Equal accessibility to computer science classes in high schools in California

As a female computer science educator, I've watched with growing alarm the drop in enrollment in our Computer Science programs from a ratio of 1:1 of males and females in 1983, to a current ratio of 5:1. The lack of interest of female students in Computer Science is still a very serious problem. As educators we should all be watching our own campus and addressing this problem. The panelists assembled from various institutions will address the issues of gender imbalance and relate their experiences in implementing solutions to counter this problem. Two of the panelist will discuss utilization of the World Wide Web addressing reasons for creating both Web sites. As long as this gender imbalance exists in our schools we need to continue our dialog to share and develop new ideas to encourage female participation in Computer Science Programs. The audience will be welcomed to participate in a larger group discussion.

We asked all of the liberal arts faculty who advise undergraduates on course selection at the 14 colleges in the Associated Colleges of the Midwest a series of questions regarding their perceptions of the personality traits of Computer Science (CS) students, topics they think are covered in CS classes, and their overall impressions of CS. Our goal was to assess empirically the hypotheses that (1) many non-CS faculty do not really know what computer science is, and (2) many non-CS faculty are unaware of the differences between CS and Information Technology (IT). We received over 250 survey responses, which revealed that, among non-CS faculty, only 9% disagree or are neutral that CS should even be part of a liberal arts curriculum, but 32% think CS students learn to administer computers and computer networks, while 34% believe that CS students are taught to use Microsoft products in the classroom. However, over 95% of non-CS faculty also recognize the importance of both programming and algorithms to the study of computer science. The overall data suggests that a majority of non-CS faculty in the Associated Colleges of the Midwest have a a basic understanding of CS, while the remainder have an overly broad definition of CS (i.e. they think that CS includes IT).

This study investigates gender differences in attitudes toward mathematics among first-year Computer Science (CS) students, focusing on three key dimensions: self-confidence, enjoyment, and value. Understanding students’ affective orientations toward mathematics is crucial, as these attitudes can influence their engagement, persistence, and performance in mathematics-related courses. The study aims to determine whether male and female students differ significantly in their levels of self-confidence, the value they place on mathematics, and the degree of enjoyment they derive from the subject. A total of 114 first-year CS students participated in the study and completed a structured questionnaire designed to measure the three attitude dimensions. The instrument’s reliability was confirmed through internal consistency analysis, while the Mann–Whitney U test was employed to assess gender differences in the responses. The findings revealed no statistically significant gender differences in self-confidence and enjoyment, suggesting that male and female students hold similar levels of belief in their mathematical abilities and experience comparable levels of positive affect toward the subject. However, the analysis identified a small but significant difference in perceived value, with female students reporting a stronger recognition of mathematics as valuable in their academic and professional pursuits than their male counterparts. These results suggest that while self-confidence and enjoyment in mathematics appear unaffected by gender among CS students, female students may place greater importance on the role of mathematics in their studies and future careers. The study contributes to the growing body of literature on gender and mathematics attitudes, highlighting the need for educators to acknowledge and leverage these perceptions to foster equitable and supportive learning environments.

The substantial decline in female enrollment in computer science programs has been a cause of concern, especially as the application of computer technology to an ever-wider range of human endeavor expands. While many studies have examined the attitudes and perceptions of female computer science students, little attention has been paid to studying empirically how classroom interventions-such as curricular choices and pedagogical approaches-may result in disparate impacts in the learning outcomes of male and female students. This study examines recent research articles in leading journals and conference proceedings of computer science education to analyze the gender composition of the subject pool, the extent to which cognitive learning results are disaggregated by gender, and whether there are gender differences in outcomes. This study found that about one-third of studies indicated the gender composition of the subjects, and about one-third of those research subjects were female. About ten percent of papers disaggregated research findings by gender; of those, 30% found differences between male and female subjects. No studies recommended gender disaggregation of data in future work. The lack of data for learning outcomes by gender may be one of the contributors to the paucity of female computer science students; it is possible that interventions found to be more (or less) effective would show different outcomes if the data were considered in light of the gender of the participants. Thus, further research into potential gender differences in the effectiveness of computer science instructional tools is recommended.

This research shows an audience of fellow computer science teachers that there is benefit in testing college student's scientific reasoning skills and that the students increase their logical thinking skills in computer science classes when they are presented with real world problems, engaged in group activities, and given hands-on experiments.Students' scientific reasoning skills from several different computer science courses are analyzed and tested before and after taking the computer science course to measure their improvement in logical thinking. The higher order thinking skills test results are compared, and the overall class and individual student improvement between the classes that use different teaching strategies are analyzed. Also, the test results are compared with students' ability to perform adequately in a computer science course. This information is valuable to advisors when placing students in computer science courses.In the assessments of students' entering knowledge and evaluations of students' thinking improvement, the students' individual higher order thinking skills as well as their overall level of cognitive development are analyzed. Through the analysis of their individual skills and level of thinking, one can expand conclusions about the students' and teacher's performance over time.

This Research to Practice Full Paper discusses an approach to motivating graduate computer science and electrical engineering students in the study of quantum computing. The U.S. Congress and other governmental and industrial organizations have recognized that teaching Quantum Computing in university-level Computer Science and Electrical Engineering programs is strategically important for workforce development along with technology development. Success in this endeavor requires generating genuine interest in the topic and motivating potential students. Quantum Computing requires an understanding of relatively difficult related subjects including physics, math and computer science. Many computer science and electrical engineering students shy away from quantum computing because of its complexity. This paper discusses our success with generating interest in quantum computing among graduate students and motivating them through exploring, in related courses, some aspects of quantum computing that have the potential to generate discontinuities. The approach is also examined in terms of the Scientific Learning Cycle as discussed by Wankat & Oreovicz. Opportunities and challenges of adding Quantum Computing to Computer Science and Electrical Engineering programs were studied through a student small group project in a cybersecurity course. The work built on extensive research into the effectiveness of small group projects and the role of “play” in learning. Our small group project on quantum computing was introduced three years ago into a cybersecurity course which is required for all students in our university's Masters in Computer Science and Masters in Electrical Engineering programs. The basic goals of the project are to teach students some basics of quantum computing by allowing them to “play with it” and to alert students to the fact that quantum computing is a rapidly developing new field that they need to follow during at least the next decade. The small group project helped students to explore the potential of quantum computing to substantially undermine current Public Key Cryptography and, at the same time provide a new approach to encryption that is even more secure than Public Key Cryptography. A qualitative analysis of discussions and assigned tasks suggests that this strategy succeeded in generating significant interest in quantum computing among students. They became motivated and immersed in a difficult subject despite the requirement for investment of significant time and effort to understand a complex combination of physics, math and computer science.

Despite great effort in research and teaching as well as in raising women’s quotas in the public sector and in enterprises, a gender gap in computer science can still be observed. The reasons are manifold, including the lack of interest of girls because of existing stereotypes of male nerds, misconceptions in the field of computer science, and concrete differences in students’ self-concept and performance. Girls do not choose schools or studies in the field of computer science because working on computers or coding is unattractive to them. Research shows poorer performance, missing interest, and lower self-concept for girls in secondary computing education as well as a high dropout rate of female students in computer science courses at the bachelor’s level. Software development exams contribute to those high dropout rates, and women often choose a different subject or even stop their university education altogether. This leads to fewer female employees in the field of computer science, and this situation calls for special measures at several levels. The current paper provides an overview of the initiatives of our university that aim to address several aspects of the gender gap. The programs offered aim to (1) increase interest in computer science and recruit (highly) gifted girls for our talent programs, (2) recruit and support female bachelor’s and master’s students in computer science, and (3) redesign programming courses and teaching materials to reduce the gender gap in performance and support, especially for female students. This study also describes a cyber tutoring program in which highly gifted girls between 13 and 16 years collaborate with and are supervised by female role models in higher positions in STEM. The evaluation results gained in the first year of this case study are promising and suggest that the extension and further development of the program would be advantageous.

Most studies of gender and computer science have been conducted (out of necessity) in gender-imbalanced environments. The findings often point to significant gender differences, leading the researchers to recommend strategies to meet these differences. One such recommendation is to adopt a female-friendly, contextual approach to curriculum development.1 In contrast, based on our recent and ongoing studies of undergraduate computer science (CS) students at Carnegie Mellon University, we hypothesize that in a more balanced environment, gender differences tend to dissolve. That is, the spectrum of interests, motivation, and personality types of men and of women becomes more alike than different. This leads us to be considerably more pragmatic in our recommendations for effective and positive change. Indeed, we believe that recommendations for curricular changes based on presumed gender differences can be misguided and may help reinforce, even perpetuate, stereotypes. Here, we describe some of the changes in the culture of computing as our undergraduate CS environment has become more balanced in three critical domains: gender, the mix of students and breadth of their interests, and the professional experiences afforded all students. Brief Background for the Evolving Culture In 1995, just 7percent (7 out of 96) of the entering freshmen CS majors at Carnegie Mellon were women. Since 1999, the percentage has increased nearly fivefold (on average, 45 out of 132), challenging trends across the country.2 Two major factors have contributed to the dramatic increase of women in CS at Carnegie Mellon: an outreach program for high school CS teachers that combined technical training with discussions of gender-gap issues and a broadened admissions policy (emphasizing diverse interests—along with high [End Page 110] achievement in mathematics and science—and de-emphasizing prior programming experience). To meet the needs of students with varying backgrounds, multiple entry routes were built into the first-year programming sequence.3 The subsequent creation of the proactive student organization Women@SCS has been catalytic in building an environment in which the new student body can flourish.4 Women@SCS explicitly provides crucial educational and professional experiences generally taken for granted by the majority in the community but typically unavailable for the minority participants.5 Many of these experiences are casual and often happen in social settings. For example, in an undergraduate CS program, male students often have the opportunity to discuss homework with roommates, with friends late at night, or over meals. Course and job information and recommendations are passed down from upperclassmen, from fraternity files, or from friends. Women students, being in the minority, do not have access to—in fact are often excluded from—these implicit and important advantages. As one proceeds into the professional world, similar phenomena occur. These key actions, and implications for other venues, are discussed further at the end of this paper. Our recent study, based on a set of interviews with seniors in the class of 2002, may be viewed to a limited degree as a follow-up to the intensive longitudinal studies of CS students at Carnegie Mellon carried out by Jane Margolis and Allan Fisher between 1995 and 1999.6 Their studies, funded by the Sloan Foundation and discussed in Unlocking the Clubhouse, were undertaken to help understand differences in male and female students' engagement (attachment, persistence, and detachment) with computer science, with a special focus on the gender imbalance in the field.7 A major goal was to devise and effect changes in recruitment, curriculum, pedagogy, and culture to encourage the broadest possible participation in the computing enterprise. Unlocking the Clubhouse paints a bleak picture for women in the undergraduate computer science program in the 1990s, one that still resonates with many CS programs across the nation. Margolis and Fisher note that for the most part, "women who were enthusiastic about computing find their confidence and interest extinguished in the college years."8 Consequently, many of the (few) women students who entered the...

Literature Review It is projected that from 2008 to 2016 there will be a 29% increase in workforce demands for computer system analysts, a 37% increase in demand for jobs for database administrators, and a 38% increase in the availability of jobs for software engineers (U.S. Department of Labor, 2005). Despite increasing demands, women and minorities remain underrepresented in computing fields. This has become a cause for significant concern echoed by a study of corporate executives (Delos, 2008) that found that the lack of minorities and women in computing professions is causing a talent deficit. The executives surveyed blamed the pre-college school system for contributing to the low representation of women and minorities in science and technology fields by not exposing learners to computing through course offerings and/or career counseling. Furthermore, Young (2004) reported that our perception of student computer skills may be inflated. Young's charge was echoed by Wallace and Clariana (2005) who found that incoming college students lack the necessary computer knowledge, skills, and abilities to pursue undergraduate degree programs that are dependent on strong computing skills. The National Science Foundation (NSF) examined the population of students who earned computing and/or technology degrees in 2005. According to the NSF (Chute, 2009), only 25% of the 2005 graduates nationwide were women while 75% were men. When race was considered, only 10% of the 2005 graduates were Black. Further, the enrollment of underrepresented groups in CS and IS programs continues to decline at a significant rate (Clinging, 2006). Clinging (2006) explains that this is influenced by a bias where low expectations foster diminished confidence and reduced success for women and minorities considering and/or attempting to study computing. Compounding the problem is the lack of technology professionals acting as role models and limited exposure to computing professions. Chute (2009) explained that female and minority students who have not been exposed to family members who are successful in technology-related fields are unlikely to be scheduled for math or computer science classes in high school. This was echoed at a 2005 conference held by the NSF (National Science Foundation [NSF], 2005) that reported that many current science, technology, engineering, and math (STEM) professionals had family connections or other points of contact in STEM fields that helped to influence and support their decision to select and persist in STEM studies. The result is that underrepresented minority learners who lack family connections and other points of contact are at a disadvantage due to the lack of role models and support. The digital divide remains a significant concern in the United States, with race/ ethnicity, income level, and education contributing to inequalities with the use of computers and reliable and expedient access to the internet (Morgan & VanLegen, 2005). Sax, Ceja, and Teranishi (2001) conducted a nationwide survey of college freshmen and found that level of technological preparedness varied significantly by race, class, and academic background. They explained that these technological disparities are a hindrance to students' academic success. Further, a 2007 study of 748 freshmen students at two public HBCUs, (Buzzetto-More & Sweat-Guy, 2007) found that while the number of students having studied computers had grown it was still significantly lower than what had been reported in the studies conducted at majority serving institutions. Another problem is that when female and minority students arrive on college campuses they find a lack of women and minority faculty in STEM areas. Between 2002 and 2007, the number of underrepresented faculty in the top 100 departments for science and engineering increased by only 0.5 percent rising to 5 percent (Nealy, 2007). Nealy explains that Underrepresented minorities are projected to constitute almost 32 percent of the American population by 2020; therefore, proactive steps should be taken now in order to insure that the proportionate inclusion of such a large part of the population in science and engineering, throughout all levels of academia, (Nealy, 2007, p. …

In the context of higher education strongly transforming itself under the impact of technology, Artificial Intelligence (AI) has become an important support tool in the learning process, especially for Computer Science (CS) students. Integrating a structured literature review and conceptual analysis, this paper evaluates the role of AI as a self-learning assistant, focusing on outstanding benefits such as personalized learning, source code debugging, and explaining complex algorithms, as well as challenges related to academic integrity, ethics, and independent thinking skills of students. Through analysis, the paper proposes a comprehensive recommendation framework, including: (1) an in-depth analysis of the five most effective AI tools; (2) smart strategies for AI-use through Prompt Engineering; (3) new pedagogical approaches for instructors; and (4) support policies from institutions. The results indicate that although AI cannot substitute human instructors completely, it can act as a powerful lever to enhance self-learning capabilities. When applied appropriately, it contributes to elevating the quality of Computer Science education in universities. Keywords: AI-assisted learning, Artificial Intelligence, Computer Science students, higher education, self-learning assistant.

With the fast-growing sector of information technology in digitizing societies, the attraction and education of qualified recruits in computer science becomes a key task of tertiary education. Considering the high dropout rates and the continuing gender gap in computer science, the current study builds on the “leaky pipeline” phenomenon of women in STEM (science, technology, engineering, and mathematics) by investigating belonging uncertainty in computer science as a predictor of students’ dropout intentions. In a study with first-semester computer science students (N = 217) at two time points, we tested the hypotheses that female students experience a greater belonging uncertainty than male students and that this belonging uncertainty is predictive of students’ dropout intentions. Furthermore, we explored whether belonging uncertainty is a more relevant predictor of female than male students’ intentions to drop out of computer science. In line with our predictions, our results show that female students experienced greater uncertainty about their belonging within the domain of computer science than male students and that belonging uncertainty significantly predicted students’ dropout intentions above and beyond the pertinent predictors academic self-efficacy, expectancy of success, perceived future utility value of the subject, and previous academic performance. Belonging uncertainty, however, was a relevant predictor of both female and male computer science students’ dropout intentions.

Encountering failure while cultivating computational literacy is inevitable, as debugging is a normal and necessary part of any programmer's workflow. Unfortunately, internalization of this failure is one discouraging factor in many students' choice not to pursue computer science. In this proposal, I outline my dissertation research on constructive mindsets for overcoming failure in introductory programming contexts. This work is motivated by an overarching interest in broadening participation in computing -- and, in particular, attracting and retaining more female computer science students. My doctoral research examines the differences in how technical students and non-technical students approach learning to code, with the goal of generating best practices for other educators.

This case study introduces the STARS (Supporting Talented African American Undergraduates for Retention and Success) project, designed to foster the retention and success of academically talented African American computer science students from low-income backgrounds at Historically Black Colleges and Universities (HBCUs) in the U.S. The STARS program employs a holistic approach, integrating four primary pillars of support: academic, social, career, and financial. Specific support provided includes near-peer mentoring, technical skill development seminars, undergraduate research, and high school outreach activities. To explore the program’s effectiveness and areas of improvement, a mixed-method evaluation study was conducted, collecting data through surveys, observations, individual interviews, and focus group interviews. The findings revealed that the STARS program contributed to high levels of retention among its scholars, and the mentoring program provided valuable networking opportunities. The study suggests that the program’s comprehensive approach, tailored to scholars’ needs, and combined with a culturally affirming learning environment, facilitates the retention and success of talented African American students in computer science.

There has been an increasing tendency and an interest to make computer science (CS) a core subject in the K-12 curriculum, however in many countries there is a CS teacher shortage in high schools. In order to define the possible reasons for CS teacher shortage, we investigated the factors that influence CS students’ career choices and their preferences about teaching. We also studied the requirements students view as important for their career. Semi-structured interviews were conducted with 18 CS bachelor and master students from four different universities in the Netherlands. The results show that the most important factors influencing the career choice of CS students are organization related expectations such as the characteristics of the organization (scale, reputation etc.), the field of expertise and salary expectations. Regarding CS students career plans about becoming a teacher, a large part (almost 75%) of the students stated that they definitely do not think of teaching or teaching is not a priority career goal. The most cited demotivating factors for following a teaching career are the nature of the teaching job and low salaries. Perceived required skills for good CS teachers are frequently defined as pedagogical skills and social skills.

Different points of view on the nature and content of the assertiveness are followed in this paper. The main purpose is to study the assertive profile of Bulgarian students in computer science and computer engineering by analyzing the components of assertiveness. Research was performed using testing methods. It was found that the level of expressivity of this personal quality among subjects were above-average level.