities that are found in all cultures as well as in nonhuman primates, and show moderate heritability estimates. Sex differences in several biologically secondary mathematical domains (i.e., those that emerge primarily in school) are found throughout the industrialized world. In particular, males consistently outperform females in the solving of mathematical word problems and geometry. Sexual selection and any associated proximate mechanisms (e.g., sex hormones) influence these sex differences in mathematical performance indirectly. First, sexual selection resulted in greater elaboration in males than in females of the neurocognitive systems that support navigation in three-dimensional space. Knowledge implicit in these systems reflects an understanding of basic Euclidean geometry, and may thus be one source of the male advantage in geometry. Males also use more readily than females these spatial systems in problem-solving situations, which provides them with an advantage in solving word problems and geometry. In addition, sex differences in social styles and interests, which also appear to be related in part to sexual selection, result in sex differences in engagement iii mathematics-related activities, thus further increasing the male advantage in certain mathematical domains. A model that integrates these biological influences with sociocultural influences on the sex differences in mathematical performance is presented in this article.

The logic of the sociobiological model Geary-style

AbstractGeary's is the traditional view of the sexes. Yet each part of his argument – the move from sex differences in spatial ability and social preferences to a sex difference in mathematical ability, the claim that the former are biologically primary, and the sociobiological explanation of these differences – requires considerable further work. The notion of a biologically secondary ability is itself problematic.

Neuroscience, Prejudice, and Human Nature

Because I am generally in agreement with Fox's argument, let's begin with one of the rare points on which I think he is wrong. The problem arises from an apparently erroneous parallel between the human brain and a computer. Fox's main point is, however, both reinforced and clarified by considering the neuroscience of stereotyping and prejudice. In exploring why humans-unlike Star Trek's Mr. Spock or Kahneman and Tversky's rational decision makerare more comfortable with stereotypical thinking than with logically treating each case on its own merits, Fox says that reliance on prejudice or stereotype is a rough-and-ready process whose routine would be an elaborate critical-path analysis and would indeed be a computer program if we could work the whole thing out. In this view, thinking in stereotypes is logical analysis, at a trillion times the speed. I believe this is incorrect-or at least misleading insofar as these kinds of thinking are qualitatively distinct. Cognitive neuroscience has shown that the human brain has a hierarchically organized, modular structure (Gazzaniga, 1985, 1988). For each sensory modality, functionally specialized processing tasks are localized; distinct neuronal structures and pathways process information in parallel. In addition to being shaped by feedback (conditioning, associative learning, memory, etc.), these neuronal modules often exhibit feedforward characteristics: selective response, expectation, and active search for appropriate stimulation. Many neuronal modules or ensembles have innate response tendencies, though in most cases they can be modulated or changed by experience. The holistic, tabula rasa model of the brain, inherited from Locke and the empiricists, and popularized by the behaviorists, is dead. Whereas Kahneman and Tversky apparently conceptualize thought in terms of the processing algorithms of a serial computer, the findings in neuroscience show that the human brain functions as a complex parallel processing system. Within this system, of course, there is a capacity for abstract, linear computation (usually associated with lefthemispheric functioning, though one should beware of the popularized left brain-right brain dichotomy). Individuals differ in the ease with which they use such linear processing-as is evident in differences in mathematical ability. Indeed, variations in the role played by abstract, linear cognitive processing, as contrasted with other modes of concrete and/or holistic response, probably explain not only individual learning styles but also broader gender differences those emphasized by Carol Gilligan (1982). Thinking in stereotypes is thus probably not like conventional computer programming at all. Instead, it seems to represent a mode of pattern matching that is concrete rather than abstract and holistic rather than linear. This difference has profound implications not only for models of artificial intelligence, but also for our understanding of human nature. Why is it, then, that clarifying Fox's apparent mistake only strengthens his main point?