Quantitative Methods in Biomedical Applications: Creative Inquiry and Digital-Learning Environments to Engage and Mentor STEM Students in Mathematics (NSF Funded Research)
With an increasing demand for biomedical and bioengineering professionals in the coming decades, educators are tasked with readying a greater number of STEM students who are able to apply mathematical concepts to critical health care decisions. In this work, we have developed a series of for-credit, applied learning modules that are being given in parallel to the freshman and sophomore calculus curriculum. These modules use creative inquiry and applied learning experiences to connect mathematical concepts with bioengineering and medical applications. We hypothesize that exposure and participation in the applied learning experiences outside of standard mathematics classes will improve the students’ performance and perceived appreciation for their math curriculum.The four module series is offered over a 2-year period to groups of up to 25 students and emphasizes mathematics and statistics relevant to four biomedical research areas (1) orthopedics, (2) infectious diseases, (3) heat propagation in the human body, and (4) mammography and radiology.This scalable project utilizes a diverse set of faculty from the math and bioengineering departments. The project value to STEM goals is found in (1) convincing students through applied learning experiences that mathematics is an important component of any research plan and indispensable to their career success and (2) ensuring that these students do not falter in calculus and abandon their STEM goals. This paper presents our developed methods and initial findings from module one with the hopes of inspiring other institutions to adopt similar applied learning experiences for their STEM students.
KeywordsTotal Joint Replacement Creative Inquiry Applied Learning Stem Field Bioengineering Department
The authors wish to thank Clemson University for supporting the efforts of the Creative Inquiry program and the NSF DUE Award number 1044265. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the National Science Foundation.
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