I teach statistics, data science, and statistical programming at Utrecht University. I also give workshops on these subjects.
Teaching is great! I’ve been doing some form of teaching since my days as a bachelor student, and teaching makes up the majority of my duties in my current position at Utrecht University (UU). Of course, teaching has obvious altruistic benefits such as improving society by educating the citizenry and “paying forward” all of the energy my own teachers and mentors put into training me. In addition to these noble motivations, however, teaching also has plenty of more self-serving benefits to appeal to those of us who may lean more toward the anti-social side of the spectrum.
For example, teaching is great way to get new research ideas. If my students repeatedly ask interesting questions for which the literature has no answers, then I know there’s probably demand for research on that topic. Depending on the teaching context, I may even be able to recruit the curious students as collaborators. If I take a broader view, I recognize that I am educating the people who will shape the world in which I will grow old. So, it certainly behooves me to train my students as well as possible. I’m counting on these folks to make the future a nice place to be.
One of my favorite benefits of teaching, though, is its effect on my own learning. Like most academics, I’m eternally curious and always eager to learn new things. I suppose I stuck around academia after graduate school largely because I wasn’t ready to give up on being a student. I’m rarely satisfied with using a tool that “just works”; I want to know how and why the tool works, and teaching is an excellent way to facilitate this kind of deep learning. In my experience, the best way to master a subject is to put yourself in a position where you must teach that subject to others. In this sense, I completely agree with the sentiment variously attributed to Albert Einstein, Richard Feynman, and Ernest Rutherford:
You do not really understand something unless you can explain it to your grandmother.
All things considered, if we’re meant to leave the world a better place than we found it (which seems like a pretty good goal to me), then devoting a considerable portion of my energy to education seems like a good use of the limited time I have to hang out on this planet.
I first dipped my toe in the teaching waters by tutoring statistics as a bachelor student. In graduate school, I worked as a teaching assistant in the statistics courses given by the University of Kansas Quantitative Psychology Program. During that time, I also taught short seminars on missing data and worked as a teaching assistant for the Stats Camp workshop series run by YHat Enterprises.
During my postdoc at Texas Tech University, I developed and taught my first full-scale courses. These master-level courses covered missing data analysis, Monte Carlo simulation methods, and conditional process analysis. I went on to teach statistics and data science courses to bachelor students in the Psychological Methods and Data Science major and master students in the Data Science and Society program during my first faculty appointment as an assistant professor at Tilburg University.
I now teach courses on statistics, data science, and statistical programming in the Applied Data Science program and various master and bachelor programs of the Faculty of Social and Behavioural Sciences at UU. I also teach in the Utrecht Summer School, and give workshops for UU students and staff.
Here is a list of the UU courses in which I am currently involved:
- Elective Statistical analysis with R
- Programming with R
- ADS: Fundamental techniques in data science with R
- Missing Data Theory and Causal Effects
- Advanced Research Methods and Statistics for Psychology: