If you had a chance to design a new course from scratch, would you take advantage of the opportunity to include Vision and Change Competencies? Would you follow comfortable patterns and retrofit a similar course’s design, or would you embrace a new way of thinking about your role in biology education?
As part of my reflection assignments as a LifeSciTRC Vision and Change Scholar, I was posed with the question of ‘what would your ideal course be like’? For this assignment I considered aspects of a course that I have been wanting to develop for several years, Computational Physiology. Such a course has never been taught at my institution and would be a welcome complement to our traditional offerings in physiology as well as integrating across disciplines (e.g., biology, mathematics, and physics).
This hypothetical opportunity quickly became an actual opportunity as I was able to offer Computational Physiology as an experimental course during the fall semester of 2014. Core concepts of the relationship between structure and function provide a framework for developing two competencies (e.g., ability to use quantitative reasoning and ability to use modeling and simulation). These competencies drove the selection and sequencing of topics for the course. Resources that I used in designing the course have been compiled into a LifeSciTRC Vision and Change Teacher-Recommended Collection: Computational Physiology Course Development and Simulations.
We meet once per week in an extended class session that allows in-depth examination of models and to run the selected simulation experiments. Prior to each class, students read and prepare a summary of a review paper or research article on the week’s topic. During each class (which is held in a computer lab) students perform calculations based on the models to use numbers to reason through physiological cause-and-effect relationships. Once the relationship is understood, students design and conduct simulation experiments based on information from the research or review papers, calculations or models, or their personal interests. Data from the simulation experiments are analyzed and interpreted in reports that the student then write and submit.
The successes of the course are in the simulation experiments run by the students. Feedback indicates that these are course elements that are enjoyed, are stimulating, and can lead to cross-over applications in other courses taken by the students. While not a failure, the biggest unknown that I have struggled with is by what “yardstick” is student performance measured, particularly in new course. Some simulations work really well and it is easy to push students to new levels of understanding. Other simulations are not so effective and frustration is common for all students. To date, I have been assessing the yardstick of performance on a week-by-week basis but would like to have greater consistency across weeks.
Carol Britson, Ph.D., is a Lecturer in the Biology department at Ole Miss. She earned her B.S. at Iowa State University and her M.S. and Ph.D. at the University of Memphis. She has been at Ole Miss for over 15 years and teach courses in Vertebrate Histology, Human Anatomy and Physiology, and Introductory Physiology. Carol is a LifeSciTRC Scholar, Fellow, and Advisory Board Member.