I recently enrolled in the University’s MA in Academic Practice programme to learn about well, learning and teaching. I am keen to enhance and improve my teaching using the latest technology available as well insights that learning theory can give.
So I entered the world where humanism and meta cognitive theory (and many others) are approaches within the context of which learning is looked at. How do these frameworks impact teaching design, curriculum, learning, assessment and so much more.
Perhaps it is this interest that has led me to noticing more articles about teaching or maybe more people are writing about it in STEM, I do not know.
In a recent issue of Physics World devoted to eduation, many articles addressed making Physics more interesting to young students (ages 5-16), designing curriculum with this in mind; about educating or informing general audiences about Physics using Youtube.
In other posts I have mentioned Just in Time teaching and topdown approaches to teaching that some people advocate: talk about a big problem (how does you recognise a picture?) that interest students and then breaks them down level by level to get them to the concepts they have to learn in the class/module. This keeps more students engaged than the regular approach of bottom up..
I am yet to find an article/theory/approach about effectively teaching mathematical content (within Physics for example) at university level. My class has a large distribution in terms of both interest and ability in Mathematics: some students enjoy it and are adept while others find math difficult and scary. The challenge is how to engage and develop the ability of the weaker students. In my view (everyone may not agree) it is difficult to go to a higher level in Physics without being able to do Mathematics.
If you have any ideas on how to solve this puzzle get in touch!
1. Anderson, T (ed), Elloumi, F (ed). (2004) Theory and Practice of Online Learning.
2. Miller, G. A. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review, 63, 81-97