Abstract
In traditional tutoring system, the quality assessment of student learning is identified by hard division regardless of the uncertainty of results. In the paper, Cloud M odel T heory was applied to build student model in Intelligent Tutoring System. And a quality assessment approach of student learning based on cloud m odel was proposed. S tudents’ test score s are regarded as cloud drop let s, and data is discret ized according to contribution of the cloud concept in the research . Further more , cloud transform algorithm is introduced to compute membership cloud. Finally, maximum determination algorithm is used to obtain more actual grade division of learning quality. Experimental results show that membership concept can reflect not only t he mastery level of knowledge points but also the stability and psychology in the process of student learning . The study will help improve the efficiency of Intelligent Tutoring System.
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