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Page last modified 16:22, 15 Feb 2009 by ahoskinson

Welcome to the Biology Scholars Program Wiki > RESEARCH RESIDENCY > 2008 Research Cohort > Research Scholars > Hoskinson, Anne-Marie > Journal > ASMcue09

Cooperative curriculum helps students learn mathematical biology

Biological sciences increasingly use mathematical modeling to describe, predict, or control complex systems. Unlike physics or chemistry, many problems in mathematical biology cannot be solved with algorithms, and biology undergraduates resist the steep learning curve. Based on well-understood principles of cooperative learning, I designed a one-semester undergraduate course in mathematical modeling in biology. Students learned principles of mathematics, biology, and collaborative teamwork by building models to solve real biological problems. While the principles of cooperative learning are well-documented, I found very few practical accounts of implementing cooperative learning, so I describe the development and evolution of the curriculum over four sequential semesters. Students assessed their own learning at 0, 4, 12, and 16 months after completing the class, in both academic and interpersonal learning. Students reported significant and persistent gains in learning mathematics and biology, and in understanding the connections between the two fields. Students also reported significant and persistent gains in their collaborative and team skills. Since the curriculum is based on broad objectives of cooperative learning and of mathematical biology, this curriculum design can be adapted to many settings.

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I think that the abstract could be improved by reducing the initial introductory sentences and adding more detail of what you did: e.g. the types of biological problems solved and how you implemented cooperative learning. This is particularly important because your final sentence talks about extending the approach to other settings, but the reader will not easily be able to see this, because there is too little about your curriculum. At the moment I think that your abstract undersells your research, you have a really nice data set on long-term retention, which is really important, but this doesn't really come through in the abstract. When you say significant gains, is this a statistical gain or what the students perceived? Do you have data on their actual learning in addition to their perceptions?

I agree with Chris that some details on the problems and resulting data would flesh this out, especially the alluded to long-term retention data. You won't have to reduce the intro material by much -- you have only 1388 characters (including spaces) and ASM-CUES is allowing 1850, so you have some room to make those additions.

I am looking forward to seeing this project at the meeting. My only comment is on the second sentence "Unlike physics or chemistry, many problems in mathematical biology cannot be solved with algorithms, and biology undergraduates resist the steep learning curve" it is an awkward sentence given that it is unclear which learning curve you refer to (algorithms) however this problem will disapear if you follow some of the other comments.