Difference between revisions of "Biology is not destiny"

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[note from ab: Race and gender are social constructions.  ALSO challenge the notion that economic intuition is inborn. It can be taught/learned/acquired--why else are we here?]
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[note from ab: Target to teacher as well as to student.  Explain that race and gender are social constructions.   
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ALSO challenge the notion that economic intuition is inborn. It can be taught/learned/acquired--why else are we here?
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ALSO see heterodox page cite: "One last interesting article I will mention is Cecilia Conrad’s critique of race as a category in econometric OLS regression techniques. Here, the assumption that race is a fixed variable from sample to sample does not capture the inherent fluidity of this socially constructed category that is reinvented time and time again. Race is an unstable category. Lack of attention to historical understandings of race can lead to false conclusions in studies on, say, longitudinal differences in wage. Conrad offers some clues as to how a more fluid representation of race can be incorporated into econometric models (endogenous variables with simultaneous equations) but does not suggest any kind of firm answer."]

Revision as of 12:13, 9 June 2011

"Biology is not destiny" refers to the idea that female students are often stuck in this mindset that intelligence is inherent and it cannot be expanded. Societal beliefs about intelligence and a learning environment are key issues that make a female student competent in various academic fields.

In one finding, when teachers and instructors tell female students that their intelligence can grow and expand with learning and experience, the students do better on math tests and are more optimistic about their futures in the mathematics field. By emphasizing that intelligence is nurture, not nature (especially in male-dominant fields), professors create inclusive environments where female students feel more confident about their skills and abilities.

At Stanford University, Carol Dweck, a social and developmental psychologist, has been conducting research on the idea of motivation for the past 40 years. She argues that there are two kinds of mindset when it comes to academic motivation. "A 'growth mindset' (viewing intelligence as a changeable, malleable attribute that can be developed through effort) as opposed to a 'fixed mindset' (viewing intelligence as an inborn, uncontrollable trait) is likely to lead to greater persistence in the face of adversity and ultimately success in any realm."

Dweck finds that fixed mindsets among students in junior high and college plays a role in creating a gender gap with boys performing well in math and science and growth mindsets among students create no sort of gender gap in academic performance. Dweck and her colleges followed several hundred women at a top-tier univesity in a one semester calculus course and found that growth mindsets also promotes persistence for students. Female students in classrooms where growth mindsets are promoted are more likely to continue taking classes in that field and were less susceptible to negative gender stereotypes about intelligence.

Faculty in tertiary education should stress to female students that academic skills and abilities can be acquired through hard work and biology does not determine intelligence.

Citation: Dweck, C. (2008). Mindsets and math/science achievement. New York: Carnegie Corporation of New York, Institute for Advanced Study, Commission on Mathematics and Science Education as cited in Hill et al. (2010). "Why so Few? Women in Science, Technology, Engineering, and Mathematics". American Association of University Women.

Name: Angela

Rating: 8


[note from ab: Target to teacher as well as to student. Explain that race and gender are social constructions. ALSO challenge the notion that economic intuition is inborn. It can be taught/learned/acquired--why else are we here? ALSO see heterodox page cite: "One last interesting article I will mention is Cecilia Conrad’s critique of race as a category in econometric OLS regression techniques. Here, the assumption that race is a fixed variable from sample to sample does not capture the inherent fluidity of this socially constructed category that is reinvented time and time again. Race is an unstable category. Lack of attention to historical understandings of race can lead to false conclusions in studies on, say, longitudinal differences in wage. Conrad offers some clues as to how a more fluid representation of race can be incorporated into econometric models (endogenous variables with simultaneous equations) but does not suggest any kind of firm answer."]