After many essential conversations with members of my QUBES Faculty Mentoring Network, I implemented the Demography from Cemeteries module in my course MAT 1314 Modeling for the Life Sciences, a new course offered for the first time in the spring 2016 semester. This new course was designed at the request of the Department of Biology and the Program in Cognitive and Behavioral Neurosciences, to complement redesigned courses in Biocalculus and Statistics for the Life Sciences. The class was in lecture-discussion format, meeting twice per week for 75 minutes each. We did not have a long lab session time available to us. Since this was a quantitative course designed for life sciences students rather than a quantitative module in what is otherwise a life sciences course, the focus was on the quantitative skills. The primary objectives were to acquire some understanding of and facility with using and interpreting life tables. Other objectives included familiarity with Excel in a scientific context, experience in selecting a data set, formulating and addressing questions that are both on topic for the classroom discussion and appropriate for the data set available. Finally, the broader objective was to place the questions and tools of the module within the context of the remainder of the course, since this module came at the end of the semester.

Since the students arrived with some experience with Excel and data, I was able to present the module as follows. I introduced the concepts for the module in the final portion of one class period and handed out a subset of the Lanza paper for the students to read for the next class, along with a couple of brief handouts on cohort vs. static life tables. In the next class, I spent part of the class period talking through the planned exercise and addressed any student questions from the reading. I also talked briefly about several online references to life tables (links included above) as we looked through them together in class, projected on the screen. I asked the students to search for an appropriate data set online, download it, and bring it to the next class in Excel, ready to work. In the next class, I took questions and went on to other material, leaving them several days to complete their assignment and submit it to me online.  We did not take the time for oral presentations to the class as suggested in the Lanza paper.

Because this was a Math course rather than a Science course, the quantitative focus pervaded the entire semester, so there was inherent scaffolding in some sense. On the other hand, I tried throughout the semester when dealing with seemingly more theoretical structures such as differential equations and difference equations to talk about how data could inform, validate, and verify the models, so a module specifically on data was a natural follow-on by the end of the semester.​

In my next version of the course, I would place the module earlier in the mix of the course topics, spend more time on other uses of life tables, and be a little more explicit in constructing examples rather than simply talking through finished examples.

​Douglas Norton

Villanova University

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