Expanding STEM Talent Through Upward Transfer: Factors Influencing Transfer in STEM Fields of Study from Two-Year to Four-Year Institutions

Two-year institutions are essential components of the nation's education system and increasingly recognized as critically important in established and emerging areas of science, technology, engineering, and mathematics (STEM). However, there is a limited body of research examining what influences student transfer from two-year colleges into STEM fields of study at four-year institutions. Drawing upon social cognitive career theory, the project will develop and refine a STEM transfer model that hypothesizes that STEM transfer is influenced by demographic factors, contextual factors, learning experiences in STEM, and motivational beliefs related to STEM learning and transfer. The four-year longitudinal mixed methods research project will investigate STEM transfer and will advance and test a model of postsecondary STEM pathways to the baccalaureate and careers in STEM or to alternative educational and occupational attainment in STEM. The research team will follow a cohort of 3,000 students beginning in STEM programs or courses required for STEM programs at two-year community and technical colleges in Wisconsin and study factors that facilitate or hinder their transfer into a STEM major at 4-year colleges and universities during the study period.

The research adopts an explanatory sequential mixed methods design in which the quantitative approach is dominant and is followed by a complementary qualitative approach. The quantitative phase will consist of collection and analysis of students' administrative records from participating institutions integrated with students' data from a new longitudinal survey on STEM transfer. To establish construct validity, the research team will perform exploratory factor analysis to identify the factor structure. This will be followed by a confirmatory factor analysis. Additional factor analyses will be ongoing as each wave of the survey data becomes available. Three waves of data collection will be conducted. Structural equation modeling (SEM) will be used to analyze the multivariate data and to test the theoretical framework. SEM defines latent and observed variables while testing the direct and indirect relationships among variables that are hypothesized. The interview and focus group sample will be purposively selected from survey participants. While specific selection criteria will depend on the analysis of the survey data, it is anticipated that a combination of intensity sampling, maximum variation sampling and/or homogenous sampling will be the most viable strategies to provide more depth and insight into the factors influencing STEM transfer as identified by quantitative findings. Deductively guided and inductively grounded data analyses will be utilized to discover common themes across interview and focus group qualitative data. The project will advance the knowledge base on STEM transfer and contribute to theory building in this important area of study.