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

   Taheri, M and (January 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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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. Student Persistence Factors for Engineering and Computing Undergraduates

   Gholezadeh, Sona; Petrulis, Bob; Gatzke Edward P (June 2023, ASEE Annual Conference)

   The research and evaluation team of an S-STEM project at a large, research-intensive Southeastern public university conducted a cross-sectional survey as a first step to compare factors which may influence undergraduate student persistence in engineering and computing. All engineering and computing students were invited to participate in the survey, and 282 (10.4%) provided responses. The respondents included 15 high financial need students who were participating in the S-STEM program, of which 7 were first-year students and 8 were sophomores. The remaining 267 respondents were undergraduates ranging from first-year to seniors. Survey questions were adapted from previously developed instruments on self-efficacy, sense-of-belonging, identity, community involvement, and overall college experience. Additional questions related to stress levels, academic life, use and effectiveness of academic supports, and the impacts of COVID-19 on their college experiences. The team compared responses by level of academic progression, declared major, gender, and race/ethnicity. Student responses showed a variety of similarities and differences between subgroups. Overall, the students said that they often attended lectures (in-person or online) and came to class prepared. At the same time, students rated these activities as the least effective academic supports. On the other hand, the students rated working assigned or extra homework problems and studying for exams as their most effective activities. Consistently among the subgroups, the students said their community involvement and identity as developing engineers were relatively low while self-efficacy and team self-efficacy were seen as stronger personal skills. The students said they were highly stressed about their grades and academic success in general, and about finances and future careers. They reported feeling less stress about aspects such as living away from home and negotiating the university social scene. Students reported spending the most time preparing for class in their first year compared to students in later years. Female students (104 responses) reported higher levels of community involvement, engineering identity, and engagement in college life compared to male students (142 responses) while there was little gender-related difference in self-efficacy and sense of belonging. Levels of self-efficacy and team self-efficacy did not show large differences based on year in college. Interestingly, first-year students expressed the highest levels of engineering identity while senior students the lowest. Senior students reported the lowest community involvement, sense of belonging, and engineering identity compared to other students. Overall, students from different races self-reported the same levels of self-efficacy. Black/African American students reported the highest levels of community involvement, college life, and identity. There were no substantial differences in self-efficacy among the different engineering and computing majors. This study is a first step in analysis of the students’ input. In addition to surveying the students, the team also conducted interviews of the participating S-STEM students, and analysis of these interviews will provide greater depth to interpretation of the survey results. Overall, the research and evaluation team’s intention is to provide insight to the project’s leadership in how best to support the success of first-year engineering and computing students. https://peer.asee.org/student-persistence-factors-for-engineering-and-computing-undergraduates 

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