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Predictive accuracy based on cognitive approach in web based learning

机译:网络学习中基于认知方法的预测准确性

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With bandwidth increasing at a constant pace, technology in education has become an important part for delivery of educational content to students. Online learning in various forms is gaining popularity but lacks the adaptability required to hold the learners attention due to its rigid structure. Though animation and powerful graphics enhance the learning content, delivery of content according to learners need is yet to become a reality. It is not possible to build a learning system that can satisfy every learner as some people respond best when they see basic facts on a clean page, others when they have a lot of charts and graphs at their fingertips. To overcome these shortcomings, the content delivery itself can be made dynamic based on the learner's need. In this paper, we propose a novel method to identify a user's need based on the cognitive behavior of the user. Based on the response of the user, a decision tree induction algorithm is used to predict the requirements of future users.
机译:随着带宽的不断增长,教育技术已成为向学生提供教育内容的重要组成部分。各种形式的在线学习正变得越来越流行,但由于其僵化的结构而缺乏保持学习者注意力所需的适应性。尽管动画和强大的图形增强了学习内容,但是根据学习者的需求交付内容仍未成为现实。建立一个使每个学习者都满意的学习系统是不可能的,因为有些人在干净的页面上看到基本事实时反应最好,而另一些人的指尖却有很多图表。为了克服这些缺点,可以根据学习者的需求使内容交付本身变得动态。在本文中,我们提出了一种基于用户的认知行为来识别用户需求的新颖方法。基于用户的响应,决策树归纳算法用于预测未来用户的需求。

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