My teaching centers on instructing students how to use spatial data science methods to describe and analyze dimensions of global human development and the subsequent process of communicating those results from their research. My teaching emphasizes reproducible methods that use open source, interpretative programming languages such as R, SQL, LaTeX and HTML. Following are two College Courses I am currently teaching at William & Mary.
This course is a writing seminar that introduces students to the process of writing about their research. Each student is guided in their choice of topic on a dimension of global human development and then investigates that topic both broadly and in terms of an applicable data science method. The semester is structured around the process of writing for publication as part of a research team, beginning with an annotated bibliography, literature review, general topic paper, specific inquiry paper and the final research paper. The course concludes with a colloquium that offers each student an opportunity to present their work in a public forum and a journal that binds the results from the semester into a single publication. Please see the Colloquium tab for our results from this Spring.
This is primarily a computer laboratory based course that also includes weekly guest lectures from William & Mary faculty who have research interests that incorporate data science methods. Laboratory assignments introduce students to data science fundamentals including spatial, temporal and probabilistic methods and applications. While this course is not necessarily focused on dimensions of global human development, many of the laboratory exercises have a very development centric focus. Following are a few of the laboratory excercises from the course.