COS 7-7 - Infusing quantitative literacy in large-enrollment introductory biology courses

Monday, August 2, 2010: 3:40 PM
336, David L Lawrence Convention Center
Elena Bray Speth1, Jennifer L. Momsen2, Gregory Moyerbrailean3, Tammy M. Long3 and Diane Ebert-May3, (1)Biology, Saint Louis University, Saint Louis, MO, (2)Department of Biological Sciences, North Dakota State University, Fargo, ND, (3)Plant Biology, Michigan State University, East Lansing, MI
Background/Question/Methods

Quantitative literacy (QL) – the ability to interpret, represent and communicate about numerical information in a “real world” context – is a desired learning outcome in most colleges and universities. However, because QL is not a discipline in itself, it is often unclear whose responsibility it is to teach it, what evidence demonstrates achievement, and what pedagogical practices lead to development of QL skills.  The practice of biology is increasingly dependent on the ability to reason with numbers. The undergraduate biology curriculum, therefore, must incorporate opportunities for students to develop QL.

We sought to find out (a) what QL skills students bring into introductory biology courses, and (b) what instructional designs could improve students’ ability to apply quantitative reasoning in biology (i.e., formulate scientific arguments based on numeric evidence).  We assessed students’ QL skills at the beginning and at the end of a large-enrollment introductory biology course. Based on these data, we identified the need to explicitly incorporate QL in the design of our course objectives, instruction, and assessments.

Results/Conclusions

On a case-based assessment at the beginning of the semester, we provided a table of raw data, and asked students to: (a) compute simple arithmetic means, (b) construct an appropriate graph, (c) articulate a claim based on the data, and, (d) provide justification (warrants) for their claim. Analysis of the assessment revealed that, at the beginning of the course, 57% of students correctly calculated and represented means on a graph; 10% correctly labeled the dependent variable (y axis); 29% formulated a complete and correct claim about the data; 27% provided appropriate reasoning to support their claim.  Based on these data, we tailored instruction and assessment in the course to incorporate QL.  Analysis of a problem embedded in the final exam provided evidence of students’ progress in their ability to graphically represent numerical data and to justify data-driven claims. Given a data set, 95% of students correctly calculated and plotted frequency values on a graph; 92% correctly labeled the y axis; 30% appropriately reasoned that a statistical test of significance would be necessary to support a claim based on the data.

We conclude that an instructional design that aligns QL objectives with assessments, coupled with an active learning pedagogy, is feasible, consistent with the broader undergraduate introductory biology learning goals, and enables students to develop important QL skills.

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