This study describes our current effort to expand our previous research to a national scale, exploring the implications of students' employability and salary between Bachelor of Arts (BA) and Bachelor of Sciences (BS) in Computer Science (CS) degrees. The literature on broadening participation has identified numerous barriers, but these challenges frequently burden students instead of addressing the underlying systemic issues within the curriculum. Previous research has identified bottleneck courses like calculus and physics as barriers to persistence in CS. Reimagining the curriculum and introducing alternative pathways, such as BA in CS, can eliminate bottlenecks and enhance access and retention without compromising essential skills in computing. To understand the implications of the BA pathway on employability and salary, we conducted a study at a large minority-serving institution (MSI) with a CS department serving around 2,000 students. Our research revealed that the BA degree offers comparable employment opportunities to the BS. Students choose BA due to broader career aspirations, a faster route to graduation, and view math courses as a significant barrier. Despite earning potential being important, we discovered salary differences between the two degrees, emphasizing the need for clear communication to help diverse students make informed decisions about their degree paths in CS. Given the findings from a single MSI, we recognize the importance of expanding this project nationally. This lightning talk will discuss background context, lessons learned, and potential collaborations for broader implementation.

This paper reviews the application of Schlossberg's transition theory in understanding the learning experiences of women in computing. Computing education communities have been consistently exploring approaches and strategies to increase the participation of underrepresented groups. Even though efforts are being made, it remains challenging to address the shortage of highly skilled computing professionals, and gender disparities still persist. A primary goal in computing education is to attract and engage with this historically minoritized population to retain them in the field for long-term contributions. In this pursuit, we propose reviewing Schlossberg's transition theory in the context of women in computing education to understand how to improve their learning experiences and improve their long-term engagement. Transition theory examines how individuals identify with and adapt to a changing situation in their personal and professional lives. In this study, we focus on non-computing women, those who have earned bachelor's degrees in non-computing fields but wish to change their career directions to computing after completing their undergraduate education. We argue that non-computing women have deferred interests in computing, so they leverage these learning experiences to facilitate their computing career transition. It is important to investigate non-computing women's learning experiences to gain a comprehensive understanding of how they navigate the transition process. Schlossberg's transition theory, originally developed for adult education and career counseling, provides a framework to guide our inquiry into women's interpretations of computing career transitions and for determining which resources are best suited to support them during the process. This paper seeks to synthesize relevant literature on Schlossberg's transition theory in engineering and computing education, focusing on the underrepresentation of women in computing. It explores broadening the application of Schlossberg's transition theory by applying it to the study of non-computing women to inquire into how it can help disrupt gender disparities in computing education. Our discussion of Schlossberg's transition theory also demonstrates how this theory is appropriate to study the non-computing women's career transition in computing and outlines future studies that can further the discoveries in engineering and computing education research.

The rapid growth of the computing industry requires a diverse and highly qualified workforce. The Computer Science Education Research (CSER) community has been working towards increasing diversity in computing, but there are still obstacles to overcome. The shortage of skilled computing professionals and gender disparities remain major challenges. It is crucial to attract and involve more women in computing careers to tackle this problem. However, early exposure to computing is critical for inspiring career aspirations, and many women miss out on this opportunity due to a lack of earlier exposure. In addition, there is a group of post-baccalaureate women who completed their undergraduate degrees in non-computing fields but aspired to transition into computing later in their career trajectories. I define this group as non-computing women, and the potential of engaging them as one of the solutions to the underrepresentation of women in computing should be further explored.

Technology innovation requires a set of diverse employees with computing skills. Yet, it remains a challenge for the global digital labor market to obtain an equitable representation of women. This is particularly true for women who enter the computing workforce after obtaining an initial undergraduate degree in a non-computing field. To resolve discrepancies, it is important to learn more about the factors influencing career trajectories and the possible alternative pathways that may encourage participation in the field. We define alternative pathways as any post-baccalaureate program or training that meets the needs of bachelor's degree-holding women with computing aspirations. This research paper, guided by Schlossberg's Transition Theory, conducted a content analysis on publicly available job profiles to characterize the types and features of alternative pathways commonly chosen by women in the United States (U.S.) to aid in understanding their transitions into a computing career. Findings from this study provide guidance and suggestions to women who are interested in transitioning to computing later in their career paths. It further outlines potential avenues with actionable recommendations for the computing education community to attract and retain women in the computing workforce in an effort to build an inclusive ecosystem.

Despite the projection of an increase in the number of jobs in the computer science (CS) field by 13% from 2020 to 2030 in the United States (as reported by the Bureau of Labor Statistics), the representation of women, especially women of color, in the field remains low. Lack of representation for women in computer science negatively impacts the growth of this demographic as it becomes harder for prospective individuals to envision themselves in the field when they do not see others like them already succeeding in CS. Studies have found that the retention of women in the field is stronger when the representation of women is evident in their environment, however, it is hard to come by considering the low population of women computer scientists. While new prospects may find fewer women in their CS departments in their college experience, or at their workplaces, there is a plethora of social media personalities and communities for them to engage in and find like-minded individuals.This full research paper investigates the experiences of women, or lack thereof, in CS communities centered around social media and how it contributes to their sense of belonging in the CS field at large. It is evident that there is limited scope in the existing literature that studies the impact social media participation has on CS women. This literature review distinguishes the narrow scope of literature focused on women’s experiences with open-source software communities in CS from women’s experiences with more generic widespread platforms such as Twitter, or Instagram. It argues for the expansion of knowledge for the effects of CS women’s participation on such platforms and provides insight into approaches, such as photovoice, that may be utilized to study this space. The outcomes of this review reveal the potential of utilizing online platforms in retaining women in the CS workforce effectively. Considering the current status of many organizations that have switched from in-person to remote engagement due to COVID, this review contributes to the analysis of the effective use of technology and its impact at a critical time.

Background and Context: Women remain minoritized in the global digital labor market [4], which is problematic since technology innovation requires a diverse set of employees with computing skills [6]. Existing studies have primarily focused on examining students at the K-12 and/or post-secondary levels [1, 2, 3], but less is known about women who are in the workforce and choose to enter a computing program or who transition into a computing role after obtaining an initial undergraduate degree(s) in a non-computing field. It is critical to learn more about the unique trajectories taken by those with non-traditional backgrounds to encourage the participation and retention of additional women in computing. Objectives: We conducted this pilot study to characterize the types and features of alternative pathways commonly chosen by women in the United States. The framework of Super’s Life Span and Life Space [5] guided our inquiry as we considered the correlation between life spaces for women and their career transitions into computing from other fields. This theory addresses different career development paths as a consequence of career development at distinct stages through progressive efforts in pursuing career growth [5]. It considers factors which may influence career development, such as social learning experiences, personality development, and one’s values, needs, and abilities. We use this theory to explore women’s life roles and the potential impact on career aspirations. Method: Data collection involved leveraging publicly available background information from profiles shared on a professional networking website. Specifically, we examined the profiles of women who entered computing later in their educational and/or career paths and who are currently working in computing-related positions. To characterize their trajectories, we conducted a content analysis, with a focus on their education, computing-related job information, and organizational affiliations. Findings: The exact alternative pathway programs selected by women from the targeted population varied on a case-by-case basis. We observed that women may obtain additional degrees in computing from higher education institutions, although they may also hone their skills through coding bootcamps and via self-learning through online resources. In particular, women switchers often have a background in mathematics, statistics, and electronic engineering. Moreover, we discovered that the majority of women, despite the field of their undergraduate majors, experienced exposure to computing through serving as research assistants. Implications: Exploring the backgrounds of these women, who may enter the field through alternative pathways, furthers our understanding of potential avenues to attract and retain an untapped talent pool. By examining different pathways, we seek to provide insight into ways to better support these women’s transitions and to find additional ways to encourage more women to join the profession. We recommend offering increased flexibility in coursework for learners and increased opportunities to gain exposure through undergraduate research. The results could not only be of interest to program administrators but could also offer suggestions for computing educators looking to make their lessons more inclusive.

This research paper serves as a benchmarking study to investigate the types and availability of resources available to postdoctoral scholars on university websites. Postdoctoral education in engineering and computer science disciplines is a forgotten stage of the academic pipeline, with very few scholars investigating the learning and development that occurs through the transient postdoctoral years. The few studies that have been done report postdocs feeling “forgotten” and on a “postdoctoral treadmill,” often without formal mentorship or guidance in developing the skills required to land academic careers. While most postdoctoral scholars do have supervisors to whom they report, most literature indicates that postdocs in engineering and computer science are still lacking mentorship in the peripheral skillsets essential for career success, and these effects are amplified for women and postdocs of color. Given a lack of interpersonal mentorship, it is plausible that postdocs turn to institutional resources for guidance and directions for professional development. To date, literature has not benchmarked the type or extent of resources available that are aimed at postdoctoral scholars. To this end, the purpose of this paper is to characterize university webpages using content analysis methods in order to understand the presence or absence of various types of support for postdocs at universities.

This research full paper describes how web scraping and natural language processing can be utilized to answer complex questions in computer science education. In this work, we apply connectivism as the theoretical framework, and demonstrate how web scraping can be useful for extrapolating large amounts of data from publicly available web pages to pool data from a wider array of sources and to further knowledge in the field. In addition, we discuss how natural language processing can be used to reliably obtain salient information from textual data, and how it can complement qualitative analysis. To illustrate these techniques in practice, we provide a specific application in which we examine the current trends in the job market for computer science students. The information gathered in this example provides additional areas for educational consideration, such as offering students Python programming language and machine learning. Also, the job postings delineate a clear need for applicants to exhibit programming and testing skills. Although programming may be taught already, testing is widely considered a knowledge deficiency, which suggests that educators should consider placing an increased emphasis on this area to ensure their students are adequately prepared for their career endeavors, and able to transfer the knowledge taught to critically assess and debug their own programs.

This work-in-progress (WIP) paper in the research track explored the muddiest point and self-efficacy for students in introductory computer science courses, starting with one course at a southern public institution. With the increasing demand in computing-related careers, the increased enrollments in undergraduate computer science courses are facing challenges to ensure the average passing rate. In this work, we applied the muddiest point to capture student's perceptions of concepts of difficulty and used self-efficacy to better contextualize students' perfections of self-efficacy in relation to concepts of difficulty. In this paper we present the results of one section of one introductory computing course, that revealed the perceived difficult topics as well as changes in self-efficacy throughout the semester. Furthermore, a positive correlation was found between self-efficacy and performance.