Exploring the Relationship Between High School Mathematics and Bioscience, Standardized Testing and College Performance in Biotechnology-Related Fields

This project will focus on an early stage exploratory study of an idea that will reveal ways to develop more effective interventions to address student retention in bioscience and bioengineering pipelines. The study will attempt to initiate a new line of research in search of factors associated with bioscience and bioengineering education as a novel approach for uncovering factors that may negatively influence student participation in these fields.

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This project will focus on an early stage exploratory study of an idea that will reveal ways to develop more effective interventions to address student retention in bioscience and bioengineering pipelines. As such, this study will help meet future workforce needs by taking a radical approach and looking beyond mathematics as the key major factor that determines student participation in STEM fields. To better understand what these factors might be, this study will examine high school transcripts from two local high schools. It will also review records of 350 undergraduate students who have been enrolled, are currently enrolled, have graduated, switched to another non-STEM field at the same institution, or left undergraduate programs in biotechnology-related fields. Data sources will include information on all mathematics, bioscience, biotechnology-related courses taken in high school and in college; college entrance test scores, and students' performance in bioengineering at the undergraduate level. This study will attempt to initiate a new line of research in search of factors associated with bioscience and bioengineering education as a novel approach for uncovering factors that may negatively influence student participation in these fields.

An interdisciplinary approach will be used to mine and analyze student data at the intersection of mathematics, biosciences, engineering, and technology. Although it is unclear if this approach will generate any new insights potentially beneficial to society, knowing whether the idea works or not will be a valuable contribution to the field. Additionally, this approach will not only be relevant to biosciences and bioengineering, but also important to national efforts, and will contribute to NSF's Big Idea on Harnessing the Data Revolution. However, attempting to merge data sets from multiple sources is risky since it may not reveal any meaningful information useful to addressing student retention. Such risks may be further compounded by the limited focus of the study on mostly content driven factors, a wide variation of pathways and classes, availability of courses, personal variation of student development, and motivation and interest in particular STEM subjects. Due to the complexity of this undertaking and the focus largely on student performance and success in these fields, the risk is high. These risks notwithstanding, outcomes from this study could potentially identify factors, other than mathematics, that might contribute to current attrition rates. Thus, this study will inform the development of more effective models of intervention, help prioritize broadening participation efforts, and promote further research.

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