运用贝叶斯分类器提高学习者的熟练程度

D. Burdescu, M. Mihăescu, B. Logofatu
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引用次数: 1

摘要

提高学习者的熟练程度是电子学习系统中一个持续存在的问题。本文提出了一个解决方案,建议学习者关于他应该访问和学习的资源,以获得所需的熟练程度。该解决方案使用朴素贝叶斯作为分类算法,输入数据由学习者执行的活动表示。执行的活动被记录下来,并用作培训和测试数据。获得的分类器用于新生,并为他们提供有关需要访问和学习哪些资源的必要信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Employing Bayes Classifier for Improving Learner's Proficiency
Improving learner's proficiency is a continuous issue in e-Learning systems. This paper presents a solution for advising the learner regarding the resources he should access and study in order to obtain a required proficiency level. The solution uses a Naive Bayes as classification algorithm with input data represented by learner's performed activities. The performed activities are logged and used as training and testing data. The obtained classifier is used for new students and provides them with necessary information regarding what resources need to access and study.
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