Changes in CS students' sttitudes towards CS over time (original) (raw)
Related papers
Computer Science Education, 2014
This study addresses why women are underrepresented in Computer Science (CS). Data from 1319 American first-year college students (872 female and 447 male) indicate that gender differences in computer selfefficacy, stereotypes, interests, values, interpersonal orientation, and personality exist. If students had had a positive experience in their first CS course, they had a stronger intention to take another CS course. A subset of 128 students (68 females and 60 males) took a CS course up to one year later. Students who were interested in CS, had high computer self-efficacy, were low in family orientation, low in conscientiousness, and low in openness to experiences were more likely to take CS courses. Furthermore, individuals who were highly conscientious and low in relationalinterdependent self-construal earned the highest CS grades. Efforts to improve women's representation in CS should bear these results in mind.
Gender differences in computer science students
ACM SIGCSE Bulletin, 2003
We examined gender differences and differences in Computer Science (CS) majors vs. non-majors in ability in quantitative areas, educational goals and interests, experience with computers, stereotypes and knowledge about CS, confidence, personality, support and encouragement, stress and financial issues, gender discrimination, and attitudes toward the academic environment in CS. What is unique to this investigation is its multivariate nature. While others have studied these variables in isolation, our study looks at them collectively to identify important interactions among variables. This will eventually allow us to identify a profile of women who pursue careers in CS. The findings are reported in detail below. Particularly noteworthy is that men had more confidence in using computers than did women even when statistically controlling quantitative ability.
Journal of Women and Minorities in Science and Engineering
Although teenage girls engage in coding courses, only a small percentage of them plan to pursue Computer Science (CS) as a major when choosing a career path. Gender differences in interests, sense-of belonging, self-efficacy, and engagement in CS are already present at that age. This article presents an overview of gender stereotypes by summarizing the negative impressions female teenagers experience during CS classes and also influences that may be preventing girls from taking an interest in CS. The study draws on published research since 2006 and argues that those findings point to the existence of the stereotypical image of a helpless, uninterested, and unhappy "Girl in Computing". It may be even more troubling a construct than that of the geeky, nerdy male counterpart, as it is rooted in the notion that women are technologically inept and ill-suited for CS careers. Thus, female teenagers think they must be hyper-intelligent as opposed to motivated, interested, and focused to succeed in those fields. To make CS more inclusive for teenage girls, cultural implications, as well as stereotypization in CS classrooms and CS education, need to be considered as harmful and must be eliminated by empowering female teenagers through direct encouragement, mentoring programs, or girls-only initiatives.
Gender differences in attitudes toward and confidence in computer science
2002
A study examined gender and student group differences in stereotypes and confidence for first-year and more advanced computer science (CS) students. In the spring of 2001, 18-page questionnaires were distributed to first-year students (n=30: 21 females, 9 males) and students enrolled in an introductory CS course (n=32: 11 females, 21 males) designed for students considering majoring in CS. Findings showed no gender difference in coMputer confidence for first-year students, but females in CS had significantly lower confidence than did males. (Contains 27 references.)
2008
This study focuses on how Computer Science and Engineering Students (CSESs) of both genders address certain critical issues for gender differences in the field of Computer Science and Engineering (CSE). This case study is based on research conducted on a sample of 99 Greek CSESs, 43 of which were women. More specifically, these students were asked to respond to a specially designed questionnaire addressing the following issues: a) essential motives in selecting CSE as a subject of study, their primary experience with computers and their family’s views regarding CSE as a career prospect, b) the relationship between gender, strengths and weaknesses in CSE and cooperation with fellow students of the opposite gender, c) the desirability of having both male and female University Professors in CSE, d) CSE courses and CSESs choice, and e) career issues. The analysis of the data shows that: a) gender inequality in CSE still exists at tertiary level, b) there is a number of students of both ...
How Gender Issues Can Influence Studying Computer Science
Proceedings of the First International Conference on Computer Supported Education, 2009
Sad; in order to explore the following points amongst female undergraduate students: (i) general success rate, (ii) professional confidence, interests and ambitions, (iii) level of satisfaction with the choice of studies, (iv) attitudes and beliefs towards the gender issue. The query resulted in indicative statistical data, providing basis for future work and discussion, as a contribution to narrowing of the gender gap within the field of Computer Science.
Exploring Gender Diversity in CS at a Large Public R1 Research University
2017
With the number of Computer Science (CS) jobs on the rise, there is a greater need for Computer Science graduates than ever. At the same time, most CS departments across the country are only seeing 25-30% of female students in their classes, meaning that we are failing to draw interest from a large portion of the population. In this work, we explore the gender gap in CS at Rutgers University using three data sets that span thousands of students across 3.5 academic years. By combining these data sets, we can explore interesting issues such as retention, as students progress through the CS major. For example, we find that a large percentage of women taking the Introductory CS1 course for majors do not intend to major in CS, which contributes to a large increase in the gender gap immediately after CS1. This finding implies that a large part of the retention task is attracting these women to further explore the major. We correlate our findings with initiatives that some CS programs across the country have taken to significantly improve their gender diversity, and identify initiatives that we can start with in our effort to increase the diversity in our program. These findings may also be applicable to the computing programs at other large public research universities.
Identifying Barriers for Women Participation in Computer Science
Pro Edu. International Journal of Educational Sciences
This study focuses on the development of a framework for the identification of main barriers that discourage women to pursue Computer Science (CS) as their University studies and their careers options. The proposed framework is based on the analysis of secondary data emerged from the research literature. In fact, a large number of papers were qualitatively analyzed and the themes who act as barriers for women participation in the CS scientific field and career were estimated. The analysis of the data identifies as essential barriers: school, family, computer games, role models, peers and work culture, stereotypes and communication of stereotypes. All these barriers form a model that seemed to shape females' perceptions, attitudes, interest, confidence and career decisions regarding CS education and career choices. Based on the aforementioned barriers, proposals for future research dimensions and suggestions for the treatment of the phenomenon of females' under-representation in CS education is given.
2019
Although teenage girls engage in coding courses, only a small percentage of them plan to pursue Computer Science (CS) as a major when choosing a career path. Gender differences in interests, sense-of belonging, self-efficacy, and engagement in CS are already present at that age. This article presents an overview of gender stereotypes by summarizing the negative impressions female teenagers experience during CS classes and also influences that may be preventing girls from taking an interest in CS. The study draws on published research since 2006 and argues that those findings point to the existence of the stereotypical image of a helpless, uninterested, and unhappy "Girl in Computing". It may be even more troubling a construct than that of the geeky, nerdy male counterpart, as it is rooted in the notion that women are technologically inept and ill-suited for CS careers. Thus, female teenagers think they must be hyper-intelligent as opposed to motivated, interested, and focu...
Gender Diversity in Computer Science at a Large Research University
2020
With the number of Computer Science (CS) jobs on the rise, there is a greater need for Computer Science graduates than ever. At the same time, most CS departments across the country are only seeing 25-30% of female students in their classes, meaning that we are failing to draw interest from a large portion of the population. In this work, we explore the gender gap in CS at a large public research university, using three data sets that span thousands of students across 5.5 academic years. By combining these data sets, we can explore many issues such as retention as students progress through the CS major. For example, we nd that a large percentage of women taking the Introductory CS1 course for majors do not intend to major in CS, which contributes to a large increase in the gender gap immediately a er CS1. is nding implies that a large part of the retention task is a racting these women to further explore the major. We report ndings in three areas of research in the context of the CS department at our university: the CS environment, the computing background of our students, and the students' grades. ese ndings may also be applicable to computing programs at other large public research universities.