The module and supplements were implemented at McPherson College the by Jonathan Frye, PhD.
- Course: BI 310 Statistical Data Analysis
- Course Level: Upper-level natural science majors
- Instructional Setting: Lecture/Lab (Students using computers in the classroom, collaborating synchronously)
- Implementation Timeframe: The course met for two two-hour-long blocks per week. The module occupied 3 class sessions in March and April, with a presentation on Monday May 1st (last week of classes). Some homework (i.e. outside of scheduled class time) was required to complete the data analyses.
- I distributed the TIEE Climate Change in the 21st Century materials without modification to the students in BI 310 Statistical Data Analysis, including the data sets from 7 different latitudes along the North American transect, from 18°N to 68°N. We discussed, but did not work through the details of the seasonal trend analyses outlined in the exercises.
- The next time that I use this module I will use approximately the same pacing - working through the analysis and presentation of the data over the course of the semester - as well as same objectives for the BI310 Statistical Data Analysis class. Although the TIEE materials provided a context for working on the concepts and skills that were already a part of BI310, I did not provide my students with a separate evaluation rubric for this module as a part of their course. Instead, I shared with them out the outset that I was experimenting with the course, and that my educational experiment would not have any negative consequences for them so long as they participated in good faith. I have found that the goodwill generated by relieving a bit of grade anxiety goes a long way to sustaining the kind of positive and collaborative environment that characterizes the most fruitful of scientific research groups.
- Also, the next time that I use this module we will begin by going to the Canadian Centre for Climate Modeling and Analysis website (http://www.cccma.ec.gc.ca/data/data.shtml) to download and reformat the data sets ourselves. Accessing existing data sets for analysis is an additional skill that this module could help me introduce to my students.
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