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

This dissertation explores the impact of computing identity sub-constructs on the academic persistence of computing students. This research provides models, quantified relationships, and insights to increase the number of graduates with the intention of pursuing a career in computing. Despite the growing significance of computer science and all the projected new jobs in computer science, many university and college programs suffer from low student persistence rates. One theoretical framework used to better understand persistence in other STEM disciplines is disciplinary identity. Disciplinary identity refers to how students see themselves with respect to a discipline. This study examines the effects of computing identity sub-constructs (performance/competence, recognition, interest, and sense of belonging) on the academic persistence of computing students. A quantitative analysis with three phases was performed for this study. First, confirmatory factor analysis (CFA) and structural equation model (SEM) analysis were performed to validate and explore the relationship between sub-constructs in the computing identity model. Second, a multigroup SEM was performed to estimate the impact of the identity sub-constructs on persistence for students with diverse demographics in this case by gender and level of education. Third, a time-series SEM were used to investigate the impact of identity development on computing persistence over time. The findings indicated that students\u27 academic persistence was directly influenced by their interest as the most significant factor. In addition, performance, competence, recognition, and sense of belonging contributed to students’ identity development and academic persistence. Results of the second analysis indicated identity sub-constructs contributed differently to academic persistence among freshman and senior students; however, no significant differences were found between male and female students. Ultimately, the last analysis with time-series data indicated that interest and competence/performance, as individual factors had the strongest direct impacts on persistence over time. Considering student identity in understanding academic persistence in computing programs may provide a meaningful lens of analysis for institutes and their curriculum and extracurricular planning methods. In addition, the development of students’ self-beliefs provides ways for increasing the number of graduates with increased likelihood of pursuing computing careers

Modeling and Validating Structural Relationship among Customer Data Privacy in E Commerce and Data Breaches.

This abstract provides an overview of a comprehensive study aimed at modeling and validating the structural relationships between customer data privacy practices in e-commerce platforms and the occurrence of data breaches. This research bridges the gap in understanding how the level of investment and adherence to data privacy measures in e-commerce businesses influences the likelihood and severity of data breaches.The study employs a mixed-methods approach, combining quantitative analysis of large-scale data sets related to e-commerce platforms and data breach incidents with qualitative analysis of privacy policies, regulatory frameworks, and industry best practices

Undergraduate STEM majors on and off the pre-med/health track: A STEM identity perspective

Despite the wealth of research exploring science, technology, engineering, and mathematics (STEM) identity and career goals in both formal and informal settings, existing literature does not consider STEM identity for undergraduate students pursuing health and medical careers through STEM pathways. We address this gap by examining the STEM identity of undergraduate STEM majors on pre-med/health tracks as it compares with that of other STEM majors, thus focusing on a population that is chronically understudied in STEM education research. We surveyed 440 undergraduate STEM students enrolled in entry- level STEM courses to assess their STEM identities and three identity precursors: interest, performance-competence, and recognition. Through regression analyses accounting for gender, major, and perceived home support around STEM, we found that pre-med/health students were more likely to have higher STEM identity and recognition scores than their peers; we did not detect a significant difference for performance-competence or interest in STEM. Although there is little tracking of pre-med/health students’ ultimate career attainment, the implications of our findings support a potential for sustaining pre-med/health students while simultaneously creating pathways to other STEM pursuits for the nearly 60% of those who do not enter medical school by offering participation in experiences that affirm their STEM identities