The best way to improve one's teaching is to work with a coach who knows what they're doing. I coach young faculty on how to split up lecture and activity so that both benefit. The sole secret towards high evals. is returning graded work quickly. I don't worry about them.
I personally experienced terrible comments early in my career at @UCIrvine comments on my looks. How I acted like I knew a lot. Worse was administration refusing to acknowledge deep biases in systemhttps://twitter.com/random_walker/status/1209296824089141248 …
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On the remark of high evals, maybe this is just because of where I did my undergrad/what I did it in (pure math at Waterloo), I noticed that if you cannot return the assignments quickly then a good alternative to maintain high evals is to be lax on student deadlines
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I wish You a wonderful Christmas
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I didn't know you were an Anteater.
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Yes. Our annual evaluation and raises still use student results despite plenty of research showing how biased it is for women and other minorities in science. Admin acknowledges but nothing changes.
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So sorry this happened, we really need to change the frameworks with which students think.
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As someone just starting out my career in ML, I’ve been jumping through the same hoops and trying to work through how we can change these problems from within. So many biases that go hidden with zero acknowledgement.
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