A Comparison of Two Different Methods to Individualize Students and Skills

نویسندگان

  • Yutao Wang
  • Neil T. Heffernan
چکیده

One of the most popular methods for modeling students’ knowledge is Corbett and Anderson’s [1] Bayesian Knowledge Tracing (KT) model. The original Knowledge Tracing model does not allow for individualization. In this work, we focus on comparing two different individualized models: the Student Skill model and the two-phase model, to find out which is the best for formulating the individualization problem within a Bayesian networks framework.

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تاریخ انتشار 2013