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by aryzach
2283 days ago
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Appropriate assignments. For me, that often makes or breaks a MOOC. I want to be stumped in an intellectual way, but not a cryptic way. I don't want to feel like I'm just trying to decode the professors cryptic problem. I want to feel like it's a genuine hurdle to learn the content well, yet still accessible, and definitely not busy work. Good example: write an interpreter for the given (made up and simple) programming language. We had to figure out how to implement certain language features such as clojures. Bad example: in networking course, we had to recall details about certain protocols, and do calculations. While this might be useful to know how to do in practice, it didn't contribute anything to my understanding, and it just always felt like tedious busy work, and lacked projects that contributed to the course goals. I don't know data science, but here's a project I've heard of:
Somebody's hobby was disc golf. Discs come with ratings on them (I'm assuming things like curve and distance). They created a controlled experiment to take various data points from many discs, and compare them to their stated ratings, and apply a bunch of data science-y things to the data. Edit: I'd add some type of reference resources like a wiki, and ideally some auto-grader that gives feedback if possible (like what tests failed) |
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