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Adaptive Hypermedia System in Education: A User Model and Tracking Strategy Proposal

机译:教育自适应超媒体系统:用户模型和跟踪策略提案

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New technologies are quickly changing the traditional educational approaches and systems. In fact the integration of new technologies in the field of education offers new challenges and opportunities in distance learning, lifelong learning and e-learning in general. On the other hand e-Learning is an interesting application area for adaptive hypermedia system (AEH). Through the use of user models intelligent tutoring and students tracking techniques an AEH can recognize individual users and their needs adapting in an effective way the student learning path. This paper attempts to enhance student learning by addressing different learning styles by the use of the Adaptive Hypermedia System approach. In particular it addresses to define a standardized and simple user model and some tracking parameters and techniques in order to update the proposed learning path. The proposed system collects information on the user learning style by the use of various well known in literature test. We propose a mapping of this acquired information in some parameters defined in standard metadata user description like IMS LIP. The final goal is a student learning style representation by the use of a quantitative model. So we can develop a tracking strategy through the observation of the main model parameters. A similar approach could be used for the description of learning objects in order to provide the introduction of well defined metrics for the dynamic tailoring of the learning path to the student's learning style and needs.
机译:新技术正在迅速改变传统的教育方法和系统。事实上,新技术在教育领域的整合提供了远程学习,终身学习和电子学习的新挑战和机遇。另一方面,电子学习是适应超媒体系统(AEH)的有趣应用领域。通过使用用户模型智能辅导和学生跟踪技术可以认识到个人用户,他们的需求以学生学习路径有效的方式适应。本文试图通过使用自适应超媒体系统方法来解决不同的学习方式来提高学生学习。特别是它地址以定义标准化和简单的用户模型和一些跟踪参数和技术,以便更新所提出的学习路径。通过在文献测试中使用各种众所周知,建议的系统收集有关用户学习风格的信息。我们提出了在标准元数据用户描述中定义的一些参数中的该获取信息的映射,如IMS唇。最终目标是通过使用定量模型来学习风格表示。因此,我们可以通过观察主要模型参数来开发跟踪策略。一种类似的方法可以用于学习对象的描述,以便为学习方式和需求的学习路径的动态剪裁来提供良好定义的度量。

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