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This is a good example of why it's important to recognize the difference between individual anecdotal experience and results gained from properly analyzing data

This is a good example of why it's important to recognize the difference between individual anecdotal experience and results gained from properly analyzing data. It's rare for people to make enormous improvements or experience enormous depredations in performance one experience to the next. It's common for natural variations due to random factors, especially when still learning, to crop up and impact performance from instance to instance. That's true whether one is shooting a basketball at a net or flying a jet aircraft. This means that quite often the experience of providing negative feedback will seem to result in improvement. But this is also true if one simply were to secretly write their negative feedback down, put it in a letter, and never show it to the student. Due to the regression to the mean effect. Students who do poorly in one round will often do better in the next, just as students who do well in one round will often do slightly worse in the next. Only over a longer period of time and collecting data from multiple students will you balance out these effects and be able to determine whether positive or negative re-enforcement work better. And the data does seem to indicate that positive re-enforcement is superior.

AstralStorm 9y ago
The question then is, what is the optimal latency to recognise improvement or decline? Could deferring judgement help with combating this observation? Then also what magnitude of praise or negative feedback elicits best results? Essentially this could down to finding out the optimal training schedule for humans. (Like for neural nets or classifiers.) And this is similar to adversarial training. You have to consider both the trainee and the trainer (discriminator).
piker 9y ago
> It's rare for people to make enormous improvements or experience enormous depredations in performance one experience to the next. Not a golfer, I see.

AstralStorm 9y ago

The question then is, what is the optimal latency to recognise improvement or decline? Could deferring judgement help with combating this observation? Then also what magnitude of praise or negative feedback elicits best results? Essentially this could down to finding out the optimal training schedule for humans. (Like for neural nets or classifiers.) And this is similar to adversarial training. You have to consider both the trainee and the trainer (discriminator).

piker 9y ago

> It's rare for people to make enormous improvements or experience enormous depredations in performance one experience to the next. Not a golfer, I see.