Abstract
As part of a broader effort of developing a comprehensive neuroscience curriculum, we implemented an interdisciplinary, one-semester, upper-level course called Biophysical Modeling of Excitable Cells (BMEC). The course exposes undergraduate students to broad areas of computational biology. It focuses on computational neuroscience (CNS), develops scientific literacy, promotes teamwork between biology, psychology, physics, and mathematics-oriented undergraduate students. This course also provides pedagogical experience for senior Ph.D. students from the Neuroscience Department at the Medical University of South Carolina (MUSC). BMEC is a three contact hours per week lecture-based course that includes a set of computer-based activities designed to gradually increase the undergraduates’ ability to apply mathematics and computational concepts to solving biologically-relevant problems. The class brings together two different groups of students with very dissimilar and complementary backgrounds, i.e., biology or psychology and physics or mathematics oriented. The teamwork allows students with more substantial biology or psychology background to explain to physics or mathematics students the biological implications and instill realism into the computer modeling project they completed for this class. Simultaneously, students with substantial physics and mathematics backgrounds can apply techniques learned in specialized mathematics, physics, or computer science classes to generate mathematical hypotheses and implement them in computer codes.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Austin, A.: Preparing the next generation of faculty: graduate school as socialization to the academic career. J. High. Educ. 73, 94–122 (2002). https://doi.org/10.1353/jhe.2002.0001
Bialek, W., Botstein, D.: Introductory science and mathematics education for 21st-century biologists. Science 303, 788–790 (2004). https://doi.org/10.1126/science.1095480
Caldwell, J.E.: Clickers in the large classroom: current research and best-practice tips. CBE Life Sci. Educ. 6(1), 9–12 (2007). https://doi.org/10.1187/cbe.06-12-0205
Chien, Y., Smith, M.L.: Powerpoint: is it an answer to interactive classrooms? Int. J. Instr. Media 35(3), 271 (2008)
Ermentrout, B.: Simulating, Analyzing, and Animating Dynamical Systems: A Guide to XPPAUT for Researchers and Students. SIAM (2002). https://doi.org/10.1137/1.9780898718195
Feldon, D., et al.: Graduate students’ teaching experiences improve their methodological research skills. Science 333, 1037–1039 (2011). https://doi.org/10.1126/science.1204109
Holley, K.A.: The longitudinal career experiences of interdisciplinary neuroscience PhD recipients. J. High. Educ. 89(1), 106–127 (2018). https://doi.org/10.1080/00221546.2017.1341755
Hunter, A.B., Laursen, S., Seymour, E.: Becoming a scientist: the role of undergraduate research in students? Cognitive, personal, and professional development. Sci. Educ. 91, 36–74 (2006). https://doi.org/10.1002/sce.20173
Hurd, M., Vincent, D.: Functional magnetic resonance imaging (fMRI): a brief exercise for an undergraduate laboratory course. J. Undergrad. Neurosci. Educ. 5, A22–A27 (2006)
Kaplan, D.: Explanation and description in computational neuroscience. Synthese 183(3), 339–373 (2011). https://doi.org/10.1007/s11229-011-9970-0
Knight, J.: A primer on instructional coaching. Principal Leadersh. 5, 17–20 (2005)
Kozeracki, C., Carey, M., Colicelli, J., Levis-Fitzgerald, M.: An intensive primary-literature-based teaching program directly benefits undergraduate science majors and facilitates their transition to doctoral programs. Life Sci. Educ. 5, 340–347 (2006). https://doi.org/10.1187/cbe.06-02-0144
Latimer, B., Bergin, D., Guntu, V., Schulz, D., Nair, S.: Open source software tools for teaching neuroscience. J. Undergrad. Neurosci. Educ. 16(3), A197–A202 (2018)
Luft, J., Kurdziel, J., Roehrig, G., Turner, J.: Growing a garden without water: graduate teaching assistants in introductory science laboratories at a doctoral/research university. J. Res. Sci. Teach. 41, 211–233 (2004). https://doi.org/10.1002/tea.20004
Mazur, E.: Peer Instruction: A User’s Manual. Series in Educational Innovation. Prentice Hall, Hoboken (1997)
Miller, J., Martineau, L., Clark, R.: Technology infusion and higher education: changing teaching and learning. Innov. High. Educ. 24, 227–241 (2000). https://doi.org/10.1023/B:IHIE.0000047412.64840.1c
Moore, J., Stuart, A.: Neurons in Action Version 2: Tutorials and Simulations Using NEURON. Sinauer Associates, Sunderland, MA, USA (2007)
Muir, G.: Mission-driven, manageable and meaningful assessment of an undergraduate neuroscience program. J. Undergrad. Neurosci. Educ. 13(3), A198–A2015 (2015)
Oprisan, S.: Teaching computational neuroscience at a liberal arts and sciences undergraduate college. Society for Neuroscience, Washington, DC (2011)
Oprisan, S.: Introducing computational neuroscience concepts and research projects to undergraduates. Society for Neuroscience, New Orleans, LA (2012)
Ramirez, J.J.: Undergraduate neuroscience education: meeting the challenges of the 21st century. Neurosci. Lett. 739, 135418 (2020). https://doi.org/10.1016/j.neulet.2020.135418
Salomon, D., Martin-Harris, L., Mullen, B., Odegaard, B., Zvinyatskovskiy, A., Chandler, S.: Brain literate: making neuroscience accessible to a wider audience of undergraduates. J. Undergrad. Neurosci. Educ. 13(3), A64–A73 (2015)
Schultheiss, S.: Ten simple rules for providing a scientific web resource. PLoS Comput. Biol. 7(5), e1001126 (2011). https://doi.org/10.1371/journal.pcbi.1001126
Stanley, D.: Can technology improve large class learning? The case of an upper-division business core class. J. Educ. Bus. 88, 265–270 (2013). https://doi.org/10.1080/08832323.2012.692735
Stuart, A.: Teaching neurophysiology to undergraduates using neurons in action. J. Undergrad. Neurosci. Educ. 8(1), A32–A36 (2009)
Wiertelak, E., Hardwick, J., Kerchner, M., Parfitt, K., Ramirez, J.: The new blueprints: undergraduate neuroscience education in the twenty-first century. J. Undergrad. Neurosci. Educ. 16(3), A244–A251 (2018)
Acknowledgments
This work was supported by a Research & Development grant form the CofC and an award from the South Carolina Space Grant Consortium.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Oprisan, S.A. (2021). Biophysical Modeling of Excitable Cells - A New Approach to Undergraduate Computational Biology Curriculum Development. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12747. Springer, Cham. https://doi.org/10.1007/978-3-030-77980-1_46
Download citation
DOI: https://doi.org/10.1007/978-3-030-77980-1_46
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-77979-5
Online ISBN: 978-3-030-77980-1
eBook Packages: Computer ScienceComputer Science (R0)