Context-aware and Personalization Method based on Ubiquitous Learning Analytics
Context-aware and Personalization Method based on Ubiquitous Learning Analytics
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发表时间：
2016
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通讯作者：
Kousuke Mouri;H. Ogata;Noriko Uosaki;Erdenesaikhan Lkhagvasuren
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作者：
Kousuke Mouri;H. Ogata;Noriko Uosaki;Erdenesaikhan Lkhagvasuren
在过去的几十年里，泛在学习一直是世界各国教育研究的焦点。大多数u-Learning系统都是使用无处不在的技术构建的，例如RFID标签和卡、无线通信、移动电话和可穿戴计算机。也有越来越多的人认识到，它可以通过利用由U-学习系统收集的无处不在的学习日志来增强和增加学习者、上下文和基于上下文的知识之间的交互来改进。基于u-学习的分析问题之一是如何检测或挖掘由u-学习系统收集的学习日志。此外，有必要评估分析发现的建议在学习水平、背景和学习者偏好方面是否合适。为了解决这些问题，我们开发了一个系统，可以根据学习者的个性化在正确的时间在正确的地点推荐有用的学习日志。进行了一项实验，以评估系统的性能和建议对学习的有用性。在评价实验中，我们找到了在现实世界语言学习中推荐的重要标准。此外，通过我们的推荐方式，参与者能够增加他们的学习机会。
: In the past decades, ubiquitous learning (u-learning) has been the focus of attention in educational research across the world. Majority of u-learning systems have been constructed using ubiquitous technologies such as RFID tags and cards, wireless communication, mobile phones, and wearable computers. There is also a growing recognition that it can be improved by utilizing ubiquitous learning logs collected by the u-learning system to enhance and increase the interactions among a learner, contexts, and context-based knowledge. One of the issues of analytics based on u-learning is how to detect or mine learning logs collected by u-learning systems. Moreover, it is necessary to evaluate whether the recommendations detected by analysis are appropriate in terms of learning levels, contexts and learners’ preference. To tackle the issues, we developed a system that could recommend useful learning logs at the right place in the right time in accordance with personalization of learners. An experiment was conducted to evaluate the system’s performance and the recommendations’ usefulness for learning. In the evaluation experiment, we found important criteria for recommending in the real-world language learning. In addition, the participants were able to increase their learning opportunities by our recommendation method.