That should likewise account for variations in rate of learning, since you can't predict what prior knowledge they possess of the subject matter.

If the rate is consistent, there must be more than existing knowledge bases, or there would be clear staggered tiers or leapfrogging reflecting different accumulative advantage.

Agree with this, the data is consistent with small, additive, effects of learning over time. (And those additive effects don't show much variance between students, at least for these short courses.)

I have a pet theory in general for noisy social science data -- the best we can do is often find additive effects (there is a boutique subset of social science showing "simple models" do almost just as well as more complicated machine learning models).

Here there is variance in each of the test stages, maybe I am guessing standard deviation of 5 percent points within person (e.g. if you could have a person retake the entry exam, one time 65, another time 70, another 60, etc. would not surprise me). The variance likely swamps any ability to identify different rates of growth over the shorter course period. (Also for course instruments, truncation of 100% makes it more difficult as well.)

Just a pet theory anyway!

"Prior knowledge" is a strange way to write IQ.

IQ has barely anything to do with learning.

???? Smarter people require less exposure to the same concept to "get it". You might actually just be lying and there is no reason for me to engage.

They can understand faster. But not learn (remember) faster.

I think higher IQ people might in some cases learn faster because if they understand the thing they are trying to remember, they can "replay it" in their heads bumping up the number of exposures which might help remembering. But not everyone with high IQ does that.

Learning isn't just remembering, it's also reflective of skills. Someone with considerably higher IQ can arguably understand how to program computers faster, and thus start writing programs on their own sooner. Would we not say they learned programming faster?

The real difference appears to be they simply cover more ground in aggregate over the long run on their own steam because their physiology makes it calorically cheaper for them to do so compared to their peers.

IQ seems to correlate most strongly with working memory, though ones capacity for working memory doesn't seem to have much bearing on the mechanism behind the formation of new memories themselves. Building semantic memory requires repeated exposure.

What really matters is the rate at which the individual exposes themselves to learning opportunities. This appears to be a function of how rewarding it is to you, how expensive it is for you, and how much (or in some cases little) executive control you have.

> Building semantic memory requires repeated exposure.

I think the point of this research is that this requirement is pretty consistent in humans regardless of their other capacities or prior knowledge.

Yes, that's my understanding of what this research says too.

Reading through all the comments I can see a lot of people struggling to reconcile this result with their existing mental models of intelligence and learning.

> Smarter people require less exposure to the same concept to "get it".

Or not.

I'm been labeled gifted my whole life and typically require much more exposure to concepts, in order to catch up to most folks. The gifted part comes in with what I can do once I reach their level.

Think of a skill where 'a' is an entry-level understanding, 'c' is average and 'e' is exceptional.

Most people transition easily, hitting a then b then c. Past that is harder and most don't go there.

For me to get to b, I have to learn a.1-a.100. To get to c it's b.1-b.100 (hopefully faster).

By the time I get to c, I'm far, far behind everyone else. However, my much broader understanding of a, b & c can make the hop to d & e trivial for me.