Method for test results analysis of e-learning based on rough set theory

In order to improve personalized service of e-learning systems, this paper introduces a method of attribute value reduction algorithm and decision rules generation based on rough set theory. This work analyzes e-learners' online test results and creates decision tables via expanding information of all the examination questions. The rough set based algorithm generates rules, which are used to evaluate the degree of e-learners master the knowledge, to provide personalized feedback, and to make the e-learners select instructional resources more specifically.