holly r. lord j. mcgrath cohoon gender diversity in computing workshop
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Defining Academic “Quality”: The Gendered Effects of Admissions Criteria in Doctoral CS and CE Programs. Holly R. Lord J. McGrath Cohoon Gender Diversity in Computing Workshop. Big Picture, Bottom Line, Overview. Recruitment practices affect women’s representation - PowerPoint PPT PresentationTRANSCRIPT
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Defining Academic “Quality”: The Gendered Effects of Admissions Criteria in Doctoral CS and CE Programs
Defining Academic “Quality”: The Gendered Effects of Admissions Criteria in Doctoral CS and CE Programs
Holly R. LordJ. McGrath Cohoon
Gender Diversity in Computing Workshop
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Big Picture, Bottom Line, OverviewBig Picture, Bottom Line, Overview
Recruitment practices affect women’s representation
Admission criteria affect women’s representation
Institutional characteristics affect women’s representation
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Data are from a large studyData are from a large study
Three surveys in Fall 2003
Stratified random sample of 48 departments
775 faculty members 1976 students Master’s and PhD
Response rates • 94% chair• 63% faculty• 55% grad students
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Notable Gender Differences in Program ChoiceNotable Gender Differences in Program Choice
Women more than men emphasized• Geographic preferences or constraints• Impression of faculty from campus visit• Department culture• Flexibility in program content
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Recruitment ModelRecruitment Model
Regression on Women's Representation in Graduate CSE Programs
Beta for all
departmentsBeta for departments
where effort >=2.6
n=46 n=34
Flexibility in program content 0.21* 0.18
Personal recruitment by men -0.49** -0.35*
Effort to enroll women 0.29* 0.36*
Adjusted R2 0.29** 0.29**
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How do admissions criteria affect women’s representation?How do admissions criteria affect women’s representation?
Admissions criteria• formal index• ambiguous index• other criteria
Admissions-related attitudes
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Dependent Variable: female proportion PhD studentsDependent Variable: female proportion PhD students
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ControlsControls
Public/private
1993 National Research Council rank
Program size
Student/faculty ratio
Proportion of female faculty
Carnegie classification
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Ambiguous criteria are commonly used to assess applicant qualityAmbiguous criteria are commonly used to assess applicant quality
#1 General quality of academic record
#2 Motivation
#4 Academic letters of recommendation
#6 Communication skills
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Extensive & Intensive differ in emphasisExtensive & Intensive differ in emphasis
Grades in computing courses 85% 94%
Communication skills 73% 64%
Res. Exten. Res.Inten.
% of faculty rating criteria very or extremely important
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Faculty want to increase diversityFaculty want to increase diversity
Most agree their department should actively recruit underrepresented groups (80%)
Few faculty believe CSE is inherently unattractive to women (21%)
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Women’s Representation is Lower in Research Extensive InstitutionsWomen’s Representation is Lower in Research Extensive Institutions
Research extensive
Female proportion PhDs-
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Formal index exhibited no effectFormal index exhibited no effect
Formal index (functionally relevant, specific) • grades in computing courses• math background• GRE Score• reputation of undergraduate institution/program
No measurable relationship with women’s representation
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Ambiguous criteria has a positive affectAmbiguous criteria has a positive affect
Ambiguity Index • general quality of academic record• motivation• communication skills• maturity• academic letters of recommendation
women’s
representation+
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Life experience criterion favors womenLife experience criterion favors women
Consider life experiences
Ambiguous criteria
Female Proportion ofPhDs
+
++
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Diversity as a criterion favors womenDiversity as a criterion favors women
Membership in an underrepresented group
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Gendered criteria has an affectGendered criteria has an affect
Computing work/volunteer experience negatively affects the gender balance
www.cptc.edu/.../Computer%20Work%20Station.jpg
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Final ModelFinal ModelRegression Results for Women's Representation
Beta t test Sig.
Carnegie Classification -0.33 0.00
Member of underrepresented group 0.41 0.00
Computing work or volunteer experience -0.36 0.01
Consider life experience 0.44 0.00
Constant ns
Adjusted R-squared for model 0.46 0.00
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Questions?Questions?