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Ranking Reusable Learning Objects With Rough Sets Based Methods

机译:使用基于粗糙集的方法对可重用学习对象进行排名

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Many educational institutions collaborate for developing joint bachelor, master and PhD programs. Quite often in the process of completing learning materials, included in an intelligent tutoring system f. ex. they have to choose among different learning objects developed by different teams and originally intended to be presented to different type of students. In order to be effective this process should involve both content providers and IT experts. The objective of this paper is to show how a rough set theory based approach can facilitate the process of ranking available learning objects.
机译:许多教育机构合作开发联合的学士,硕士和博士学位课程。经常在完成学习材料的过程中,包括在智能辅导系统f中。例如他们必须在不同团队开发的不同学习对象中进行选择,这些对象最初旨在呈现给不同类型的学生。为了有效,此过程应同时涉及内容提供商和IT专家。本文的目的是展示基于粗糙集理论的方法如何促进对可用学习对象进行排名的过程。

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