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The Quality Assessment of Student Learning Based on Cloud Model

机译:基于云模型的学生学习质量评估

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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.
机译:在传统的补习系统中,无论结果如何不确定,都会通过严格的划分来确定学生学习质量的评估。本文采用云模型理论在智能辅导系统中建立学生模型。提出了一种基于云模型的学生学习质量评估方法。学生的考试成绩被视为云滴,根据云概念在研究中的贡献离散数据。此外,引入了云变换算法来计算成员云。最后,使用最大确定算法获得学习质量的更多实际等级划分。实验结果表明,隶属度概念不仅可以反映知识点的掌握水平,而且可以反映学生学习过程中的稳定性和心理。该研究将有助于提高智能辅导系统的效率。

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