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A naive bayes approach for converging learning objects with open educational resources

机译：朴素的贝叶斯方法将学习对象与开放式教育资源融合在一起

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摘要

Open educational resources (OER) are digitised material freely available to the students and self learners. Many institutions had initiated in incorporating these OERs in their higher educational system, to improve the quality of teaching and learning. These resources promotes individualised study, collaborative learning. If they are coupled with Learning Objects of Learning Management System (LMS), they can lead to opportunities for further pedagogical innovation. It has become increasingly important for educational institutions to support these resources, in a planned and systematic manner. Adapt, assemble and conceptualise existing OERs to respond to diverse learning needs of students and support a variety of learning approaches for a given learning goal is a challenge. In this work, convergence of OERs with Learning Objects is done through metadata using classification techniques. Localisation of these high quality learning materials with the learning content of LMS, delivered as a single instructional unit may help in greater knowledge delivery and this can satisfy the learning needs of diverse student.
机译：开放式教育资源（OER）是数字化的材料，可供学生和自学者免费使用。许多机构已开始将这些OER纳入其高等教育系统，以提高教学质量。这些资源促进个性化学习，协作学习。如果将它们与学习管理系统（LMS）的学习对象结合在一起，则可以为进一步的教学创新带来机会。对于教育机构来说，以计划和系统的方式支持这些资源变得越来越重要。适应，组合和概念化现有的OER，以应对学生的不同学习需求，并为给定的学习目标支持多种学习方法是一项挑战。在这项工作中，OER与学习对象的融合是通过使用分类技术的元数据完成的。将这些高质量的学习材料与LMS的学习内容一起本地化，以单个教学单元的形式提供，可能有助于更大程度的知识传递，并且可以满足不同学生的学习需求。

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