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A Novel Approach for Selection of Learning Objects for Personalized Delivery of E-Learning Content

机译:选择用于个性化交付电子学习内容的学习对象的新方法

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Personalized E-learning, as an intelligent package of technology enhanced education tends to overrule the traditional practices of static web based E-learning systems. Delivering suitable learning objects according to the learners' knowledge, preferences and learning styles makes up the personalized E-learning. This paper proposes a novel approach for classifying and selecting learning objects for different learning styles proposed by Felder and Silverman The methodology adheres to the IEEE LOM standard and maps the IEEE LO Metadata to the identified learning styles based on rule based classification of learning objects. A pilot study on the research work is performed and evaluation of the system gives an encouraging result
机译:个性化的电子学习,作为增强技术的智能包装,往往会推翻基于静态网络的电子学习系统的传统做法。根据学习者的知识,偏好和学习方式交付合适的学习对象,构成了个性化的电子学习。本文提出了一种新颖的方法,用于分类和选择Felder和Silverman提出的针对不同学习风格的学习对象。该方法遵循IEEE LOM标准,并基于基于规则的学习对象分类将IEEE LO元数据映射到已识别的学习风格。对研究工作进行了初步研究,对系统的评估给出了令人鼓舞的结果

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