Make adaptive learning of the MOOC: The CML model

Yan-hong Li, Zhao Bo, Jian-hou Gan
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引用次数: 8

Abstract

The chance to learn from the best educators of the top universities for free has attracted wide interests of millions who have registered for MOOCs across the world. As MOOCs have gained caused great repercussions, critical debate is brewing on the pedagogical effectiveness of MOOCs. The high attrition rate of students who register at the beginning of a MOOC is a major cause of concern regarding the long-term success, impact, and sustainability of MOOC. Having conducted many studies on the application of adaptive learning in personalized MOOC learning. This article describes the details of customized MOOC learning (CML) model, which contains MOOC cloud, personalized course map and adaptive MOOC learning system. The results indicate that providing a strong pedagogical framework and a personalized learning experience in a MOOC learning environment is very important.
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实现MOOC的自适应学习:CML模型
免费向顶尖大学最优秀的教育家学习的机会吸引了全球数百万注册mooc的人的广泛兴趣。随着mooc的反响越来越大,关于mooc教学效果的争论也愈演愈烈。在MOOC开始注册的学生的高流失率是影响MOOC长期成功、影响和可持续性的主要原因。对适应性学习在个性化MOOC学习中的应用进行了大量研究。本文详细介绍了定制化MOOC学习(CML)模式,包括MOOC云、个性化课程地图和自适应MOOC学习系统。结果表明,在MOOC学习环境中提供强大的教学框架和个性化的学习体验是非常重要的。
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