1, 2, 3, 4: infusing quantitative literacy into introductory biology

Abstract

Biology of the twenty-first century is an increasingly quantitative science. Undergraduate biology education therefore needs to provide opportunities for students to develop fluency in the tools and language of quantitative disciplines. Quantitative literacy (QL) is important for future scientists as well as for citizens, who need to interpret numeric information and data-based claims regarding nearly every aspect of daily life. To address the need for QL in biology education, we incorporated quantitative concepts throughout a semester-long introductory biology course at a large research university. Early in the course, we assessed the quantitative skills that students bring to the introductory biology classroom and found that students had difficulties in performing simple calculations, representing data graphically, and articulating data-driven arguments. In response to students' learning needs, we infused the course with quantitative concepts aligned with the existing course content and learning objectives. The effectiveness of this approach is demonstrated by significant improvement in the quality of students' graphical representations of biological data. Infusing QL in introductory biology presents challenges. Our study, however, supports the conclusion that it is feasible in the context of an existing course, consistent with the goals of college biology education, and promotes students' development of important quantitative skills.

Figure 1.

The Frog problem, adapted from an original problem (http://first2.plantbiology.msu.edu/resources/inquiry_activities/frog_activity.htm). This problem was developed by D. L. and D.E.M., based on the work of Kiesecker (2002), and includes text quoted from Miller (2002).

Figure 2.

The Wolf problem. The data that guided design of this problem are publicly available through the “Wolves and Moose of Isle Royale” website (www.isleroyalewolf.org/overview/overview/wolf%20bones.html).

Figure 3.

QL skills demonstrated by students at the beginning of the course (assessed through the Frog problem).

Figure 4.

Pre- and postinstruction change in the quality of student-generated graphs; “pre” refers to the Frog problem on quiz 1, and “post” refers to the Wolf problem on the final exam. (A) Scores attributed to students' graphs significantly improved after instruction. (B) Examples of student graphs that earned a score of 4 on the Frog problem (top) and the Wolf problem (bottom). (C) Change in the percentage of students who demonstrated specific graphing skills.