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Factors Associated With Women's Interest In Computing Fields

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Conference

2006 Annual Conference & Exposition

Location

Chicago, Illinois

Publication Date

June 18, 2006

Start Date

June 18, 2006

End Date

June 21, 2006

ISSN

2153-5965

Conference Session

Climate Issues for Women Students

Tagged Division

Women in Engineering

Page Count

17

Page Numbers

11.632.1 - 11.632.17

DOI

10.18260/1-2--343

Permanent URL

https://peer.asee.org/343

Download Count

103

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Paper Authors

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Elizabeth Creamer Virginia Tech

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Elizabeth Creamer is an associate professor of educational research in the Department of Educational Research and Policy Studies at Viginia Tech. She is the co-PI of the Women and Information Technology project funded by NSF, PI of a grant to assess the climate of engineering departments, and Director of Research and Assessment for the Virginia Tech Advance Project. Creamer's disciplinary background is in the field of higher education and her research insterests involve gender equity and faculty careers and work-family issues.

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biography

Soyoung Lee Virginia Tech

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Soyoung Lee is a graduate research assistant for the Women in Information Technology Project and a doctoral candidate in Human Development at Virginia Tech.

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Peggy Meszaros

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Dr. Peggy S. Meszaros is the William E. Lavery Professor of Human Development and Director of the Center for Information Technology Impacts on Children, Youth, and Families. She is the former Senior Vice President and Provost at Virginia Tech and has been a faculty member and administrator for 28 years at private and public research universities. She has published over 80 scholarly articles and book chapters on research topics such as academic benchmarking, mother and daughter communication, adolescent decision-making, and the application of technology to areas like cell phone use and parent education.

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Abstract
NOTE: The first page of text has been automatically extracted and included below in lieu of an abstract

Factors Associated with Women’s Interest in Computing Fieldsi

Abstract

This paper presents a theoretically driven and empirically supported model that identifies key factors that predict high school and college women’s interest and choice in a career in information technology (IT). At the center of the model is the developmental construct of self- authorship and variables related to the process individuals use to make personal and educational decisions. For female high school and college students, the expression of interest in a career in the IT field is often made with little concrete information from sources outside of the immediate circle of trusted friends and family members. Findings have direct implications for recruiting and advising practice.

Introduction

Research since the early 1970s indicates that a different set of variables are required in models that predict women’s and men’s career interests and choice30. There are particularly significant gender differences in how men and women become interested in, enter, and remain in the computing field2. A number of factors are associated with women’s career interests that are not significant for men. These include self-efficacy5, consideration of the needs of others39, attachment to parents4, 31, 34 and the value awarded to marriage and a family16. There is a much weaker connection for women than there is for men between interests, enjoyment, and career choice31.

The purpose of this paper is to explain a theoretically driven statistical model of key variables that predict high school and college women’s interest and choice of a career in a computer-related field and to identify areas where there are statistically significant gender differences. Our focus is on careers in the field of information technology (IT). By IT, we mean a full range of professional careers that are computer driven, including those that involve web design, web development, and hardware and software engineering, but exclude data processing.

Theoretical Framework

We employ the developmental construct of self-authorship as a theoretical lens to understand the cognitive processes students use to make decisions, including career decisions9. Defined as “the ability to collect, interpret, and analyze information and reflect on one’s own beliefs in order to form judgments” (p. 143) 6, self-authorship is grounded in the work of Perry33 and Kegan23. Self-authorship is linked to decision making because it influences how individuals

Creamer, E., & Lee, S., & Meszaros, P. (2006, June), Factors Associated With Women's Interest In Computing Fields Paper presented at 2006 Annual Conference & Exposition, Chicago, Illinois. 10.18260/1-2--343

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