MathBench Biology Modules: Web-Based Math for All Biology Undergraduates

By Nelson, Karen C.; Marbach-Ad, Gili et al. | Journal of College Science Teaching, March-April 2009 | Go to article overview

MathBench Biology Modules: Web-Based Math for All Biology Undergraduates


Nelson, Karen C., Marbach-Ad, Gili, Schneider, Katie, Thompson, Katerina V., Shields, Patricia A., Fagan, William F., Journal of College Science Teaching


Historically, biology has not been a heavily quantitative science, but this is changing rapidly (Ewing 2002; Gross 2000; Hastings and Palmer 2003; Jungck 2005; Steen 2005). Quantitative approaches now constitute a key tool for modern biologists, yet undergraduate biology courses remain largely qualitative and descriptive. Although biology majors are often required to take a full year of calculus, these courses generally use examples unrelated to biology (Gross 1994) and ignore fields of mathematics that may be more relevant to biology, such as linear algebra or theoretical probability and statistics (NRC 2003).

Consequently, reform of the undergraduate biological science curriculum is urgently needed (NRC 2003; Steen 2005). However, there are significant barriers to integrating more quantitative approaches. Students have a reputation (deserved or not) for opposing the addition of mathematical content, and many professors are likewise uncomfortable with negative reactions and lack of mathematical mastery they perceive among their students (Yuan 2005; Jungck 2005). Finally, even when students have mastered both biology and mathematics, the connection between the two is problematic (Gross 1994; Jungck 2005). Math courses are rarely taught in a way that facilitates the ability to transfer mathematical knowledge to real-life, open-ended situations, still less to problems specifically involving the biological sciences.

The problematic connection between math and biology has been evident at the College of Chemical and Life Sciences at the University of Maryland, a large, public, Research I university. Surveys of our faculty indicated that they wanted to make their courses more mathematically rigorous but hesitated to do so because they feared students would respond negatively or would not be adequately prepared for a more quantitative approach. Nonetheless, there was consensus among faculty that tighter integration of biology and mathematics would better prepare our students for scientific careers. We designed these modules to provide tighter integration in a way that does not require instructors to substantially revise their courses. Mathematics can be integrated in a systematic way across the curriculum so that students experience a progression of instruction that builds both their quantitative reasoning skills and their confidence.

[ILLUSTRATION OMITTED]

We began by assembling a list of "metaconcepts"--mathematical skills and concepts to be emphasized (Table 1), drawing from precalculus mathematics exclusively, because many students enrolled in introductory biology have yet to complete calculus. We then worked with faculty teaching introductory biology courses to identify the best places to introduce or reinforce mathematical concepts within the existing syllabus. Using this information, we developed the MathBench Biology Modules, a suite of interactive, web-based modules that supplement existing course content across the first two years of the biological sciences curriculum. Undergraduate biology majors will encounter 25 to 30 modules over the course of their first five fundamental biology courses. The modules cover a variety of topics but focus repeatedly on a core set of skills and concepts. Thus, MathBench makes quantitative approaches accessible and relevant to all students enrolled in biology courses.

Designing the modules

In designing the modules, we considered three key findings from the science education literature:

* Many college students have trouble with quantitative work because of "math anxiety" (Betz 1978). The modules are written in uncomplicated, colloquial speech, following numerous studies showing that a "personal voice" fosters deep learning while minimizing anxiety (d'Ailly, Simpson, and MacKinnon 1997; Mayer et al. 2004; Ross and Anand 1987). The modules also provide carefully structured repetition of key concepts, which has been shown to reduce math anxiety (Betz 1978) and "cement" mathematical knowledge (Bahrick and Hall 1991).

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