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What is an Intelligent Tutoring System?

One definition of an intelligent tutoring system (ITS) is computer based instruction that uses AI methods. To me this does not seem like a good definition, since it is quite possible that a piece of instructional software that does not use AI methods could appear and behave to a learner like one that does. Then again, what once were AI methods may now be considered to be commonplace.In a discussion I once had with Alan Lesgold , he said “We call something artificial intelligence when we don’t know how to do it. As soon as we figure it out, then it isn’t artificial intelligence any more.” Amusing.

Then there is Elliot Solaway’s statement I’ve heard him make on one more than occasion “I tried so long to figure out how to make computers smarter, then one day I realized, its not the computers that we should try to make smarter, its the students, so that is what I’ve tried to focus on since.” Both of these resonate with the theme of the Social Life of Information by JSB that I’m currently reading.
I ran across Quantum Simulations intelligent tutoring systems again today. I’ve looked at it briefly before and will look at it again. I have been a student of the ITS literature and attended the CIRCLE Summer School a couple of years ago. I taught a semester of College Algebra here at USU using Carnegie Learning’s Quantitative Literacy Tutor. My masters project involved in the creation of an ITS for teaching solving systems of simultaneous linear equations (I’ll post a link to it tomorrow). I also created an expert system as part of some research on feedback that I conducted with Dr. Gibbons. One of the five dissertation proposals I put together focused on problem sequencing. To prepare for that project I conducted an extensive review of the literature on problem sequencing including ITS research (I’ll post that too).

So what does ITS have to offer? From my reading:

  • Methods for analyzing human performance that are perhaps more rigorous than those typically offered by the field of ID.
  • User interfaces that allow performances to be carried out in non-linear sequences as opposed to the strictly sequential sequences typically found in most CBT.
  • Ways to interpret more complex types of student input than typical CBT.
  • Methods for dynamically sequencing instruction or problems.

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