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Towards a computationally intelligent lesson adaptation for a distance learning course

机译:面向远程学习课程的计算机智能课程改编

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A neuro-fuzzy approach is introduced to implement lesson adaptation in a Web-based course. Several key points that affect the effectiveness of an adaptive learning environment are investigated the development of the educational material, the structure of the domain knowledge, the instructional design and the evaluation of the learner knowledge under uncertainty. The proposed approach allows the generation of the content of a hypermedia page from pieces of educational material based on goal-oriented teaching and making use of the background knowledge of the learner.
机译:引入了神经模糊方法,以在基于Web的课程中实现课程自适应。研究了影响自适应学习环境有效性的几个关键点,研究了教材的发展,领域知识的结构,教学设计以及不确定性下学习者知识的评估。所提出的方法允许基于面向目标的教学并利用学习者的背景知识,从教育材料中生成超媒体页面的内容。

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