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Conversational dialogue seems like a fascinating distraction. Many people who have (unsuccessfully) attempted to apply AI to education have focused too much on
by JustinSkycak 2y ago
Conversational dialogue seems like a fascinating distraction.
Many people who have (unsuccessfully) attempted to apply AI to education have focused too much on the "explanation" part and not enough on scaffolding, navigating, and managing the entire learning process. It’s easy to go on a wild goose chase building an explanation AI.
You fall in love with the idea of AI having conversational dialogue with students, and then you get lost in the weeds of complexity. You solve just enough of the problem to produce a cool demo, yet you're still hopelessly far away from self-service learning in real life.
I don't think conversational dialogue is even necessary.
What we do at mathacademy.com is hard-code explanations and break them up into bite-size pieces that are served at just the right moment. And we close the feedback loop by having students solve problems, which they need to do anyway. (The student's "response" is whether they got the problem correct.)
Sure, hard-coding explanations feels tedious, takes a lot of work, and isn't "sexy" like an AI that generates responses from scratch – but at least it's not a pipe dream. It's a practical solution that lets us move on to other components of the AI that are just as important.
What are those other components? A handful off the top of my head:
* After a minimum effective dose of explanation, the AI needs to switch over to active problem-solving. Students should begin with simple cases and then climb up the ladder of difficulty, covering all cases that they could reasonably be expected to solve on a future assessment.
* Assessments should be frequent and broad in coverage, and students should be assigned personalized remedial reviews based on what they answered incorrectly.
* Students should progress through the curriculum in a personalized mastery-based manner, only being presented with new topics when they have (as individuals, not just as a group) demonstrated mastery of the prerequisite material.
* After a student has learned a topic, they should periodically review it using spaced repetition, a systematic way of reviewing previously-learned material to retain it indefinitely into the future.
* If a student ever struggles, the system should not lower the bar for success on the learning task (e.g., by giving away hints). Rather, it should strengthen a student’s area of weakness so that they can clear the bar fully and independently on their next attempt.
- JustinSkycak 2y agoShould mention that I recently wrote an essay that elaborates on this argument with plenty more detail: https://www.justinmath.com/the-situation-with-ai-in-education/ https://www.justinmath.com/the-situation-with-ai-in-educatio...
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- chongli 2y agoI find myself endlessly frustrated by these discussions around the teaching of mathematics. People seem to want to make it more conversational, more interactive, more engaging. It doesn't work that way! Learning mathematics is like learning to play a musical instrument. No amount of 1-on-1 discussion with a teacher will get you to mastery. You just need to practice. For hours and hours and hours. The teacher's job is to help guide you to what you might want to study next. The teacher cannot replace individual practice time.
- BaculumMeumEst 2y agoReally? I struggled with calc in school because lectures were dry proofs (without ever formally teaching how proofs work!!) and then they just told us to read the textbook. Then I found mit ocw and ripped through the material because it was much more engaging. Never would have passed calc I-III, linear algebra, and diff eq without those lecture recordings.
- RugnirViking 2y agoIt's a sad fact that teachers are often not very good. This often has to do with the fact that they do not know what you already know, and proscribe inappropriate things for you to try next. You struggled in school, it seems, because you had a teacher very focused on proofs and you never learned proofs. This is a common problem I find in mathematics, where someone never learned one key element, and struggles to pin down why everything is so difficult for them. For many people, it can be calculus, or linear algebra, or bayeseian statistics, or fourier transforms, to name a few topics myself and people I know have had aha moments in when they finally learned.
- JustinSkycak 2y ago> This is a common problem I find in mathematics, where someone never learned one key element, and struggles to pin down why everything is so difficult for them. Reminds me of Ben Orlin's "law of the broken futon": a single missing part can, over time, warp an entire futon and render it unusable. https://horizonsaftermath.blogspot.com/2016/02/the-law-of-broken-futon.html https://horizonsaftermath.blogspot.com/2016/02/the-law-of-br...
- jasfi 2y agoAs long as there are enough people working on this problem, I don't mind how many approaches there are. Education systems around the world just aren't good enough.
- cwoolfe 2y agoHard-coding explanations does seem like the way to go here. It's what researchers at Carnegie Mellon did back in 1984 with demonstrated success. See: Intelligent tutoring Systems: The ACT Project https://www.youtube.com/watch?v=boDH_pW14B0 https://www.youtube.com/watch?v=boDH_pW14B0 My question is, if we've had intelligent math tutoring demonstrating success in real classrooms since 1984, then why haven't we been actually using them to help teach math?
- JustinSkycak 2y agoI don't know enough about the ACT Project to make any hard claims regarding why it didn't go mainstream, but I imagine one big source of friction was that students didn't have their own school-issued Chromebooks like is so common nowadays. Remember that in 1984, computers were way, way more expensive than they are now.