A Scalable Solution for Adaptive Problem Sequencing and Its Evaluation
نویسنده
چکیده
We propose an associative mechanism for adaptive generation of problems in intelligent tutors. Our evaluations of the tutors that use associative adaptation for problem sequencing show that 1) associative adaptation targets concepts less well understood by students; and 2) associative adaptation helps students learn with fewer practice problems. Apart from being domainindependent, the advantages of associative adaptation compared to other adaptive techniques are that it is easier to build and is scalable.
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