I would like to be a better teacher than I am, which largely means teaching undergrads. Here is where I will make notes about that.
Maybe I should read Little Soldiers – Inside the Chinese Education System.
Orr Shalit rants about data-driven teaching methods: Why a “scientific approach” to science education is something I reject. This is worth reading because I enjoyed disagreeing with it as much asI took away some good ideas.
I claim that teaching — like making a scrambled eggs or kissing or riding a bicycle — is an activity that humans can do very well without the pretence of approaching it scientifically.
For the record, some of my favourite science about bikes is blogged here and my favourite egg-scrambling research is at J. Kenji López-Alt’s Food Lab. I am currently not familiar with published studies on kissing but I can recommend field research.
In order to reject certain movement in teaching reform, Orr takes some contentious positions about science, which if I understand them correctly, include that
- contemporary machine learning is not science (because it is engineering, which is not science)
- that social sciences is largely impossible, (In particular, science education research, it seems, by definition, cannot be science) and indeed
- evidence-driven statistical research should not generally be referred to as science unless it meets some specific but unarticulated criteria. These are not incoherent stances, but they are definitely abnormal usages. Fortunately, he permits you to use data-led, logical, peer-reviewed argument to improve systems, as long as you describe that approach as something other than science-based.
Idiosyncratic definitions aside, some things he says are worth bearing in mind. He defends the idea that traditional methods are not pointless, observers that scientific consensus can be faddish, that incrementalism can be an OK way of improving a thing, that it is complicated to map from coal-face evidence to the overall design of human systems, that human dignity is a real concern and that the weight of evidence is often weak in social research.