teaching

My educational statement is two-fold, teaching students to:

  • Build on fundamental concepts, in both theory and practice, to critically rethink what is taken for granted, design tests, analyze results, come up with creative solutions and validate them;
  • Take the responsibility to engage their surroundings while handling the inherent uncertainty in doing research.

You can find these reflected in my guidelines.

I aim to teach students, even if they do not show strong intrisic motivation. One tool for that is activating students in the lectures through a Socratic Q&A. This contrasts from the typical lecture style which are to ‘broadcast’ knowledge. When broadcasting, the students often feel they learned more, but they actually learned less, because students are not forced to reproduce the knowledge. Reproducing the knowledge can be deferred to labs or to assignments, but, in my opinion, this only reaches the students who have the intrinsic motivation, but less the students who have difficulty with motivation. My lectures aim to teach something, whether students like to, or not :grin:.

My lecture style therefore is extremely interactive, where I adopt the Socratic style of asking many questions during a lecture. I stucture the questions such that they follow the narrative. I refuse to continue before my questions are answered; and I take care to not always have the same students answering the questions.

Similarly, I do not believe in excluding unmotivated students who might not have remembered all concepts from their previous courses. Of course, there must be some basis, but I find that it’s easy to just add 1 line to the slides to ask the class to plenary explain a concept from a previous course instead of assuming everyone knows, eg, the multi-variate chain rule, or what a Jabobian is, etc. In the worst case, we lose a few minutes, but in the best case, I get to keep some students engaged, whom I otherwise would have lost. I believe that this inclusive style of teaching makes education more broadly accessible.

Lecture slides

Deep Learning

Here are my slides for the Deep Learning part of the Machine and Deep Learning course at TU Delft.