I want to model the human learning while operating a machine about which the human has a vague idea and then slowly picks up expertise in operating it. What are the techniques through which this can be done. Thanks in advance.
I think Artificial Neural Networks is a good computational model of brain so that you can move towards modeling human learning model. But at this point, using one technique will be limited so you should create some kind of hybrid system including several techniques. As you can understand, I mean use of more than one Artificial Neural Networks. For example, you may need continuous and combinatorial optimization techniques to achieve some aspects of learning processes.
Hi there,
The ideas of Sugata Mitra and his "Hole in the wall" may ring some bells.
https://www.ted.com/talks/sugata_mitra_build_a_school_in_the_cloud?language=es
I also agree with Köse when picking Neural Networks (think about "knotworking").
Kind regards.
I suggest drawing on the explanation of learning based on Activity Theory. Activity Theory provides a model of how the learner (the subject) pursues a goal (whatever you want your learner to do with the machine you mention) using tools (the machine) and the knowledge of the community in which this learning takes place.
Yrjö Engeström (1987). Learning by Expanding. Online: http://lchc.ucsd.edu/mca/Paper/Engestrom/expanding/toc.htm
https://youtu.be/jP2v6pzhCQw
Thank you everyone for the answers, I am looking for solutions from control systems point of view. I was able to find pilot models being used for aerospace control applications, but these models have fixed parameters and does not reflect fast evolution of parameter selection to correctness with expertise.
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