Book contents
- Frontmatter
- Contents
- Preface
- Acknowledgments
- List of Contributors
- 1 Research on the Women and Mathematics Issue: A Personal Case History
- 2 The Perseverative Search for Sex Differences in Mathematics Ability
- 3 A Psychobiosocial Model: Why Females Are Sometimes Greater Than and Sometimes Less Than Males in Math Achievement
- 4 Gender Differences in Math: Cognitive Processes in an Expanded Framework
- 5 Cognitive Contributions to Sex Differences in Math Performance
- 6 Spatial Ability as a Mediator of Gender Differences on Mathematics Tests: A Biological–Environmental Framework
- 7 Examining Gender-Related Differential Item Functioning Using Insights from Psychometric and Multicontext Theory
- 8 The Gender-Gap Artifact: Women's Underperformance in Quantitative Domains Through the Lens of Stereotype Threat
- 9 “Math is hard!” (Barbie™, 1994): Responses of Threat vs. Challenge-Mediated Arousal to Stereotypes Alleging Intellectual Inferiority
- 10 The Role of Ethnicity on the Gender Gap in Mathematics
- 11 The Gender Gap in Mathematics: Merely a Step Function?
- 12 “I can, but I don't want to”: The Impact of Parents, Interests, and Activities on Gender Differences in Math
- 13 Gender Effects on Mathematics Achievement: Mediating Role of State and Trait Self-Regulation
- 14 Gender Differences in Mathematics Self-Efficacy Beliefs
- 15 Gender Differences in Mathematics: What We Know and What We Need to Know
- Author Index
- Subject Index
- References
3 - A Psychobiosocial Model: Why Females Are Sometimes Greater Than and Sometimes Less Than Males in Math Achievement
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface
- Acknowledgments
- List of Contributors
- 1 Research on the Women and Mathematics Issue: A Personal Case History
- 2 The Perseverative Search for Sex Differences in Mathematics Ability
- 3 A Psychobiosocial Model: Why Females Are Sometimes Greater Than and Sometimes Less Than Males in Math Achievement
- 4 Gender Differences in Math: Cognitive Processes in an Expanded Framework
- 5 Cognitive Contributions to Sex Differences in Math Performance
- 6 Spatial Ability as a Mediator of Gender Differences on Mathematics Tests: A Biological–Environmental Framework
- 7 Examining Gender-Related Differential Item Functioning Using Insights from Psychometric and Multicontext Theory
- 8 The Gender-Gap Artifact: Women's Underperformance in Quantitative Domains Through the Lens of Stereotype Threat
- 9 “Math is hard!” (Barbie™, 1994): Responses of Threat vs. Challenge-Mediated Arousal to Stereotypes Alleging Intellectual Inferiority
- 10 The Role of Ethnicity on the Gender Gap in Mathematics
- 11 The Gender Gap in Mathematics: Merely a Step Function?
- 12 “I can, but I don't want to”: The Impact of Parents, Interests, and Activities on Gender Differences in Math
- 13 Gender Effects on Mathematics Achievement: Mediating Role of State and Trait Self-Regulation
- 14 Gender Differences in Mathematics Self-Efficacy Beliefs
- 15 Gender Differences in Mathematics: What We Know and What We Need to Know
- Author Index
- Subject Index
- References
Summary
We have some numbers that may surprise you, but first you need to supply some of your own. Make your best estimate in answering the following questions: What percentage of all accountants and auditors in the United States in 1983 were female? Now answer the same question for the year 2000. What about other math-intensive professions, say economists? What percentage of economists in the United States in 1983 and in 2000 were female? What about the percentage of all engineers who were female in 1983 and in 2000? Finally, is the difference in achievement scores between girls and boys much larger on tests of reading literacy or tests of mathematical literacy?
Are you fairly confident about your answers? Give yourself a “point” for each answer you supplied that is within five percentage points of the correct answer. According to the U.S. Bureau of the Census (2001), the majority of accountants and auditors in 2000 were female (56.7%), up considerably from 1983 when females made up slightly more than one-third of this profession (36.7%). The comparable values for economists in 1983 and 2000 were 37.9% and 53.3%. Surprised that these values are so high? Most people are. What about engineers? Females were 5.9% of all engineers in 1983 and still only 9.9% in 2000 – values that are probably closer to what most people estimated for all these math-intensive professions.
- Type
- Chapter
- Information
- Gender Differences in MathematicsAn Integrative Psychological Approach, pp. 48 - 72Publisher: Cambridge University PressPrint publication year: 2004
References
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