“I Always Feel Dumb in Those Classes”: A Narrative Analysis of Women’s Computing Confidence

Amanda Ross; Sara Hooshangi

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Conference: 2024 ASEE Annual Conference & Exposition
Location: Portland, Oregon
Publication Date: June 23, 2024
Start Date: June 23, 2024
End Date: June 26, 2024
Conference Session: Women in Engineering Division (WIED) Technical Session 1 - Women in Computing
Tagged Division: Women in Engineering Division (WIED)
Tagged Topic: Diversity
Page Count: 12
DOI: 10.18260/1-2--46404
Permanent URL: https://peer.asee.org/46404
Download Count: 97

Paper Authors

biography

Amanda Ross Virginia Polytechnic Institute and State University

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Amanda Ross is a graduate student in the Department of Engineering Education at Virginia Tech. She holds a B.S. in Computer Science and Mathematics from the University of Maryland, Baltimore County.

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biography

Sara Hooshangi The George Washington University

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Dr. Hooshangi is an assistant professor and program director at the College of Professional Studies at The George Washington University. In her role she oversees the operation of an undergraduate degree completion program which allows community college gr

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Abstract

The lack of women in computer science is a decades old problem. Numerous studies have looked at contributing factors that lead to this problem, one of which is lack of self confidence in female students. Having less confidence than their male peers lead women to feel uncomfortable asking questions and speaking out in class, feel isolated in the field, and ultimately steer them away from computer science. The purpose of this study is to understand how women’s computing confidence is shaped by their experiences in introductory computer science courses and to understand how their experiences lead to negative attitudes towards computer science. To answer these questions, this study uses a narrative analysis approach. Four female, non-computer science students at a large public university were interviewed, using a semi-structured protocol. Interviews were then qualitatively coded using thematic analysis, and analyzed using the theoretical frameworks of self-efficacy and self-concept. Results show that while participants were highly successful in their course (reporting a high mark in the class) and had relatively high self-efficacy when discussing specific programming problems, they lacked computing self-concept in whether or not they were good at programming in general. Some participants directly said they were not good at coding, while others noted that they knew they could be successful but then used unconfident language such as stating they often asked ‘stupid questions’ or believed they were only successful due to the help of instructors and TAs. Results also show a common theme in which most participants believed that if they had to work hard in the course, then they were not good at computer science. Understanding how women grapple with self-confidence even while being highly successful in computing courses is needed to better understand how to create environments that are welcoming and inclusive of women. While self-efficacy can be built through mastery experiences, this study suggests that mastery experiences are not enough to build general computing self-concept. Since a lack of computing confidence in women can cause negative attitudes towards the field of computer science, future work should focus on ways in which this confidence can be increased so as to try and minimize the number of women avoiding or leaving the field of computer science.

Citation
Format

Ross, A., & Hooshangi, S. (2024, June), “I Always Feel Dumb in Those Classes”: A Narrative Analysis of Women’s Computing Confidence Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--46404

TY  - CPAPER
AB  - The lack of women in computer science is a decades old problem. Numerous studies have looked at contributing factors that lead to this problem, one of which is lack of self confidence in female students. Having less confidence than their male peers lead women to feel uncomfortable asking questions and speaking out in class, feel isolated in the field, and ultimately steer them away from computer science. The purpose of this study is to understand how women’s computing confidence is shaped by their experiences in introductory computer science courses and to understand how their experiences lead to negative attitudes towards computer science. 
To answer these questions, this study uses a narrative analysis approach. Four female, non-computer science students at a large public university were interviewed, using a semi-structured protocol. Interviews were then qualitatively coded using thematic analysis, and analyzed using the theoretical frameworks of self-efficacy and self-concept. Results show that while participants were highly successful in their course (reporting a high mark in the class) and had relatively high self-efficacy when discussing specific programming problems, they lacked computing self-concept in whether or not they were good at programming in general. Some participants directly said they were not good at coding, while others noted that they knew they could be successful but then used unconfident language such as stating they often asked ‘stupid questions’ or believed they were only successful due to the help of instructors and TAs. Results also show a common theme in which most participants believed that if they had to work hard in the course, then they were not good at computer science. 
Understanding how women grapple with self-confidence even while being highly successful in computing courses is needed to better understand how to create environments that are welcoming and inclusive of women. While self-efficacy can be built through mastery experiences, this study suggests that mastery experiences are not enough to build general computing self-concept. Since a lack of computing confidence in women can cause negative attitudes towards the field of computer science, future work should focus on ways in which this confidence can be increased so as to try and minimize the number of women avoiding or leaving the field of computer science.

AU  - Amanda Ross
AU  - Sara Hooshangi
CY  - Portland, Oregon
DA  - 2024/06/23
PB  - ASEE Conferences
TI  - “I Always Feel Dumb in Those Classes”: A Narrative Analysis of Women’s Computing Confidence
UR  - https://peer.asee.org/46404
DO  - 10.18260/1-2--46404
ER  -