Chapter 4 Proving the “Proof”: Interdisciplinary Undergraduate Research Positively Impacts Students M.L. Crowe, J. Rychtᡠr, O. Rueppell, M. Chhetri, D.L. Remington, and S.N. Gupta 4.1 Introduction The biological sciences encompass a broad spectrum of academic fields and most sub-disciplines include mathematical modeling and statistical analysis as an integrative component of their scientific process. Advances in computational technology have promoted the growth of the newest interdisciplinary fields such as epidemiology, systems biology, neuroscience, genomics and nanotechnology and bioinformatics. These interdisciplinary areas of study are data rich, requiring new mathematical models and tools to recognize patterns and manage informa- tion. The increasingly sophisticated modeling and analytical techniques of these and other biological fields require the twenty-first century biologist to possess more advanced skills in mathematics. Conversely, the most productive contem- porary mathematicians have a broad, interdisciplinary scientific training, with most prospects interfacing with the biological sciences. Educational approaches to prepare biology and mathematics students for these twenty-first century career opportunities, however, have lagged behind the recent advances in mathematical and computational applications in biology. The Mathematical Association of America M.L. Crowe () Associate Provost of Experiential Education, Florida Southern College, Lakeland, FL 33801-5698, USA e-mail: mcrowe@flsouthern.edu J. Rychtᡠr • M. Chhetri • S.N. Gupta Department of Mathematics and Statistics, The University of North Carolina at Greensboro, Greensboro, NC 27402, USA e-mail: rychtar@uncg.edu; m_chhetr@uncg.edu; sngupta@uncg.edu O. Rueppell • D.L. Remington Department of Biology, The University of North Carolina at Greensboro, Greensboro, NC 27402, USA e-mail: olav_rueppell@uncg.edu; dlreming@uncg.edu J. Rychtᡠr et al. (eds.), Topics from the 8th Annual UNCG Regional Mathematics and Statistics Conference, Springer Proceedings in Mathematics & Statistics 64, DOI 10.1007/978-1-4614-9332-7__4, © Springer Science+Business Media New York 2013 25