[ACT-R-users] Model of writing

[Wai-Tat Fu]

Hi, the first paper is a model of skill learning that shows the  
effects of practice, and second one is a reinforcement learning model  
on sequence learning. Hope they are useful.

Fu, W.-T., Gonzalez, C, Healy, A., Kole, J., Bourne, L. (2006),  
Building predictive human performance models of skill acquisition in a  
data entry task. Proceedings of the 50th Annual Meeting of the Human  
Factors and Ergonomics Society (pp. 1122-1126). Santa Monica, CA:  
Human Factors and Ergonomics Society.

Fu, W.-T., Anderson, J. R. (2006), From recurrent choice to skilled  
learning: A reinforcement learning model. Journal of Experimental  
Psychology: General, 135(2), 184-206.


On Aug 30, 2010, at 10:38 AM, Paul J. Reber wrote:

> This might be just slightly off the general writing/typing topic, but
> has anybody played around with an ACT-R model of something like  
> playing
> Guitar Hero?  We're using a task something like this in the lab  
> (without
> music) to look at sequence learning and thinking about the general
> process of skill acquisition (in perceptual-motor tasks).
>
> The relation to typing would be why you might be quicker to type
> familiar words/phrases due to prior practice frequently typing them.
>
> Paul
> -- 
> Paul J. Reber, Ph.D.
> Department of Psychology
> Northwestern University
>
> Dan Bothell wrote:
>>
>> To test the question about 1 fingered, 2 fingered, and 10 fingered
>> typists in ACT-R I created some test models (if you could even call
>> them that because they're mostly just Lisp code) which just push  
>> motor
>> requests through to type out sentences repeatedly for 60 seconds to
>> get a words/minute score (where a word is every 5 keypresses).  Those
>> models were then tested across the three possibilities for pipelining
>> of motor actions: "state free", "processor free", and "preparation  
>> free".
>>
>> There were 5 total models:
>>
>> One-finger is a good "hunt and peck" typist using only one finger.
>>
>> Two-fingers is a good "hunt and peck" typist using both index fingers
>> keeping each hand on its own side of the keyboard.
>>
>> Ten-fingers is a model which uses the default press-key action to
>> touch-type using all fingers.
>>
>> One-finger-savant is a perfect touch-typist using only one index  
>> finger
>> i.e. it can move that finger from any key to hit any other key
>> perfectly as a single action, without looking.
>>
>> Two-finger-savant is a perfect touch-typist using both index fingers
>> where each finger stays on its own side of the keyboard.
>>
>> Here's the average WPM I got based on 3 simple sentences which
>> each have all the letters of the alphabet at least once:
>>
>>                  state free   processor free    preparation free
>> one-finger            13.0           19.1                X
>> two-fingers           13.8           20.7                X
>> ten-fingers           25.3           40.9              47.5
>> one-finger-savant     30.5           44.6                X
>> two-finger-savant     28.3           44.1                X
>>
>> The code is attached if anyone wants to look at the individual
>> sentence results (the function run-all-tests will run the models
>> through all the conditions), but I wouldn't recommend it as a
>> guide for how to write an ACT-R model.  :)
>>
>> Here are the things which I found interesting.
>>
>> - The fastest overall was the ten fingered model in the "preparation
>> free" case at 47.5 wpm, which is faster than I expected.
>>
>> - Testing "preparation free" actually lead to typing errors for the  
>> one-
>> and two-fingered models since it was modifying the features before  
>> the
>> last action had begun (the finger was trying to do two things at  
>> once).
>> So, those models are skipped for that condition.
>>
>> - In the other cases the ten fingered model beats the "hunt and peck"
>> models as expected, but the "savant" models were faster than the
>> ten fingered one.  So the savings in preparation time is better than
>> the cost of the extra movement relative to the press-key actions
>> with the default motor module parameters.  However, from a  
>> plausibility
>> standpoint what those savant models do seems pretty super human to  
>> me.
>>
>>
>> Dan
>>
>>
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>>
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>
>
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