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Determining the Learner’s Profile and Context Profile in Order to Propose Adaptive Mobile Interfaces Based on Machine Learning

机译:确定学习者的个人资料和上下文配置文件,以提出基于机器学习的自适应移动接口

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Sociological studies show that the use of mobile phones in the whole worldwide has attained a record level. This phenomenon has influenced the field of education. The integration of mobile technologies into teaching can improve learning conditions and the way in which learners receive educational content.Changing attitudes and behaviors in the education field, developing appropriate pedagogical models, good design (pedagogical and visual), providing methods to control the students to allow for uninterrupted mobile learning activities, seem the challenges of Mobile Learning.Though the mobile devices are important in the daily lives of learners and trainers, the use of these technologies in distance learning remains weak. To carry out our project, we used tools such Moodle and Open edX databases and Google Analytics for data collection. In this project, we try to propose an approach based on machine learning algorithms in order to personalize the mobile display and the pedagogical content on mobile devices in an online learning scenario.
机译:社会学研究表明,在全球范围内使用手机已经达到了记录水平。这种现象影响了教育领域。移动技术与教学中的整合可以改善学习条件以及学习者接受教育内容的方式。强化教育领域的态度和行为,开发适当的教学模式,良好的设计(教学和视觉),提供控制学生的方法允许不间断的移动学习活动,似乎是移动学习的挑战。虽然移动设备在学习者和培训师的日常生活中都很重要,但在远程学习中使用这些技术仍然很弱。要执行我们的项目,我们使用工具此类Moodle和Open EDX数据库和Google Analytics进行数据收集。在这个项目中,我们尝试基于机器学习算法提出一种方法,以便在在线学习场景中为移动设备上的移动显示和教学内容进行个性化。

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