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Quantitative Expertise in the Undergraduate Biology Curriculum (QEUBiC) Framework at Bethune-Cookman University

Faculty #11
Discipline: Biological Sciences
Subcategory: STEM Science and Mathematics Education

Raphael D. Isokpehi - Bethune-Cookman University
Co-Author(s): Katharina Wollenberg Valero, Ahkinyala M. Cobb-Abdullah, Shukdeb Sen, and Elizabeth R. Congdon, Bethune-Cookman University, Daytona Beach, FL



The Quantitative Expertise in the Undergraduate Biology Curriculum (QEUBiC) framework provides an adoptable curriculum framework for infusing key topics in data challenges to biology coursework. Topics in the dimensions of data challenges described by the National Consortium for Data Science as data flow; data analytics and data curation are being infused in the biology curriculum at Bethune-Cookman University (B-CU) through diverse learning experiences. The project is increasing opportunities for students at Bethune-Cookman University to engage in diverse complex cognitive activities such as knowledge discovery, decision making and analytical reasoning from biological data. New questionnaires have been developed to assess learning dimensions, computing use and quantitative capabilities of students. In the QEUBiC framework, evidence-based learning strategies including metacognition and visualization are being implemented to equip students as strategic learners who are able to decide the appropriate learning strategy (strategic learning) to overcome the challenges of discovery and analysis of biological information from multiple sources. Additionally, quantitative reasoning in biology requires students to engage in practices of mathematical thinking (counting, measuring, calculating, graphing, mapping, ordering, problem solving, analysis, hypothesis testing, and, modeling). These pedagogical approaches are being introduced in general education math courses to help better prepare biology students for the upper level data-intensive biology courses. Three research and innovation facilitating courses have been developed through this project: Advanced Computing Resources in Biology; Computational Genomics; and BioMolecular Technologies. BioMolecular Technologies, a junior-level course, will be offered in the Spring 2016 semester and will include learning experiences with advanced instrumentation for biological data generation as well as industry visit to a manufacturer of advanced biological laboratory infrastructure in Volusia County, Florida.

Funder Acknowledgement(s): National Science Foundation HRD-1435186

Faculty Advisor: None Listed,

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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