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Data mining methods to assess student behavior in adaptive e-learning processes

机译:数据挖掘方法评估自适应电子学习过程中的学生行为

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How could data mining help the development of e-learning methodologies? How could an instructional designer take benefit from the use of adaptive learning? How could adaptive learning be implemented in an Open Source platform? In this paper will be described the implementation of adaptivity technology in a specific, Open Source, Learning Management System (LMS). After a preliminary study about the adaptive features already built-in and the capabilities ready to perform a suitable student modeling, the research team extended those capabilities with a specific data model, student model and tutoring engine to perform automatic monitoring and sequencing of Learning Objects for each particular learner. The future implementation of this project is related to testing activities in order to prove the efficiency method in content and course delivery. This paper describes some best practices developed during a Tempus IV Project granted by EU.
机译:数据挖掘如何帮助开发电子学习方法?教学设计师如何从使用自适应学习中获益?如何在开源平台中实现自适应学习?本文将描述在特定开源,学习管理系统(LMS)中的适应性技术的实现。在关于已经内置的自适应功能和准备好执行合适的学生建模的功能的初步研究之后,研究团队将这些功能扩展了具有特定数据模型,学生模型和辅导引擎,以执行学习对象的自动监控和排序每个特定的学习者。该项目的未来实施与测试活动有关,以证明内容和课程交付中的效率方法。本文介绍了在欧盟授予的威斯特州IV项目期间开发的一些最佳实践。

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