A novel method of case representation and retrieval in CBR for e-learning

被引：7

作者：

Khamparia A. ^{[1
]}

Pandey B. ^{[2
]}

机构：

[1] Department of Computer Science and Engineering, Lovely Professional University, 14411, Punjab

[2] Department of Computer Application, Lovely Professional University, 144411, Punjab

来源：

Education and Information Technologies | 2017年 / 22卷 / 1期

关键词：

Artificial neural network; Case based reasoning; Case representation; Data mining; Decision tree; Learning performance;

D O I：

10.1007/s10639-015-9447-8

中图分类号：

学科分类号：

摘要：

In this paper we have discussed a novel method which has been developed for representation and retrieval of cases in case based reasoning (CBR) as a part of e-learning system which is based on various student features. In this approach we have integrated Artificial Neural Network (ANN) with Data mining (DM) and CBR. ANN is used to find the relationship between student characteristics and learning performance, DM to generate classification rules for learning outcomes which are further used to generate cases for the case base and CBR for reasoning. This adaptive system helps in facilitating the course content of different difficulty level to individuals according to their features. The result shows the above method provides the learning material to student as per their need and helps them to enhance their learning. © 2015, Springer Science+Business Media New York.

引用

页码：337 / 354

页数：17

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