Teaching Econometrics Dynamically with R-Shiny
By Shawna K. Metzger, Michigan State University
Teaching is a constrained optimization problem. There are numerous topics that we could cover in a given class, and for each of those topics, there are varying levels of depth at which we could discuss them. However, we have a finite amount of contact time with the students to do so. How should we allocate that time to give students the best chance of learning the content?
Methods courses feel the time pressure in a particularly acute way. For substantive courses in political science, preexisting knowledge about history or civics is useful but not necessary. Most of the knowledge we construct for our students in these courses comprises new information that requires minimal background knowledge for comprehension on the students’ part. Contrast this with methods courses, in which the knowledge we construct for our students requires a basic grasp of algebra, at the least, if not also a minimal understanding of research design from coursework in the natural sciences and a vague recollection of probability and statistics. With time being at such a premium, how might we raise our teaching effectiveness such that students internalize more information per minute of instruction?