Intensified Leveling and Assessment System in Intelligent Tutoring using Decision Tree and Item Response Theory

Abstract

Due to the rapid growth of information and communication technology, the education environment has being enriched and become more diversified. Hence computer based assessment came as a prevalent method of administering the tests. Randomization of test items here may produce unfair effect on test takers which is unproductive in the outcome of the test. There is a need to develop the Intelligent Tutoring System that assigns intelligent question depending on the student’s response in the testing session. It will be more productive when the questions are assigned based on the learner ability in the early stage itself. So, this study focus on building up a framework to automatically assign intelligent question based on the learner ability not only all through the session, but also on entry. At end, automatic up gradation of the question levels can be done dynamically. The questions are classified based on item difficulty using Item Response Theory model. The learners are classified based on their level by Decision Tree using ID3 algorithm. Thereby the objective of Intelligent Tutoring System is achieved by using adaptability and intelligence in testing.

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Cite this paper

@inproceedings{Kavitha2011IntensifiedLA, title={Intensified Leveling and Assessment System in Intelligent Tutoring using Decision Tree and Item Response Theory}, author={R. K. Kavitha}, year={2011} }