Teaching First-Year College Students Research Skills using MATLAB: Examples from Remote Sensing and Meteorology

Abstract:

We discuss the painstaking but rewarding experience of teaching college freshers Science with a capital S. For the students this meant: instrumental data collection, hypothesis formulation, code writing, problem solving, and how to overcome frustration with a computer language (MATLAB) that is new to all of them---with some students never having programmed in their short lives. For the instructors: staying one lecture ahead, developing just-in-time modules that provide enough of a framework for the students to continue to learn, but not so much that it's all handed to them on a silver platter---and more grey hairs coming out of it than going into the semester. Our 2019 Freshman Seminar Crops, Culture, and Climate (in Italy) devoted the first six weeks to developing computational core skills, centered around the analysis of meteorological time series (from MeteoBlue), of high-resolution digital elevation models (from Tinitaly), and of multispectral remote-sensing imagery (from RapidEye/Planet). Each student took the lead in the analysis of a specific olive-growing region in Italy. Over Fall Break, the group traveled to Italy for ground-truthed analyses of a specific subset of olive groves: they set up a local weather station, performed a tree census, tree coring, soil analysis, and developed a drone-derived digital elevation model and multispectral map. After the trip, the second six weeks of instruction were spent analyzing the data and developing research hypotheses for an individual final paper finalized in the last three weeks of the course. We will show and discuss examples of instructors' pedagogical preparation and students' work, and point to the relevant archives containing our data products, analyses and code bases, such that these novel materials can be reused by teachers-researchers wherever they may coach students---from the beginning students (all of ours in Week 1) to the more experienced ones (some of ours in Week 15).