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This is just so simplistic. I'm surprised it comes from MIT. The idea that students pick songs and not albums seems a silly analogy to coursework. The use of MOOCs as evidence of anything seems very thin. I'm sure many students report that they only studied the parts they were interested in of a course rather than 1) they did not have the time to devote, 2) had some free time but did not take it as seriously, 3) it was hard an gave up, or just that maybe the student genuinely only interested in learning the pumping lemma but not much more about push down automata; however I'm not sure that sort of cherry picking does a college education make.

We can talk about costs and all of this kind of thing but I feel like we dumb down higher education because it seems hip (like picking songs for your iPod because we are all have hyper attention deficits, or something).




the very concept of structured courses in education is because we don't know what to study to understand XXX things.When it comes from a teacher , it comes with a dependency graph drawn by a person who knows the course.If proper knowledge gathering is considered an objective.This dependency is a natural consequence of subject-matter than an optional one .

For e.g. for someone to learn abstract algebra ,its highly suggested that they take up linear algebra first.As for me, i've always the dependency graph quite seriously .May be the gifted brains can leave linear algebra and directly take up abstract algebra , is that so?


I'm not sure about abstract algebra specifically, but in other subjects that I have tried to take up on my own, I have found that the dependencies become obvious once you realize you are in over your head. In fact, my preferred method of learning these days is to start with your goal, then traverse that so-called dependency graph to the dependent, and often simpler, concepts until you are able to work your way back to your original goal again.


This is a nice way of priming your mind for the concepts you're interested in--and is probably another example of why the current educational system languishes under standardized testing for metrics: when the goal isn't in the students' direct interest, the system can only provide an indirect benefit for their minds. It's very inefficient.

The class structure has grown out of the physical limitations of presenting course information to mass groups of people in physical classrooms. Take the MIT Modules, make them asynchronous and add accountability (limitations and commitments: something like, only 5 active modules at a time until you've completed them) and mentoring (which is your next module? If you struggled with X, maybe you should go back a couple dependencies?) and you could have a really effective system that creates even more amazing people--at the pace that suits them best.


They do not suggest that dependencies are ignored. Not everything in sequentially dependant. And sometimes some material may apply to multiple courses. The idea is to break things out so they can create the dependency graph and take advantage of places where there actually aren't dependencies or know for sure when there are.


I think you're taking this the wrong way. Ideally, most of what I've learned could be used under different scenarios. I mean, you can learn programming to hack music, understand data or create an intelligence to do some of your work for you. There are different applications, and everyone has a different end goal in mind.

If you allow for this kind of modularity, it allows people to adapt their courses to what they want to make in the end.

With regards to the pumping lemma or the master theorem, the point is, no one is forcing people _not_ to learn bout these concepts. However, people should have the right to choose what they learn to meet their own goals. If you can't make an informed decision by the time you're at college regarding what you need to study or what's important, then you need to think long and hard since life's about making decisions like this.

I mean, I had a choice to take automata theory. I did so, because I wanted a better understanding of how computation originated. I'm pretty sure others would be interested as well.


It's not that simplistic, data from MOOCs shows that short MOOCs (3-4 weeks) do better than long MOOCs (> 4 weeks), probably it's because the attention wains and there need to be other incentives for people to continue.




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