

The Netflix Effect: When Software Suggests Students' Courses - missn
http://chronicle.com/article/The-Netflix-Effect-When/127059

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caryme
One of my professors just mentioned the other day that some CS grad students
built a course suggestion engine. It apparently worked - all they needed was
the cooperation of the registrar's office to incorporate students' course
history.

The registrar refused.

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zck
This would require a lot of work to not violate FERPA, which is a federal law
preventing educational records -- such as course history -- from being
disclosed without consent from the student.

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rb2k_
Even without knowledge of previous performance, computer-assisted course
selection can be great.

A friend of mine implemented a genetic algorithm (in Javascript) that mutated
possible timetables until it seemingly found the best combination of your
chosen criteria. You could select things like "I like Professor X", "I don't
want to have lectures on wednesday", "I don't want to get up before 9" and
give the algorithm incentives/disincentives for specific lectures.

Worked remarkably well.

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shadowsun7
Any chance of making the script open source? I'd love to give it a try for my
classes.

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rb2k_
I'll have to see if I can reconnect with him

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Joakal
Course suggestion engines are pretty easy to start with due to limited choices
and mandatory paths in programs. In fact I implemented something akin to this
as part of a university assignment.

The tool was actually meant to be provided for course coordinators to estimate
number of students who are likely to take the course in next semester and
sometimes as far as the length of a normal program.

Post-release, maybe past peer history could be used for accuracy. It would not
solve the volatile nature of new courses though.

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missn
That would be awesome to have in our school.

All the apps people are making here seem to be confined to course scheduling
(whether something conflicts, etc.) or courses we need to graduate. They
haven't actually gone into the realm of recommending possible courses we'd be
willing to take.

As the article mentions, the schools have all these data they're not using.
They can probably predict which students would succeed in courses (they have
access to grades), know which similar courses students may be interested in
(cross-reference with previous courses taken and see what others have taken
with a similar plate) and even "learn" the scheduling habits of the student
(see the previous class times the person usually chose for clases - i.e. a
morning person scheduling all classes in the morning or someone scheduling all
classes at night).

As long as we still have a choice (to accept or reject the recommendation),
something like this would be useful (another resource to inform our
decisions).

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Groxx
Computer-generated suggestions seem likely to me to be "the future". They're
getting to be easy to implement, so I doubt it'll be long before they're
literally everywhere, and we get used to computers being creepily accurate at
predicting what we want.

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dfield
Interesting to see others doing this. I'm working on a similar project at
Brown right now with a few friends. We're lucky - the Registrar's office
agreed to give us anonymized data to bootstrap our recommendation system.

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voidnothings
This should be interesting, current course ladders right now are too rigid or
very limiting to exactly curate a student's academic career. While it has it
its downsides, this would be an experiment worth watching.

