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I've been considering making spaced repetition software to help reteach and remind me of technical concepts I've learned over college that I don't recall too we

I've been considering making spaced repetition software to help reteach and remind me of technical concepts I've learned over college that I don't recall too well. Stuff like fluid mechanics, microelectronics, thermodynamics, control systems, complex analysis, computer architecture, etc. Basically I have access to a lot of relevant course notes I took over the years (and digitized), but I don't remember it, so I would use SRS on this material to relearn it. I was thinking 20 mins a day would be a good amount of time for this. But wait, let's take a step back. Does it really matter if I can recall all this engineering material? Supposedly my brain "knows" enough of it such that if there were a big project in a field requiring that knowledge, then I could relearn it all, because I've been trained to think in a way pertinent to that material. Is my time better spent just learning new topics and building things, which is what I currently do? Why dwell on having perfect recall? It only seems to benefit test takers. I would love to hear counter-arguments for why SRS for engineering materials would be a good idea for those no longer in school, maybe then I'll be motivated to build some gamified spaced repetition software. It'll need to be fun and reward-based, imo.

cicatriz 13y ago
I've been thinking about this for a while--I created a spaced repetition system to digitize and learn material in college (alas, I don't use it anymore). I have a philosophical approach to the question here (also cited in Gwern's article): http://blog.learnstream.org/2012/08/spaced-repetition-in-natural-and-artificial-learning/ http://blog.learnstream.org/2012/08/spaced-repetition-in-nat... Your distinction between learning facts and learning ways of thinking is interesting. Most of the spaced repetition research and design is around fact recall--what's called "paired associates" because you recall some response paired with some stimulus. I don't have any evidence for it, but I'd say that the schema can be lost just as well as facts can be. One thing I will say is that spaced repetition is generally known for the repetition--that you retain something over time, and the spacing is more thought of as convenience. But the truth is that spacing is also part of better learning--when recall is difficult it's learned better (called "desirable difficulties"). I thought of that because Robert Bjork does that research with skills as well as facts. (See http://www.wired.com/geekdad/2012/01/everything-about-learning/ http://www.wired.com/geekdad/2012/01/everything-about-learni... for an overview.)
- zxcvvcxz 13y ago
  Yes it's not obvious to me how to impart knowledge in a SRS format that's more than fact recall. I was thinking of starting with thermodynamics because it's one of the more straight-forward equation courses - but then how do you properly do problem solving? I suppose if you walk through a problem broken up into enough chunks phrased as questions, and somehow give users a toolbox from which to choose equations from, it might work.
  - cicatriz 13y ago
    Not sure how deep down the rabbit hole you want to go, but here's what I know: The field of intelligent tutoring systems is essentially how to break up a problem and estimate your knowledge on each piece (called a "knowledge component"), and then how to instruct based on the resulting student model. I got started by reading about Andes physics tutor: http://oli.cmu.edu/wp-oli/wp-content/uploads/2012/05/VanLehn_2005_Andes_Physics_Tutoring_System.pdf http://oli.cmu.edu/wp-oli/wp-content/uploads/2012/05/VanLehn... but there are many examples. Most of the research doesn't actually incorporate spaced repetition. One exception is Philip Pavlik's work: http://optimallearning.org/ http://optimallearning.org/ It's still a lot of effort to break things down into knowledge components and figure out the sequencing and instruction. That's why companies like Carnegie Learning and Knewton exist, and even those are only targeting elementary or intro level material for now.
dwc 13y ago
Whether you should use SRS for any given domain is completely dependent on your specific circumstances. The answer could easily be different for you and a classmate of yours who fits the description above. But I'd say that if there's some are you'd like to work in that requires specific knowledge that fits well within SRS, why would you not? As opposed to trying to learn and recall anything that might possibly be useful, ever.

cicatriz 13y ago

I've been thinking about this for a while--I created a spaced repetition system to digitize and learn material in college (alas, I don't use it anymore). I have a philosophical approach to the question here (also cited in Gwern's article): http://blog.learnstream.org/2012/08/spaced-repetition-in-natural-and-artificial-learning/ http://blog.learnstream.org/2012/08/spaced-repetition-in-nat... Your distinction between learning facts and learning ways of thinking is interesting. Most of the spaced repetition research and design is around fact recall--what's called "paired associates" because you recall some response paired with some stimulus. I don't have any evidence for it, but I'd say that the schema can be lost just as well as facts can be. One thing I will say is that spaced repetition is generally known for the repetition--that you retain something over time, and the spacing is more thought of as convenience. But the truth is that spacing is also part of better learning--when recall is difficult it's learned better (called "desirable difficulties"). I thought of that because Robert Bjork does that research with skills as well as facts. (See http://www.wired.com/geekdad/2012/01/everything-about-learning/ http://www.wired.com/geekdad/2012/01/everything-about-learni... for an overview.)

zxcvvcxz 13y ago
Yes it's not obvious to me how to impart knowledge in a SRS format that's more than fact recall. I was thinking of starting with thermodynamics because it's one of the more straight-forward equation courses - but then how do you properly do problem solving? I suppose if you walk through a problem broken up into enough chunks phrased as questions, and somehow give users a toolbox from which to choose equations from, it might work.
- cicatriz 13y ago
  Not sure how deep down the rabbit hole you want to go, but here's what I know: The field of intelligent tutoring systems is essentially how to break up a problem and estimate your knowledge on each piece (called a "knowledge component"), and then how to instruct based on the resulting student model. I got started by reading about Andes physics tutor: http://oli.cmu.edu/wp-oli/wp-content/uploads/2012/05/VanLehn_2005_Andes_Physics_Tutoring_System.pdf http://oli.cmu.edu/wp-oli/wp-content/uploads/2012/05/VanLehn... but there are many examples. Most of the research doesn't actually incorporate spaced repetition. One exception is Philip Pavlik's work: http://optimallearning.org/ http://optimallearning.org/ It's still a lot of effort to break things down into knowledge components and figure out the sequencing and instruction. That's why companies like Carnegie Learning and Knewton exist, and even those are only targeting elementary or intro level material for now.

dwc 13y ago

Whether you should use SRS for any given domain is completely dependent on your specific circumstances. The answer could easily be different for you and a classmate of yours who fits the description above. But I'd say that if there's some are you'd like to work in that requires specific knowledge that fits well within SRS, why would you not? As opposed to trying to learn and recall anything that might possibly be useful, ever.