A Review of Retention Models for STEM Majors and Their Alignment to Community Colleges
Keywords: higher education, STEM education, community college, retention, predictive models
AbstractDuring the last decade, there have been numerous reports detailing the importance of increasing science, technology, engineering, and math (STEM) majors in the United States. Simultaneously, an increasing number of studies are being developed to predict a student’s success and completion of a STEM degree, recognizing that retention is a significant issue for STEM majors. A majority of the studies focus on traditional college students that attend college directly after high school, which is no longer the model of the majority of college students. A growing number of students delay entry into college and do not enter through traditional routes. One of the growing entry points for STEM students is the community college or two-year institution. These institutions have grown in popularity due to tuition increases and lack of preparedness for traditional selective universities. As the need for more STEM majors and a diverse workforce increases, more research should be directed towards this growing pool of students. Retention models should investigate unique retention causation factors more thoroughly to address these STEM students and this pipeline. This research provides a systematic review of the literature on retention models for STEM education and provides a discussion of future opportunities to align predictive models with community colleges.
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