The History and Intention of Q Courses

In 2003 the College of Biological Sciences at the University of California, Davis undertook a complete re-examination of its core curriculum. Among the several recommendations coming from the committee undertaking this task was a clear call for an improvement in the integration of quantitative approaches and concepts into the teaching of biology. Like many other institutions we recognized that biology has changed fundamentally in the last two decades and is now a thoroughly quantitative science relying on quantitative models to understand virtually all major, contemporary problems. As in most other institutions, we require our biological science majors to take a year of calculus, physics, chemistry, and some statistics. Yet in spite of this, the problem acknowledged by all biology instructors is that students are generally unable to apply quantitative concepts to biology. As part of a solution to this problem we wanted to integrate quantitative techniques and modeling into biology instruction. The Q courses appearing at this web site are the product of that intention facilitated by a grant from the National Institutes of Health, NIH #1K07GM073050-01, with additional support for both course and web site development provided by the Howard Hughes Medical Institute.

With the exception of BIS 20Q – the “Introductory Modeling in Biology”, all Q courses comprise only the weekly assignments (“modules”) found on this web site and are all designed to run in parallel with an already established, high-enrollment course. In this sense, most of the Q courses can be considered quantitative computer lab courses to accompany a parent lecture course. The Introductory course is self-contained and includes its own lecture component.

Q courses take examples from the parent lecture course and examine material in a quantitative light. The goals of these Q courses are, in order of importance:

  1. To familiarize students with quantitative methods and approaches in the biological sciences
  2. To increase student comfort in linking their knowledge of math to their knowledge and interest in biology
  3. For students to appreciate why quantitative models are useful
  4. For students to understand the rudiments of making and interpreting biological models.

The intention is not primarily to improve students’ understanding of a particular field of biology. Although, for example, we have found that students enrolled in Q courses earn higher grades in their concurrent parent lecture class than their GPA-matched peers. This is not surprising, but we make no claim that our quantitative courses are the best way to improve student grades.

Our Q courses are based on the software application, Mathcad. This general purpose mathematical software package is available free to instructors and available at a considerable discount to our students because of a bulk licensing agreement through our university bookstore. In addition, we make Mathcad available for student use in our computer labs. We chose Mathcad because it closely resembles familiar mathematical notation and is easier for beginning students to pick up than other applications (e.g., R or Matlab). Many of the skills students acquire using Mathcad can later be transferred to other software and we do not discourage instructors from adopting other more specialized, or just different, software in more advanced courses.

Traditionally, quantitative courses of this sort have been targeted at advanced and/or exceptional undergraduates. In contrast, our goal here is to educate the average biology undergraduate. This is one of the reasons that we focus on existing high-enrollment lecture courses required by our majors. Further, we recognize that these lecture courses are taught by a variety of faculty who may or may not have interest promoting quantitative approaches in their lecture and test material. For this reason, the Q courses are designed to be run and graded by a teaching assistant with, if necessary, little intervention on the part of the faculty lecturer. However, the modules are more or less independent of one another, and can be reasonably reordered to align with the parent lecture sequence.