Research Insights

As the U.S. invests in efforts to build its capacity to lead the world in the development of artificial intelligence and other areas of computer science, it faces a critical workforce bottleneck, a shortage of computer scientists to meet workforce demands in industry and academia, coupled with a lack of gender and racial diversity. One way to effectively expand and diversify the computer science workforce is to develop a pathway from community colleges to undergraduate and graduate degree programs. Community college transfer students in computer science are a particularly high-achieving and diverse group, and community colleges are a primary entry point into higher education for many Students of Color, women, first-generation college students, and others who hold a combination of these and other historically minoritized identities in higher education. Despite the talents and assets that transfer students bring to the computer science major, they also face unnecessary barriers at their universities, which constrain their opportunities to become leaders in their field. The goal of this project is to produce new knowledge that will address these barriers and guide efforts to transform university structures, policies, and practices to foster success among community college transfer students in computer science. This study will engage a convergent, multi-phase mixed methods design. Drawing on five years of longitudinal survey and interview data from computer science transfer students and other key university agents (e.g., university faculty, staff, administrators) across six campuses in the California State University system, the project aims to address the following overarching research questions: (1) What are the structures, policies, and practices that community college transfer students identify in shaping their degree trajectories in computer science? (2) From the perspective of key university agents (e.g., advising staff, faculty, administrators), what are the relevant structures, policies, and practices that shape community college transfer student degree trajectories and opportunities in computer science? The inquiry will be informed by social cognitive career theory (SCCT) and theories of administrative burden and street-level bureaucracy. The quantitative stream of this work will rely on descriptive and multivariate analysis of student surveys and registrar data. The qualitative stream of this research will use phenomenological methods, relying on student and university agent interview data to better understand the experienced phenomena (i.e., structures, policies, and practices that shape transfer student trajectories in computer science). This approach aligns with the research questions, which collectively focus on how participants with varying positionalities (e.g., student, staff, faculty) make meaning of the structures, policies, and practices that shape community college transfer student success and degree trajectories.

Funder: National Science Foundation 

Amount: $1,496,458 

PI: Jennifer Blaney, Louise McBee Institute of Higher Education