One common criticism of automated "Skinner-box"-like teaching machines (e.g. in Watters's book) is that they're fascistic, inhumane, etc. In the context of K-12, that's definitely true, but I think the stronger criticism is that they don't really *work*, even on their own terms!
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That is, even if a student mechanically does exactly what the Skinner box (or Khan Academy exercises) asks them to do, the resulting understanding is usually brittle, shallow, and short-lived. *Also* the experience is often awful, but that seems unimportant if it doesn't work!
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It's funny—when I was working on K12 edu, what really bothered me about teaching machines was the fascistic, anti-creative bit.
Now that I'm working on expert learning, I have a different perspective: if such a machine truly worked, I'd *love* to use one for topics I care about.
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The voluntarism makes all the difference for me. In the context of a coercive learning environment, the *affect* of the teaching machines really bother me; but if I'm just trying to efficiently learn topics I need for projects that matter to me, then sure—whatever works best!
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Questions I'd like to understand better:
Intelligent tutoring systems seem to produce more flexible, durable understanding. Is this true? If so, what differences from a Skinner-style machine make it so?
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I can't get my head around Direct Instruction. The Follow Through studies are hard to argue with, but it sure seems like a teaching machine to me. Does it produce more flexible, durable understanding than? If so, why? The teacher's human involvement, even if scripted?
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The teacher can do it well, or poorly. But my answer: the DI scripts are incredible works of engineering. They explain the outcome of Follow Through.
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