Institution/institution type: Augustana College (residential liberal arts college)

Course/Course format: General Ecology (Junior and senior biology and environmental studies majors, does not count towards general education requirements so it is a majors only course). The course had 36 enrolled students. Lab met once a week for three hours.

What I hoped to accomplish with this module was to give students an opportunity to test their own hypotheses about human survivorship, and strengthen their ability to understand survivorship curves.

I introduced the module during a broader unit on population ecology. By the time students were working on this module, we had already covered survivorship curves and basic life table parameters in lecture (Molles 6^th edition, chapter 10). Students had already worked simple, deterministic, problems in class, for example, determining which survivorship curve a population has given l_x values, and given s_x, m_x, and n_x, values predict n_t+1.  I used this module along with the plant population viability analysis module to form a lab unit on populations.  This module is also good for reinforcing the distinction between static and cohort life table approaches.

I have used this module many times, and before that I used this module’s predecessor from the 1993 Experiments to Teach Ecology (Nancy Flood’s Cemetery Demography)

I used example problems, as stated above, and assessed these by using clickers in lecture. I use clickers to provide a low stakes, immediate feedback atmosphere for quantitative work in class (questions are worth participation credit, and all responses receive credit), and we continued working example problems until a significant majority of the class was consistently getting correct answers.  These skills were also assessed on an exam.

I use selected parts of this module, because I want the experience to fit into a single, three-hour, lab session.

1) We do virtual, rather than physical cemeteries.  This is a trade-off, as the physical cemetery opens up nice liberal arts connections to local history and changing trends in funerary art. Further, students always enjoyed the field trip. However, with the physical cemetery, students were constrained to exploring a hypothesis I knew would work with the data they would find there (male vs female and/or 1860s vs 1890s cohorts). We tended to spend the whole three hours collecting data. Switching to virtual cemeteries cuts out travel time and permits students come up with their own hypotheses, and this makes this much more of an open inquiry experience. Since one of my primary objectives for this experience is that students explore hypotheses of their own choosing, the virtual cemetery simply works better.

2) We eliminate the oral presentation.  The Lanza module calls for an oral presentation of the data. This is another trade-off, of course. Oral presentations are important, but at the end of a three-hour session, students would not be ready to do that. Instead, I ask students to submit a more traditional lab report.

Here is the way I run the session.

1) Students break into pairs and come up with a hypothesis. Students clear their hypothesis with me before they begin looking for data, so I can steer them away from hypotheses that are too specific and would therefore take too long to find enough data to address. I also need to steer students away from hypotheses that can’t be addressed using survivorship curves inferred from census or cemetery data.  For example, some students will want to address something very contemporary, like zika virus, and I have to remind them that most of the affected individuals are still alive (so will not be represented in any cemetery) and that the event can’t possibly be represented in the US census. It takes some groups a few tries to come up with a hypothesis that is a good match for their interest and for the technique we want to practice.

2) Students collect data and generate survivorship curves as per the module. Students doing method 1 take longer to collect the data, but usually need less support on the calculations and graphing (steps 7-10). Students doing method 2 tend to find the data they need more quickly, but need lots of support getting through steps 5 and 6 (the calculation of l_x).This is exactly what Lanza predicts in the module.  Most of the middle hour of my class is spent circulating around the computer lab helping students with the analyses.

By the end of the lab session, most groups will have generated survivorship curves and some groups will actually have the lab report ready to submit. Groups that do not leave with their curves finished tend to be groups that did method 2 (the census method) and who really struggled with the calculations.  If I really needed every student to finish the session with graphs in hand, I might be tempted to limit them to method 1 (ages at death). 

For the lab report itself, I ask the following (lab reports in my class are always excel spreadsheets):

1) The names of all group members.

2) (5 points) a brief statement of the hypothesis you are testing and the methods you chose to test it. Why did you choose this hypothesis?

3) (5 points) Tables of the raw data and calculations used to generate graphs. Please put these tables one or more tabs and don’t put them on the main report tab. Name all tabs in the spreadsheet for easy reference.

4) (45 points) Clearly labeled survivorship curves formatted to make it easy to see if your hypothesis is supported by the data. Format your curves as survivorship per 1000, just as Lanza indicates.  You will probably find it useful to plot your curves on the same set of axes so you can see differences in the curves.

5) (40 points) Do the data support your hypothesis?  We are not using a statistical test to answer this question, but make careful reference to the figures you generated in item 4 to justify your answer.  What historical trends or events may explain any observed difference or lack of difference? You do NOT need to answer questions 1-9 in the Lanza article. However, these questions (especially 1-8) will give you some good ideas to consider as you try to explain the trends in your graph or graphs).

6) (5 points) A bibliography of any data sources consulted or references used.

This module works very well for me. While I am still not totally at peace about abandoning the physical cemetery work, I do feel that the trade-off in favor of more open inquiry for students is worth it.   I anticipate continuing to use this module. Students are often surprised by the outcomes. For example, one group this year compared survivorship in urban Chicago vs a more rural area in downstate Illinois for individuals born in the 1890s. They assumed that urban would beat rural due to access to healthcare, but were astounded to find a large difference in the other direction. This prompted a good discussion on public health, the industrial revolution, and student’s assumptions about the costs and benefits of different lifestyles.  Another group compared survivorship from a Mexican cemetery to a Californian one from the same era. The students correctly predicted higher Californian survivorship, but were surprised how large the observed difference was. Again, this was a springboard for a good discussion about public health trends and social justice.  Of all the labs I do, this one connects most easily and fully to the larger liberal arts context of the school.