Gender Differences in Computer Science Education: Lessons Learnt from an Empirical Study at NTNU

Research in Computer Science (CS) education has focused on gender differences and there is high interest in increasing female participation in CS. The present study reviews important factors that influence CS students’ decision to complete their studies in CS (retention), and empirically examines how these factors differ for males and females. To this end, we identify cognitive and non-cognitive gains, cognitive and affective engagement, motivation to study, and three different barriers as critical factors in CS students’. We test these factors on 236 Norwegian CS students in order to find any potential gender differences. The findings indicate a gender difference for cognitive gains, affective engagement, motivation to study, and satisfaction with learning effectiveness. On the other hand, no difference was found for non-cognitive gains, cognitive engagement, personal values/teaching quality, and students’ intention to dropout from their studies. The study concludes with implications that will guide both research and practice towards a better understanding of both male and female CS students

An Examination of Middle School Students’ Attitudes Toward Science

For more than 40 years, researchers have been studying the persistent underrepresentation of women in science. Today, the gender gap has narrowed in some, but not all, disciplines of science. To better understand the impetus of this continuing problem, the attitudes of middle school students toward science were examined using a causal-comparative design based on biological sex across four attitude constructs: attitudes toward school science, desire to become a scientist, value of science to society, and perceptions of scientists. A sample of 450 sixth-, seventh-, and eighth-grade science students located in suburban, central New Jersey responded to Likert-type items on the My Attitudes Toward Science (MATS) survey during their regularly scheduled science class periods. Data analysis was performed through a multivariate analysis of variance. The findings indicated no statistically significant differences in middle school students’ attitudes toward school science, desire to become a scientist, value of science to society, and perceptions of scientists based on biological sex of the students. Implications for the findings are discussed

Computing degree apprenticeships: an opportunity to address gender imbalance in the IT sector?

This paper explores the potential for new work-based apprenticeship degrees to encourage more women into computing degrees and the IT sector. In the UK, women are currently under-represented on computing courses. Meanwhile the IT industry requires more computing graduates, in general, and specifically more highly skilled women to create appropriate products and systems. The UK has recently introduced apprenticeship computing degrees, where the apprentice is a work-based employee. In some models, apprentices spend 20% of their time on Higher Education studies and also gain credits through work-based learning; in others, apprentices spend blocks of time in Higher Education and the workplace. These degrees offer a new and innovative route to studying computing at university. Largely funded by employers, apprentices are salaried, and their fees are paid, paving the way for more people to study for a degree. The work context enables apprentices to keep their jobs (if relevant) or to move into IT roles and start a computing degree without necessarily having computing qualifications; the degrees have no upper age limit. Extending the work-based approach of US cooperative education and student work placement models, apprenticeship degrees have been introduced to increase skills levels through a close partnership between universities and employers. This is particularly important in IT, where the sector is expanding, and employers are looking for both good technical and personal skills. With this model, employers are collaboratively involved in the design of the degrees and apprentices graduate with extensive work experience.We posed the following research question: Are there differences in the paths into computing apprenticeship degrees between women and men? A survey was conducted with apprentices beginning a degree in Fall 2019: Cyber Security, Data Science, IT Management for Business, or Software Engineering/Development. Participants were asked about their routes into the apprenticeship and the IT sector. Apprentices at five universities in Scotland and one in Northern Ireland completed the survey, on paper or online (n=85; 23 female, 59 male).The results revealed a less severe gender imbalance than with comparative on-campus degrees (28% female), but this varied greatly across the subjects, from Data Science, where 55% of respondents identified as female and IT Management for Business (40% female), to Software Development (27% female) and Cyber Security (only 11% female). Apprentices were more likely to have started the degree at least a few years after leaving school and this was especially true for women. More female respondents had also been with their current employer for over five years. However, women were slightly more likely to have joined their employers in order to start the apprenticeship.This initial work identifies opportunities to recruit women onto computing degree apprenticeships, for example by targeting women who have started careers. It also highlights that there are challenges in recruiting women into certain subject areas, especially Cyber Security, but also Software Development. Exploring our respondents' motivations for choosing their subjects illuminates the gender balance challenge and indicates how degree apprenticeships can encourage more women into the IT sector

Early Introduction of Computer Science Education in Minority Youth: A New Representation of Tomorrow\u27s Engineers?

Computer Science (CS) has a large underrepresentation of females and racial minority (Hispanic and African American) populations in today’s education intuitions and workforce. Public health workers and companies have reviewed the consequences of this underrepresentation. Although a promise to incorporate more STEM education in schools the large gap is still prevalent. The Google Code Corps (GCC) is a partnership between The Boys & Girls Clubs of America (BGCA), AmeriCorps, and Google with a symbiotic goal to impact minorities and low-socioeconomic (SES) communities through education, mentoring, and capacity building. GCC project aims to empower BGC members by developing a successful and sustainable CS program. The completion of GCC year-one findings resulted in more ethnic minorities partaking CS classes and an overall increase in CS concepts. In summary, 44% of BGCSV participants were female and 70% were ethnic minorities. Students who partook in classes felt they could have a career in computer science. Furthermore, staff demonstrated a feeling that CS First was an easy and well-structured program. Multiple internal and external factors including allostatic load and a leaky pipeline contribute to a large underrepresentation of minorities in CS. Implementing CS education early and through multiple layers of the Social Ecological Model (SEM) shows promise for an increased interest. Programs like the GCC can create long-term improvements and set up student success through capacity building activities. However, proper mentorship and continuing assessments and motivating are necessary for overall program success and creating a sustainable impact on both minorities and the CS workforce

Using social cognitive career theory to understand why students choose to study computer science

The aim of this research is to use Social Cognitive Career Theory (SCCT) to identify and understand reasons why students choose to study Computer Science (CS) at university. SCCT focuses on students’ prior experience, social support, self-efficacy and outcome expectation. The research is part motivated by the desire to increase female participation rates in CS, particularly in the UK. Policymakers can use the factors that both females and males identify as influencing their choice of studying CS to enhance the experiences of all students prior to coming to university, but female students in particular. The study uses a semi-structured interview with 17 mixed gender subjects currently studying CS at three Scottish universities. The findings are that social support from family, teachers, friends and mentors is a particularly important factor in choosing to study CS, especially for female subjects. The career paths offered by a CS degree is another major factor, not just the potential jobs, but also the general value of a CS education and the potential to make useful contributions to society. School education appeared to have limited influence, though exposure to problem solving, programming, online self-learning and internships are positive influences. The stereotypical view of CS students as ‘geeks’ is outdated and unhelpful – it is more appropriate to see them as ‘analytical’ or ‘over-achievers’. Subjects make many suggestions for improving the CS education provided at school, especially to make it more attractive to females, including: make it compulsory, teach it earlier, include more programming and problem solving, and increase the visibility of female exemplars and role models

Relations between gender stereotyping and foreign language attainment:The mediating role of language learners’ anxiety and self‐efficacy

BackgroundGender stereotyping of academic domains has long been a major issue in education. However, previous research has mainly focused on male-dominated fields and women’s disadvantage in such fields. Little attention has been paid to the fields of study, such as foreign language learning, which are typically stereotyped as female domains.AimsThis study aimed to investigate whether relations between (1) learners’ gender stereotypes about English as a foreign language (EFL) learning and language attainment and (2) learner perceptions of teacher stereotypes of EFL learning and language attainment were mediated by anxiety and self-efficacy.SampleData were collected from 701 university students (Mage = 19.7 years, 49.4% male) learning EFL in three Turkish universities.MethodData were collected over three waves. Multi-group structural equation modelling approach was used to analyse the data.ResultsResults showed the relations between learners’ gender stereotypes about EFL learning, and language attainment were mediated by self-efficacy. Self-efficacy also mediated the relationship between learner perceptions of teacher stereotypes of EFL learning and language attainment, but only for women. Language anxiety was not a mediator between gender stereotypes and attainment in either model tested.ConclusionsFindings show that gender stereotypes about EFL learning might affect learners’ language attainment by altering their self-efficacy. Helping learners to maximise their self-efficacy will therefore be beneficial for their language attainment

Closing the gender gap in ICT higher education: exploring women’s motivations in pursuing ICT education

Rapid development of digital technologies has stemmed profound changes in the society, positioning the ICT sector as a key driver and contributor. This sector, including education, is however characterized by a gender gap, which is problematic in the light of the increasing demand for digital competence and the ability to move toward a sustainable egalitarian society. In this study, we argue for a need to explore the concept of ICT in higher education. This involves assessing the success of educational programs in attracting women and exploring the perceptions of female students regarding their academic environment. With a specific focus on Sweden, through a survey involving 82 respondents, we provide evidence on motivations and perceptions of women regarding leading choices on pursuing ICT higher education. We propose a holistic approach to studying gender representation and inclusion in ICT higher education, with a focus on women’s perceptions, experiences, and suggestions

Development and validation of the Value-Expectancy STEM Assessment Scale for students in higher education

Background: Science, technology, engineering, and math (STEM) jobs are expected to make up a significant portion of the U.S. workforce. Unfortunately, the trend in retaining students in STEM majors has been going down. If higher education institutions are going to retain more students in STEM majors, it will be important to understand who leaves STEM fields and why. More than 32% of women college students who declare a STEM major are likely to switch to non-STEM majors before they graduate, whereas only 25% of their male counterparts do so, and women may be as much as 1.5 times more likely than men to leave STEM fields. Thus, women represent a significant potential source for increasing STEM majors. Research suggests that values and expectations are powerful predictors of motivation and persistence in a wide variety of activities, tasks, and careers. This paper describes the development and validation of an instrument to measure student motivation, particularly that of women, leading to decisions to persist in or switch out of collegiate STEM programs. Results: The Value-Expectancy STEM Assessment Scale (VESAS), adapted from the Values, Interest, and Expectations Scale, or VIES, was validated with 356 women students from a Midwestern research university as part of a larger study on the reasons that women persist or leave STEM majors. A confirmatory factor analysis suggested a two-factor model, which reflected the components of Eccles et al.’s expectancy-value model. Cronbach’s alphas suggested that the VESAS subscales had high internal consistency. Statistically significant differences were found between STEM switchers and persisters on all of the VESAS subscales, thus lending additional support for the validity of the instrument. Conclusions: The VESAS appears to be a valid scale for measuring female college students’ value for and expectations regarding STEM majors. Suggestions are made for use of the VESAS in future studies to examine how motivations of women students enrolled in STEM programs change over time and to better understand when retention interventions might be needed and with whom