Background: Although a long line of research has been devoted to transfer pathways in general, there remains limited work on the capacity for community colleges to cultivate STEM baccalaureate transfer. In particular, both quantitative and qualitative evidence is extremely sparse on how STEM-aspiring students beginning at community colleges experience supports and barriers on their journey to pursue a STEM baccalaureate.
Purpose: This mixed-methods study addresses the question: What salient factors are associated with beginning community college STEM students’ decisions to transfer into baccalaureate STEM programs, and how do students describe the supports and barriers they experienced specifically pertaining to these factors?
Research Design: Guided by the STEM Transfer model, we carried out this research using an explanatory sequential mixed-methods design. We incorporated survey, administrative, and interview data from three large two-year institutions in a Midwestern state. We applied Artificial Neural Network (ANN) techniques to identify factors associated with beginning community college STEM students’ decisions to transfer into baccalaureate STEM programs. Based on the factors that emerged from ANN, we analyzed the interview data to give meaning to the identified factors using students’ rich descriptions of their experiences.
Findings: Results from the ANN revealed that students’ initial attitudes toward science was the most salient factor related to transfer in STEM. Following that, GPA, students’ initial attitudes toward math, transfer capital, being employed full time, major declaration, science preparation in high school, income levels above middle level, and transfer efficacy also turned out to be important variables shaping students’ transfer in STEM. Qualitative results further illustrated how the factors from the ANN exerted their impact.
Conclusions: This mixed-methods research illuminated significant factors shaping the road to becoming a scientist, as well as how those factors manifested their influences within the contexts of students’ educational journeys. Through this approach, we were able to establish the significance of influential factors without presuming directionality and leverage the interview data to disentangle how these factors functioned independently and together in sophisticated and nuanced ways. Our study brings forth a deeper understanding of community college students’ STEM pathways, including the many plot twists and processes involved to overcome challenges and maintain progress.