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How true are they? Sam Langdon, Ajit Singh, Jill Thompson

Gender Stereotypes in School. VS. How true are they? Sam Langdon, Ajit Singh, Jill Thompson. Overview. An overview of gender stereotypes The Statement of the Problem The Experimental Design DATA Analysis Outcome Evaluation/Final Notes. What is a Stereotype?.

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How true are they? Sam Langdon, Ajit Singh, Jill Thompson

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  1. Gender Stereotypes in School VS How true are they? Sam Langdon, Ajit Singh, Jill Thompson

  2. Overview • An overview of gender stereotypes • The Statement of the Problem • The Experimental Design • DATA Analysis • Outcome • Evaluation/Final Notes

  3. What is a Stereotype? A widely held but fixed and oversimplified image or idea of a particular type of person or thing Stereotypes can exist along many lines: race, gender, class, etc. We chose to focus our study on a particular gender stereotype prevalent in schools

  4. Why Stereotypes? • “Women can’t do math! It explains why they can’t measure distances” • “English?! What with all the girls? No way…” • “Girls can’t do physics… Are you joking?” • “Guys are too stupid to be smart…”

  5. Where do these myths come from? • There were many matriarchal societies even as late as the 2nd century BC • With the advent of private property, women were held in a lower regard in society • They were seen as less capable in moving humans forward (ie math and science capability) • Men were viewed as conquerors, and during the onset of imperialism, were often portrayed as savages

  6. Don’t Stereotypes Reflect an opinion that’s mostly true? • Humans form snap judgments as an evolutionary mechanism to quickly analyze a complex situation • Stereotypes may describe an overlying trend among a specific population • However, it is inappropriate to assume that a particular individual will demonstrate the same behavior

  7. What do the “Experts” Suggest? In an Implicit Association Test conducted by the University of Washington, researchers found evidence to suggest that children as young as 7 begin forming stereotypes in regards to subjects. The results were significant at an alpha level of 0.05.

  8. What we decided to do • We wanted to see if there is some truth to gender stereotypes in school. Do males and females enroll differently in advanced classes in math and science vs. the humanities?

  9. Introduction • Our group looked at enrollment in advanced classes in regards to gender distribution. • We are looking at the comparison between math and sciences classes versus humanities classes.

  10. Humanities • AP American Government • AP American History • AP Art History • AP Economics • AP English Language • AP English Literature • AP Music Theory • AP Psychology

  11. Math & Science • AP Biology • AP Calculus BC • AP Chemistry • AP Environmental Science • AP Physics C • AP Statistics • Honors Anatomy and Physiology • Honors Java 1

  12. Design Gather rosters of advanced-level students with respect to gender, separate the students by Humanities and Math/Science, eliminate repeating students within each section, and eliminate underclassmen Establish the null and alternative hypotheses for a chi-square test of independence Ho = Enrollment in specific sections of advanced classes and gender are independent HA = Enrollment in specific sections of advanced classes and gender are not independent Check assumptions and conditions Perform the chi-square test of independence (2 -1)(2 -1) = 1 degrees of freedom, using the equation:

  13. Counts of Advanced Students with Respect to Gender and Section By compiling the rosters for humanities classes and the rosters for math and science classes, the group was able to count the total number of advanced students in each field with respect to gender. The group eliminated repeated students in each section, in order to obtain counts within specific sections. Underclassmen in the rosters were eliminated in order to restrict the population at hand. For both years 2009-2010 and 2010-2011 … The expected values for both years are …

  14. Graphical Displays As seen in the segmented bar chart to the left, significantly more students are enrolled in humanities than math/science. In both humanities and math/science, the majority of students enrolled are female.

  15. Assumptions and Conditions • We know that while the data was not collected randomly, it was collected in a way to prevent bias. • Everything is a count • The Observed Cell Frequency is met, all are greater than five

  16. Conclusions • The Chi square value was 0.945, with a P-Value of 0.331. • This exceeds the Alpha level of 0.1 • We fail to reject the null hypothesis that class enrollment by sections and gender are independent • There is not enough evidence to prove association

  17. Conclusions (cont.) • Certain classes did not align with the results like Honors Java, AP Physics C, and AP Calculus BC • These classes had a male bias whereas the rest of science and math had a female bias. • We may want to look further into that to expand the study.

  18. Improvements • We could expand the study beyond Newtown High school • We could include more than just the previous year and this year • This would allow us to make broader generalizations and give us more data • Why are more students are enrolled in humanities than math/science?

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