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The number of female students in computing fields remain low despite the millions of dollars spent on research for attracting more female students. In order to attract more female students to these male dominated fields, we first have to understand in which educational years we are losing female students. For the purpose of this study, we utilized the data from [title blinded for anonymity] an NSF funded study. Approximately, 1650 students from three large public universities in Florida participated in this survey. The survey contained 39 questions around identity, field of study, as well as fields they wanted to pursue during middle school, high school, and college. The responses gathered through the Qualtrics survey system were analyzed in R by the research team. The research questions that guided this study were: (1) To what extent are female students interested in computing related fields at middle school, the beginning of high school, and the beginning of college? (2) How have these occupational pursuits changed over time? Do they differ for gender? The results of the study indicated a majority of female students that were attracted to the computing fields during middle school remained in those fields during high school and college years. However, there was no significant flow from other majors to the computing fields observed during the different educational years. 

Despite increasing demands for skilled workers within the technological domain, there is still a deficit in the number of graduates in computing fields (computer science, information technology, and computer engineering). Understanding the factors that contribute to students’ motivation and persistence is critical to helping educators, administrators, and industry professionals better focus efforts to improve academic outcomes and job placement. This article examines how experiences contribute to a student’s computing identity, which we define by their interest, recognition, sense of belonging, and competence/performance beliefs. In particular, we consider groups underrepresented in these disciplines, women and minoritized racial/ethnic groups (Black/African American and Hispanic/Latinx). To delve into these relationships, a survey of more than 1,600 students in computing fields was conducted at three metropolitan public universities in Florida. Regression was used to elucidate which experiences predict computing identity and how social identification (i.e., as female, Black/African American, and/or Hispanic/Latinx) may interact with these experiences. Our results suggest that several types of experiences positively predict a student’s computing identity, such as mentoring others, having a job, or having friends in computing. Moreover, certain experiences have a different effect on computing identity for female and Hispanic/Latinx students. More specifically, receiving academic advice from teaching assistants was more positive for female students, receiving advice from industry professionals was more negative for Hispanic/Latinx students, and receiving help on classwork from students in their class was more positive for Hispanic/Latinx students. Other experiences, while having the same effect on computing identity across students, were experienced at significantly different rates by females, Black/African American students, and Hispanic/Latinx students. The findings highlight experiential ways in which computing programs can foster computing identity development, particularly for underrepresented and marginalized groups in computing. 

While starting a career may be challenging in any field, in computing the process tends to be aggravated by requirements of digital portfolios and technical interviews that necessitate coding extemporaneously. During the programming components, candidates are expected to offer a solution, while also giving consideration to the choice of algorithm and its time complexity. Although intended to assess the competency of the job applicants, the process is often more akin to a professional examination. Applicants are encouraged to prepare months, or even years before they begin looking for a position, an expectation that neglects to consider the obligations and responsibilities students already have. Moreover, this presumption can result in an unequal divide between those who have the time to commit, and those who are unable to do so. To examine students’ preparation for technical interviews and their own cultural experiences, we administered a survey at three metropolitan universities in Florida. Specifically, we utilized social cognitive career theory to examine: 1) Students’ preparation practices for technical interviews; 2) The impact of cultural experiences on preparation time; and 3) The relationship between preparation and job attainment. To address these topics, we used descriptive statistics, Shapiro-Wilk tests, Wilcoxon rank-sum tests, and Kruskal-Wallis tests. We also applied the community cultural wealth model to interpret our results. We observed that, in our sample, White students began preparing earlier for technical interviews, spent more time preparing, and received more job offers than non-White students. Females also spent more hours preparing on average, and received more job offers than students that did not identify as female. However, female, Black/African American, and Hispanic/Latinx students were more likely to have cultural experiences that would impact their availability to prepare, including non-computing related jobs, caring for a family member, or ongoing health issues. While we do consider the support mechanisms students may leverage to overcome obstacles, in general, these results emphasize the larger issues in existing hiring structures, and demonstrate the importance of not treating students as a monolith. The findings from this work are intended to inform educators about how to better prepare students to succeed on technical interviews, and to encourage industry to reform the process to make it more equitable. 

There is a substantial shortage of students pursuing graduate degrees in computing fields in the United States [1], and when examining participation rates of minoritized populations the disparity is even greater [2]. In order to attract more domestic students to graduate schools in computing it is important to understand what factors encourage or discourage them from participating. Literature suggests that students’ family, friends, school, and society play an important role in their educational paths and self-perceptions. Using social impact theory as the guiding lens, we explored support from family and friends, as well as social and program-related experiences, in this study to assess their impact on undergraduate students' reported interest in pursuing a graduate degree. The research questions that guided this study are 1) Which social and programmatic experiences have the greatest impact on students’ interest in pursuing a graduate degree in computing?; and 2) How does a student’s gender/racial/ethnic background and their participation in social and programmatic experiences impact students’ interest in pursuing graduate degrees? We answered these research questions using data from a survey conducted at three large public universities in Florida which targeted students in computing fields (n=740). Data was analyzed using Kruskal-Wallis and Wilcoxon rank sum tests, as well as logistic regression. The findings revealed that “presenting work to other students,” and “research experience” are two experiences which lead to an increase of students’ interest in pursuing a graduate degree in a computing field. This study also demonstrated the importance of having same gender friends and reported interest in pursuing a graduate degree in a computing field. These findings provide insight into which experiences may impact domestic students' interest in pursuing graduate programs in computing fields. The results of this study are beneficial for universities to consider what factors may encourage more students to pursue a future in academia or in the workforce after obtaining a graduate degree. 

Increasingly companies assess a computing candidate’s capabilities using technical interviews (TIs). Yet students struggle to code on demand, and there is already an insufficient amount of computing graduates to meet industry needs. Therefore, it is important to understand students’ perceptions of TIs, and other professional experiences (e.g., computing jobs). We surveyed 740 undergraduate computing students at three universities to examine their experiences with the hiring process, as well as the impact of professional and cultural experiences (e.g., familial support) on computing identity. We considered the interactions between these experiences and social identity for groups underrepresented in computing —women, Black/African American, and Hispanic/Latinx students. Among other findings, we observed that students that did not have positive experiences with TIs had a reduced computing identity, but that facing discrimination during technical interviews had the opposite effect. Social support may play a role. Having friends in computing bolsters computing identity for Hispanic/Latinx students, as does a supportive home environment for women. Also, freelance computing jobs increase computing identity for Black/African American students. Our findings are intended to raise awareness of the best way for educators to help diverse groups of students to succeed, and to inform them of the experiences that may influence students’ engagement, resilience, and computing identity development. 

The lack of diversity in computing fields in the United States is a known issue. Students enter the computing fields with the intention of graduating; however, a large number leave and do not persist after enrolling, due to discrimination and biases. This particularly concerns groups already underrepresented in computing fields, such as women, Black/African American students, and Hispanic/Latinx students. However, there are various experiences that can make students feel more included or excluded in the field. Some of these experiences include internships, undergraduate research, capstone courses, and projects, etc. Drawing on Astin’s I-E-O model and applying a random forest algorithm, we measure the feature importance of 14 distinct experiences on 1650 students’ feelings of inclusivity in the computing field. We observe that there are gender and racial differences in terms of the opinions of computing fields’ inclusivity. For example, tutoring experience, job offers, and job experience are considered some of the most important factors for female’s perceived inclusiveness of women. However, men perceived women’s inclusivity differently, based on the experiences they engaged in. We also looked at the perceived inclusiveness of computing fields for ethnically and racially underrepresented groups, such as Hispanic/Latinx students. Understanding the effect of different experiences on students of both genders with different races and ethnicities on the perceived inclusion could assist the computing community to provide more cohesive experiences that benefits all students and helps them to feel more welcome. 

The participation of female students in STEM majors, particularly computing and engineering, has remained low. In this study, our goal is to understand the most important factors influencing female students towards computing majors. We studied the impact of family and friends on four different racial groups including White, Black, Hispanic, and Asian students who chose computing majors (n=1650). The results of the study indicated friends had a positive significant role on White female students’ major decisions. 

Despite the projected growth of computer and information technology occupations, many computing students fail to graduate. Studying students’ self-beliefs is one way to understand persistence in a school setting. This paper explores how students' disciplinary identity subconstructs including competence/performance, recognition, interest, and sense of belonging contribute to academic persistence. A survey of 1,640 students as part of an NSF grant was conducted at three South Florida metropolitan public universities. A quantitative analysis was performed which included a structural equation model (SEM) and a multigroup SEM. The study examined different groups of students such as male versus female, and freshman versus senior students. Results suggest identity sub-constructs contribute differently to academic persistence among freshman and senior students; however, no significant differences were found between male and female students. The findings, such as the significance of particular aspects of computing identity on academic persistence, can have implications for educators and college administration. 

This Research Full Paper presents the effects of computing identity sub-constructs on the persistence of computer science students. Computer science (CS) is one of the fastest growing disciplines in the world and an emerging critical field for all students to obtain vital skills to be successful in the 21st century. Despite the growing importance of computer science, many university and college programs suffer from low student persistence rates. Disciplinary identity is a theoretical framework that refers to how students see themselves with respect to a discipline and is related to long-term membership in a disciplinary community. The theory has been effectively applied in Science, Technology, Engineering, and Mathematics (STEM) to understand students' success and persistence. This study examines the effects of performance/competence, recognition, interest and sense of belonging on the academic persistence of computer science students. A survey of approximately 1,640 computing students as part of a National Science Foundation (NSF) funded project was developed and administered at three metropolitan public institutions. Confirmatory Factor Analysis (CFA) was performed to validate the sub-constructs of identity for use in a computing identity model. Then, a structural equation model (SEM) was constructed as a snapshot of the structural relationships for describing and quantifying the impact of the identity subconstructs on persistence. The results indicated that our model for CS aligns with prior research on disciplinary identity but also adds the importance of sense of belonging. In addition, the findings indicate that students' academic persistence is directly influenced by their interest. A better understanding of these factors may leverage insight into students’ academic persistence in computer science/engineering programs as well as a meaningful lens of analysis for further curriculum and extracurricular activities. 

As technology increases in the global arena and the necessity for a more diverse group of individuals to fulfill engineering and computing roles increases, it is important to engage more students in computing majors and roles. Identity has proven to be an important lens through which researchers can better understand how to engage students in these fields. In particular, our framing for computing identity includes students’ self-perceptions about recognition, interest, and performance/competence. Using survey data, this study examines the computing identity of high achieving underserved students in computer science (CS), computer engineering (CE), and information technology (IT). For these students, we compare the constructs between men and women, computing fields, and freshmen and juniors/seniors. Based on preliminary data, results show that female participants had less of a computing identity than male students, specifically with respect to computing recognition and overall computing identity. Students in IT programs had less of an overall computing identity than students in CS and CE. Finally, freshmen were lower on their overall computing identities and specifically performance/competence beliefs and interest. These results suggest that even within computing programs, students differ in their computing identities. Furthermore, there are different constructs related to computing identity that vary for different subgroups of students. While these results are insightful, future work will compare the computing identities of high achieving underserved students with a larger population of computing students as well as strategies for building their computing identities.