Agenda

1. Lab 04: Modelling course evaluations
2. Getting started with lab

Lab 06: Modelling course evaluations

• Many college courses give students the opportunity to evaluate the course and the instructor anonymously

• The use of these student evaluations as an indicator of course quality and teaching effectiveness is often criticized because these measures may reflect the influence of non-teaching related characteristics, e.g. the physical appearance of the instructor

You’ve all seen something like this…

and then there’s also this

Data comes from…

“Beauty in the classroom: instructors’ pulchritude and putative pedagogical productivity”

Daniel S. Hamermesh, Amy Parker, Beauty in the classroom: instructors pulchritude and putative pedagogical productivity, Economics of Education Review, Volume 24, Issue 4, August 2005. http://www.sciencedirect.com/science/article/pii/S0272775704001165

Some new challenges in this lab

• There isn’t much code on the lab instructions, you might need to refer to course slides to put the pieces together, however most of the time
  • you’ll be visualizing with ggplot,
  • fitting a model with lm,
  • and viewing some model statistics with glance
• Interpretation in the context of the data matters
  • Numbers need context: saying (for example) “the \(\beta_1\) is 5” isn’t enough; what does that mean? In particular, what does that mean for these data and for this question