Search for: All records

Computing self-efficacy is an important factor in shaping students' motivation, performance, and persistence in computer science (CS) courses. Therefore, investigating computing self-efficacy may help to improve the persistence of students from historically underrepresented groups in computing. Previous research has shown that computing self-efficacy is positively correlated with prior computing experience, but negatively correlated with some demographic identities (e.g., identifying as a woman). However, existing research has not demonstrated these patterns on a large scale while controlling for confounding variables and institutional context. In addition, there is a need to study the experiences of students with multiple marginalized identities through the lens of intersectionality. Our goal is to investigate the relationship between students' computing self-efficacy and their prior experience in computing, demographic identities, and institutional policies. We conduct this investigation using a large, recent, and multi-institutional dataset with survey responses from 31,425 students. Our findings confirm that more computing experience positively predicts computing self-efficacy. However, identifying as Asian, Black, Native, Hispanic, non-binary, and/or a woman were statistically significantly associated with lower computing self-efficacy. The results of our work point to several future avenues for self-efficacy research in computing. 

Cybersecurity expertise continues to be relevant as a means to confront threats and maintain vital infrastructure in our increasingly digitized world. Public and private initiatives have prioritized building a robust and qualified cybersecurity workforce, requiring student buy-in. However, cybersecurity education typically remains siloed even within computer and information technology (CIT) curriculum. This paper's goal is to support endeavors and strategies of outreach to encourage interest in cybersecurity. To this end, we conducted a survey of 126 CIT students to investigate student perceptions of cybersecurity and its major crosscutting concepts (CCs). The survey also investigates the prevalence of preconceptions of cybersecurity that may encourage or dissuade participation of people from groups underrepresented in computing. Regardless of prior learning, we found that students perceive cybersecurity as a relatively important topic in CIT. We found student perspectives on conceptual foundations of cybersecurity were significantly different (p < .05) than when simply asked about "cybersecurity," indicating many students don't have an accurate internal construct of the field. Several previously studied preconceptions of cybersecurity were reported by participants, with one misconception - that cybersecurity "requires advanced math skills" - significantly more prevalent in women than men (p < .05). Based on our findings, we recommend promoting cybersecurity among post-secondary students by incorporating elements of cybersecurity into non-cybersecurity CIT courses, informed by pedagogical strategies previously used for other topics in responsible computing. 

Background : Affirmative action programs (AAPs) aim to increase the representation of people from historically underrepresented groups (HUGs) in the workforce, but can unintentionally signal that a person from a HUG was selected for their identity rather than their merit. We call this signal the diversity-hire narrative. Prior work has found that women hear the diversity-hire narrative during their computer science (CS) internships, but women and non-binary students' experiences surrounding the narrative are important to understand and have not been thoroughly explored. Objectives: We seek to understand the (1) sources and (2) impacts of this narrative, as well as (3) how students respond to it. Methods: We conducted and qualitatively analyzed 23 semi-structured interviews with undergraduate CS students in the gender minority (i.e., students who identify as women or non-binary). Results : Participants reported hearing the diversity-hire narrative from family and peers. They reported feeling self-doubt and a double standard where their success was not attributed to their intelligence, but their peers' success was. Participants responded to the diversity-hire narrative by (1) ignoring it, (2) attempting to prove themselves, (3) stating that their peers are jealous, (4) explaining that AAPs address inequity, and (5) explaining that everyone is held to a high standard. Implications: These results expand our understanding of the experiences that likely impact undergraduate CS students in the gender minority. This is important for broadening participation in computing because results indicate that students in the gender minority often encounter the diversity-hire narrative, which deprives them of recognition by invalidating their hard work. 

Computing is everywhere, and it's here to stay. Computing is crucial in many disciplines and influences every discipline. It’s unlikely we'll willingly return to a society unmediated by computing. How do our institutions proceed? This BoF asks, "Should computing be a requirement for all college and university students?" Some say yes, citing potential for improving equity-of-access, for expanding students' capabilities, for diversifying the people who understand and critique computing, and for increasing the diversity of computing participation. Some say no, citing the lack of equity-of-outcomes, the infeasibility of teaching all students equitably, and students' need for freedom in choosing what they study. Some say, "Let's consider the spectrum of possibilities... ." This session will discuss these possibilities, expressed and constrained by 2024's forces. Is computing's value saturated - or soon to be? Or is computing a meta-skill, whose practice in learning-to-learn amplifies individual efficacy along all paths? Is Computing1 too gate-kept to be as equitable a GenEd as Composition1? Or does requiring computing, in fact, help dismantle those gates? Can students adequately learn about core computing concepts via non-CS courses that use computing? What might required computing entail? We invite and welcome all with an interest in computing-as-degree-requirement, program-requirement, or GenEd offering. The session's seed materials will highlight evidence against the idea, for the idea, and across its vast, uncertain middle. Our BoF proposers include researchers and educators, both non-CS-requiring and CS-requiring, as well as non-CS-required and CS-required "educatees." Join us! 

Artificial intelligence (AI) and cybersecurity are in-demand skills, but little is known about what factors influence computer science (CS) undergraduate students' decisions on whether to specialize in AI or cybersecurity and how these factors may differ between populations. In this study, we interviewed undergraduate CS majors about their perceptions of AI and cybersecurity. Qualitative analyses of these interviews show that students have narrow beliefs about what kind of work AI and cybersecurity entail, the kinds of people who work in these fields, and the potential societal impact AI and cybersecurity may have. Specifically, students tended to believe that all work in AI requires math and training models, while cybersecurity consists of low-level programming; that innately smart people work in both fields; that working in AI comes with ethical concerns; and that cybersecurity skills are important in contemporary society. Some of these perceptions reinforce existing stereotypes about computing and may disproportionately affect the participation of students from groups historically underrepresented in computing. Our key contribution is identifying beliefs that students expressed about AI and cybersecurity that may affect their interest in pursuing the two fields and may, therefore, inform efforts to expand students' views of AI and cybersecurity. Expanding student perceptions of AI and cybersecurity may help correct misconceptions and challenge narrow definitions, which in turn can encourage participation in these fields from all students.