个性化学习推荐模型的研究

A Study on Personalized Learning Recommendation Model

通过分析个性化学习的特点,构造了个性化学习推荐模型。为保证学习效果,设计了基于ISM的学习序列生成方法,从整体上引导学习者的学习过程;在单个知识点学习时,采用关联规则挖掘,推荐符合学习者特征的学习材料。

Personalized learning has become an important issue of modern distance learning. Firstly, the features and differences against Electronic Commerce are analyzed. Personalized learning model not only depend on user＇ s preference, but also is driven by learning goal. Then, at the basis of Constructivism, a personalized learning recommendation model is proposed. In order to improve learning effect, a constructing method about learning sequence is designed, leading learner to study according to knowledge structure. When learner studies a specific knowledge node, Association Rule Mining is applied to recommend suitable learning material to improve learning efficiency. Through developing experimental system and comparing average score of learners assisted by system with others, the performance of proposed model is outstanding.