Women who learn computing like men: different gender positions on basic computer courses in adult education

Salminen‐Karlsson, Minna

doi:10.1080/13636820902933254

Cited by 6 publications

(6 citation statements)

References 22 publications

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“…Similar reasons for not majoring in Information Science were given by South African college females (Govender & Khumalo, 2014). Many other studies have found that women's computer self-efficacy is lower than men's (Cassidy & Eachus, 2002;Colbeck, Cabrera, & Terenzini, 2001;He & Freeman, 2010;Keup & Stolzenberg, 2004;Lee, 2003;Lips, 2004;Ogan, Robinson, Ahuja, & Herring, 2006;Salminen-Karlsson, 2009;Sax et al, 2003;Young, 2000;Zarrett et al, 2006). One study found that when controlling for computer anxiety, experience, and knowledge, the gender difference in computing self-efficacy became non-significant (He & Freeman, 2010).…”

Section: Computer Self-efficacy and Experiencementioning

confidence: 69%

“…Even women with high computer self-efficacy prefer cooperative learning styles more than men do (Salminen-Karlsson, 2009). These kinds of learning styles are still unpopular with many CS instructors who are often characterized as less supportive than instructors in other disciplines (Barker, Garvin-Doxas, & Jackson, 2002).…”

Section: Values and Interestsmentioning

confidence: 99%

“…Beyer & Haller, 2006;Carter, 2006;He & Freeman, 2010;Katz et al, 2003;Salminen-Karlsson, 2009). This is exemplified in this study by men's greater likelihood to have installed internal components such as RAM.…”

Section: Computer Self-efficacy and Experiencementioning

confidence: 99%

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Why are women underrepresented in Computer Science? Gender differences in stereotypes, self-efficacy, values, and interests and predictors of future CS course-taking and grades

Beyer

2014

Computer Science Education

250

147

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Section: Computer Self-efficacy and Experiencementioning

confidence: 69%

Section: Values and Interestsmentioning

confidence: 99%

See 1 more Smart Citation

Why are women underrepresented in Computer Science? Gender differences in stereotypes, self-efficacy, values, and interests and predictors of future CS course-taking and grades

Beyer

2014

Computer Science Education

250

147

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“…It is also possible that the competitive nature of these robotics programs is simply not as appealing to adolescent females as it is to adolescent males. Research has shown that even women with high levels of computer self-efficacy are drawn to cooperative learning styles (Salminen-Karlsson, 2009). Further research is necessary in order to determine what factors can keep girls engaged in robotics competitions through high school and whether these experiences actually lead them to pursue STEM majors in college and STEM careers later in life or not.…”

Section: Gender Issues and Robotics Competitionsmentioning

confidence: 99%

“…Self-Efficacy (or one's expectancy of success) is an important part of how we make educational and occupational choices (Correll, 2004). Many studies have demonstrated that women's computer selfefficacy is lower than men's, which may be one reason why there are fewer women in these fields (Beyer, 2014;Cassidy & Eachus, 2002;Colbeck, Cabrera, & Terenzini, 2001;Salminen-Karlsson, 2009;Zarrett, Malanchuk, Davis-Kean, & Eccles, 2006). It is possible that increasing girls' confidence is as important as increasing their competence or knowledge in engineering areas.…”

Section: Increasing Female Students' Confidencementioning

confidence: 99%

VEX Robotics Competitions: Gender Differences in Student Attitudes and Experiences

Sullivan

Bers

2019

JITE:Research

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Aim/Purpose: Educational robotics competitions are a popular way to increase students’ interest in science and engineering during their K-12 years. However, female students are typically underrepresented in these competitions. The goal of this study is to determine differences in the experiences of male and female robotics competition students in order to better support female students and increase their representation in competition leagues. Background: VEX Robotics Competitions are one of the fastest-growing educational robotics competitions available to middle school and high school students around the world. Despite growing numbers of participants, VEX programs have a notice-able lack of female participants. In order to create a more diverse and representative program, it is important to investigate why fewer female students participate in the competitions and what can be done to better support female students. Methodology: Qualitative and quantitative data were collected from VEX mentors and students through online surveys. A total sample of N=675 VEX mentors and students participated (n=47 students and n=628 mentors). The surveys asked scaled, multiple choice, and free response questions. Through these surveys, the following research questions are answered: 1) What (if any) are the differences between male and female student experiences with VEX? 2) What (if any) are the differences in male and female students’ confidence in their technical ability? and 3) What (if any) are the differences in male and female students’ performance on VEX related robotics team tasks? Contribution: This study contributes to the growing body of work on engaging female students, and other underrepresented students, in STEM fields such as programming, engineering, and robotics. Findings: Results demonstrate the male students outnumber female students and male mentors also outnumber female mentors in this sample. Male students are significantly more confident in their general technical ability and their ability to put things together (p<.05) and students of both genders generally wished to have more female students on their teams. Results also indicate that mentors generally perceive their female students as requiring more help and that they are less engaged with construction tasks as compared to male students. Recommendations for Practitioners: VEX mentors should focus on enhancing female students’ confidence with the construction and building aspects of robotics and ensuring they get the same experience with these tasks as male students. They should consider providing supplemental hands-on training sessions, within or outside of regular team sessions, for students who wish to build confidence and experience in these areas. Recommendation for Researchers: Researchers should continue to explore the experiences of female students in robotics competitions, including differences based on grade level, mentor gender, and more. Researchers should additionally look at female students who are not a part of robotics teams (or who have left a robotics team) to understand why these teams do not appeal to them. Impact on Society: Women are still underrepresented in engineering and computer science professions. In order to bridge this gap, it is critical to find effective ways to reach girls in their K-12 years to build their confidence and interest in these fields before they reach college. This study points out critical areas where robotics competition teams should focus on building female students’ confidence. Future Research: The findings in this paper present research from year 1 of a multi-year longitudinal study. Future research will continue to track the mentors and students in this study in order to gain information on retention and change over time.

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“CodePlus”—Measuring Short-Term Efficacy in a Non-Formal, All-Female CS Outreach Programme

Lawlor

Byrne

Tangney

2020

ACM Trans. Comput. Educ.

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The provision of all-female computer science outreach programmes is a common strategy used to foster greater interest in the subject for high school aged girls. Based on key factors that affect girls’ interest in computer science (CS), outreach programmes often share much in their approach. Nonetheless, there is criticism from a research perspective concerning how programmes evaluate their efficacy, and how the role of pedagogy is under-explored. This article describes the design of CodePlus, a non-formal CS outreach programme based in an Irish University, Trinity College Dublin, and the methods by which the programme is evaluated. This article aims to contribute to this area by reporting on a social constructivist pedagogical model for all-female CS outreach activities, evaluated with a structured research approach. The results from the large sample size ( n =856) are positive, with participants showing statistically significant changes in key attitudinal and intentional variables concerning girls’ interest in studying computer science.

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Women who learn computing like men: different gender positions on basic computer courses in adult education

Cited by 6 publications

References 22 publications

Why are women underrepresented in Computer Science? Gender differences in stereotypes, self-efficacy, values, and interests and predictors of future CS course-taking and grades

Why are women underrepresented in Computer Science? Gender differences in stereotypes, self-efficacy, values, and interests and predictors of future CS course-taking and grades

VEX Robotics Competitions: Gender Differences in Student Attitudes and Experiences

“CodePlus”—Measuring Short-Term Efficacy in a Non-Formal, All-Female CS Outreach Programme

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