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1. Examining the Computing Identity of High-Achieving Underserved Computing Students on the Basis of Gender, Field, and Year in School

   Garcia, A.; Ross, M.; Hazari, Z.; Solis, T.; Weiss, M.; Christensen, K.; Georgiopoulos, M. (April 2018, The Collaborative Network for Engineering and Computing Diversity Conference (CoNECD))

   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. 

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2. A Structural Equation Model Analysis of Computing Identity Sub-Constructs and Student Academic Persistence

   https://doi.org/10.1109/FIE.2018.8658378  

   Taheri, Mohsen; Ross, Monique; Hazari, Zahra; Weiss, Mark; Georgiopoulos, Michael; Christensen, Ken; Solis, Tiana; Garcia, Atalie; Chari, Deepa (October 2018, IEEE Frontiers in Education Conference (FIE) 2018)

   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. 

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3. How Do Educational Experiences Predict Computing Identity?

   https://doi.org/10.1145/3470653  

   Lunn, Stephanie; Ross, Monique; Hazari, Zahra; Weiss, Mark Allen; Georgiopoulos, Michael; Christensen, Kenneth (June 2022, ACM Transactions on Computing Education)

   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. 

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4. How Do Educational Experiences Predict Computing Identity?

   Lunn, Stephanie; Ross, Monique; Hazari, Zahara; Weiss, Mark; Georgiopoulos, Michael; Christensen, Ken (June 2022, ACM transactions on computing education)

   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. 

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5. Exploring Computing Identity and Persistence Across Multiple Groups Using Structural Equation Modeling

   Taheri, M; Ross, M; Hazari, Z; Weiss, W; Georgiopoulos, M; Christensen, K; Solis, T; Chari, D; Taheri, Z (June 2019, American Society for Engineering Education (ASEE) Conference Proceedings)

   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. 

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