Building Mathematical Models and Biological Insight in an Introductory Biology Course

A. E. Weisstein

Mathematical Modelling of Natural Phenomena (2011)

  • Volume: 6, Issue: 6, page 198-214
  • ISSN: 0973-5348

Abstract

top
A growing body of literature testifies to the importance of quantitative reasoning skills in the 21st-century biology curriculum, and to the learning benefits associated with active pedagogies. The process of modeling a biological system provides an approach that integrates mathematical skills and higher-order thinking with existing course content knowledge. We describe a general strategy for teaching model-building in an introductory biology course, using the example of a model of an infectious disease outbreak. Preliminary assessment data suggest that working through the formal process of model construction may help students develop their scientific reasoning and communication skills.

How to cite

top

Weisstein, A. E.. "Building Mathematical Models and Biological Insight in an Introductory Biology Course." Mathematical Modelling of Natural Phenomena 6.6 (2011): 198-214. <http://eudml.org/doc/222242>.

@article{Weisstein2011,
abstract = {A growing body of literature testifies to the importance of quantitative reasoning skills in the 21st-century biology curriculum, and to the learning benefits associated with active pedagogies. The process of modeling a biological system provides an approach that integrates mathematical skills and higher-order thinking with existing course content knowledge. We describe a general strategy for teaching model-building in an introductory biology course, using the example of a model of an infectious disease outbreak. Preliminary assessment data suggest that working through the formal process of model construction may help students develop their scientific reasoning and communication skills. },
author = {Weisstein, A. E.},
journal = {Mathematical Modelling of Natural Phenomena},
keywords = {mathematical modeling; education; mathematical biology; epidemiology},
language = {eng},
month = {10},
number = {6},
pages = {198-214},
publisher = {EDP Sciences},
title = {Building Mathematical Models and Biological Insight in an Introductory Biology Course},
url = {http://eudml.org/doc/222242},
volume = {6},
year = {2011},
}

TY - JOUR
AU - Weisstein, A. E.
TI - Building Mathematical Models and Biological Insight in an Introductory Biology Course
JO - Mathematical Modelling of Natural Phenomena
DA - 2011/10//
PB - EDP Sciences
VL - 6
IS - 6
SP - 198
EP - 214
AB - A growing body of literature testifies to the importance of quantitative reasoning skills in the 21st-century biology curriculum, and to the learning benefits associated with active pedagogies. The process of modeling a biological system provides an approach that integrates mathematical skills and higher-order thinking with existing course content knowledge. We describe a general strategy for teaching model-building in an introductory biology course, using the example of a model of an infectious disease outbreak. Preliminary assessment data suggest that working through the formal process of model construction may help students develop their scientific reasoning and communication skills.
LA - eng
KW - mathematical modeling; education; mathematical biology; epidemiology
UR - http://eudml.org/doc/222242
ER -

References

top
  1. J. Bransford, J. Franks, N. Vye, R. Sherwood (1989). New Approaches to Instruction: Because Wisdom Can’t be Told. In S. Vosiadou & A. Ortony (Eds.), Similarity and Analogical Reasoning (pp. 470–497). New York: Cambridge University Press.  
  2. P. Burrowes. A student-centered approach to teaching general biology that really works: Lord’s constructivist model put to a test. Am. Biol. Teach., 65 (2003), No. 7, 491–502.  
  3. Centers for Disease Control (2004). Smallpox Fact Sheet: Vaccine Overview. Available online at  ⟨  ⟩ ; last accessed on 1/20/2011.  URIhttp://www.bt.cdc.gov/agent/smallpox/vaccination/facts.asp
  4. H. Ewing, K. Hogan, F. Keesing, H. Bugmann, A. Berkowitz, L. Gross, J. Oris, J. Wright (2003). “The role of modeling in undergraduate education”. Pages 413427 in Canham CD, Cole JJ, Laurenroth WK, eds. Models in Ecosystem Science. Princeton (NJ): Princeton University Press.  
  5. S. Freeman. Biological Science, 4th edition. Pearson Benjamin Cummings, San Francisco, 2011.  
  6. R. Hake. Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. Am. J. Phys., 66 (1998), No. 1, 64–74.  
  7. J. Hodder, D. Ebert-May, and J. Batzli. Coding to analyze students’ critical thinking. Front. Ecol. Environ., 4 (2006), No. 3, 162–163.  
  8. G. Johnson (2005). “Infectious Disease and Bioterrorism.” In PH Raven, GB Johnson, J Losos, and S Singer, Biology, 7th edition (Enhancement Chapter 33e). New York, NY: McGraw-Hill.  
  9. J. Jungck (2005). “Challenges, Connections, Complexities: Educating for Collaboration”. Pages 1–12 in Math and Bio 2010: Linking Undergraduate Disciplines (ed. LA Steen).  
  10. J. Jungck and J. Calley. Strategic simulations and post-Socratic pedagogy: Constructing computer software to develop long-term inference through experimental inquiry. Am. Biol. Teach., 47 (1985), No. 1, 11–15.  
  11. K. Kastens (2002). My Top Ten Topics in Geoscience Education Research, for a conference on “Bringing Research on Learning to the Geosciences.” (accessed 1/17/2011).  URIhttp://serc.carleton.edu/files/research_on_learning/KKtopten.pdf
  12. W. Kermack and A. McKendrick. A contribution to the mathematical theory of epidemics. Proc. Roy. Soc. Lond. A, 115 (1927), No. 772, 700–721.  Zbl53.0517.01
  13. E. Kitchen, J. Bell, S. Reeve, R. Sudweeks, W. Bradshaw. Teaching cell biology in the large-enrollment classroom: Methods to promote analytical thinking and assessment of their effectiveness. Cell Biol. Educ., 2 (2003), No. 3, 180–194.  
  14. J. Knight and W. Wood. Teaching more by lecturing less. Cell Biol. Educ., 4 (2005), No. 4, 298–310.  
  15. Lauenroth WK, Burke IC, and Berry JK (2003). “The Status of Dynamic Quantitative Modeling in Ecology”. Pages 32–48 in Canham CD, Cole JJ, Laurenroth WK, eds. Models in Ecosystem Science. Princeton (NJ): Princeton University Press.  
  16. M. Meltzer, I. Damon, J. LeDuc, J. Millar. Modeling Potential Responses to Smallpox as a Bioterrorist Weapon. Emerg. Infect. Dis., 7 (2001), No. 6, 959–969.  
  17. National Research Council. Bio 2010: Transforming Undergraduate Education for Future Research Biologists. National Academies Press, Washington D.C., 2003.  
  18. J. Reece, L. Urry, M. Cain, S. Wasserman, P. Minorsky, and R. Jackson. Campbell Biology, 9th edition. Pearson Benjamin Cummings, San Francisco, 2010.  
  19. SENCER: Science Education for New Civic Engagements and Responsibilities.  ⟨  ⟩ . Accessed 13 January 2011.  URIwww.sencer.net
  20. J. Trempy, M. Skinner, W. Siebold. Learning microbiology through cooperation: Designing cooperative learning activities that promote interdependence, interaction, and accountability. Microbiol. Educ., 3 (2002), No. 1, 26–36.  
  21. Turner, MG (2003). “Modeling for Synthesis and Integration: Forests, People, and Riparian Coarse Woody Debris”. Pages 83–110 in Canham CD, Cole JJ, Laurenroth WK, eds. Models in Ecosystem Science. Princeton (NJ): Princeton University Press.  
  22. D. Udovic, D. Morris, A. Dickman, J. Postlethwait, P. Wetherwax. Workshop Biology: Demonstrating the effectiveness of active learning in an introductory biology course. BioScience, 52 (2002), No. 3, 272–281.  

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.