Using Bayesian networks to predict test scores

Pardos, Zachary A.

Student Work

Using Bayesian networks to predict test scores

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The ASSISTment online tutoring system was used by over 600 students during the school year 2004-2005 and MCAS test results were obtained for those students. Students completed online items marked with skills from our four skill models. Using Bayesian networks to predict the MCAS test scores, we found that the finer-grained of the skill models allowed for more accurate prediction. Other topology approaches such as skill hierarchy are explored as well as the effect of parameter learning on prediction performance. The work from this paper has been peer reviewed and accepted for publication at the 8th annual International Conference on Intelligent Tutoring Systems, Taiwan.

This report represents the work of one or more WPI undergraduate students submitted to the faculty as evidence of completion of a degree requirement. WPI routinely publishes these reports on its website without editorial or peer review.

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