Gender Equity in Computing Rita M. Powell Department Manager Dept. of Computer & Information Science

Statistics on Women’s Participation in Computer Science: 20% of undergraduates in selective computer science programs are women. Women held only 24% of degreed IT positions. Technology jobs will increase by 75% between 2000 and 2010, accounting for 15 percent of all new jobs in the American economy. In 1998, women earned only 27% of the degrees awarded in Computer Science. Women’s retention in undergraduate programs of Computer Science is only about 42% as compared to 70% for men.

Why and What can we do?

What the research tells us: Influencing Factors Family Environment and Support Student behavior factors such as attitudes, aspirations, and academic preparation. School/institution factors such as precollege curriculum and instruction and postsecondary special programs in recruitment, retention and financial aid.

Family Environment and Support   Parent’s educational attainment and occupation

Student Behavior—Attitudes and Aspirations: Gender differences Low self-confidence

Attitudes regarding quantitative subjects: Relative to men, women may be more sensitive to social relationships value more human aspects of the environment. Women dislike highly abstract nature of S&E knowledge Women tend to dislike strong competitive environment of S&E depts.

Gender Roles Gender roles—prioritizing career vs. marriage/family Research mixed here. Some researchers found that women with strong career commitments gravitate towanrd S&E. Unique psychological difficulty of minority students—Over-confidence and poor preparation These attitudes become apparent during middle school and are held by college women.

Academic Preparation Gender gap in science related achievement not as great as gender differences in science related attitudes and activities. Girls and underrepresented minorities found to have taken fewer advanced courses in math in high school than males and white and Asian peers. Girls that major in computer science are often the products of and excelled in schools with strong math curricula.

School/Institution Factors Precollege Education Intensive curricula and excellent instruction in high school mathematics coupled with high expectations Teachers and Counselors Counselors’ encouragement in choice of S&E majors. Quality of math and science teachers. Teachers’ expectations of girls vs. boys Teachers’ interaction with girls vs. boys

Postsecondary Institutions Small liberal arts colleges with an apprenticeship model of education do better! Academic and Social climates of the institution: Contents and approach to S&E education are inherently disadvantageous to women and underrepresented minorities.

How? Valuing personal success VS. Valuing people and groups Over-emphasis on grades at the expense of other assessment methods Need to match special programs for recruitment and retention with effective program organization to support admitted students. Need to offer Enrichment programs, not remedial programs

My study: freshmen women’s persistence in computer science at Penn

Women’s issues that impact their success in the first year of the major: Lack of a community Perceived lack of prior experience in computer science Lack of confidence in their ability to learn computer science. Distaste for the competitive, male environment termed “CSish attitudes,” impeded cooperative and collaborative learning and formation of community within the student body. Testing Anxiety which develops from Stereotype Threat. Poor or mediocre grades. Fear of not being passionate enough about computer science.

Remedies: What helps? What works to encourage women’s persistenc high school teachers’ encouragement Parental encouragement and support Build community within the school and the department through shared activities and experiences. Increase collaborative learning opportunities Increase faculty involvement

Remedies: What helps. What works to encourage women’s persistenc (cont Show students what they can do with computer science in addition to programming: Artificial Intelligence Robotics Cognitive Science applications Bioinformatics Natural Language Processing Computer animation Business applications Network security Internet application Computer game development Computer vision