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A Machine Learning Based Framework for Adaptive Mobile Learning

机译:基于机器学习的自适应移动学习框架

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Advances in wireless technology and handheld devices have created significant interest in mobile learning (m-learning) in recent years. Students nowadays are able to learn anywhere and at any time. Mobile learning environments must also cater for different user preferences and various devices with limited capability, where not all of the information is relevant and critical to each learning environment. To address this issue, this paper presents a framework that depicts the process of adapting learning content to satisfy individual learner characteristics by taking into consideration his/her learning style. We use a machine learning based algorithm for acquiring, representing, storing, reasoning and updating each learner acquired profile.
机译:无线技术和手持设备的进步在近年来对移动学习(M-Learch)产生了重大兴趣。现在学生可以随时学习。移动学习环境还必须满足不同的用户偏好和具有有限功能的各种设备,而不是所有信息都与每个学习环境相关的和至关重要。为了解决这个问题,本文提出了一个框架,它描绘了通过考虑他/她的学习风格来调整学习内容以满足个别学习者特征的过程。我们使用基于机器学习的算法来获取,代表,存储,推理和更新每个学习者获取的配置文件。

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