Journal of Software, Vol 7, No 3 (2012), 588-593, Mar 2012
doi:10.4304/jsw.7.3.588-593

The Quality Assessment of Student Learning Based on Cloud Model

Lizhen Liu, Wentao Wang, Maohong Zhang

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 Model Theory was applied to build student model in Intelligent Tutoring System. And a quality assessment approach of student learning based on cloud model was proposed. Students’ test scores are regarded as cloud droplets, and data is discretized according to contribution of the cloud concept in the research. Furthermore, 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 the 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.



Keywords


cloud model, student learning quality evaluation, student model

References


 

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