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How will the Internet of Things and big data analytics impact the education of learning-disabled students? A Concept Paper

机译:物联网和大数据分析将如何影响学习障碍学生的教育?概念文件

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In the last decade, the increasing plurality of materials, media types and software tools within the internet has established first steps towards more individualized learning approaches. However, the development of utilizing Big Data-based algorithms of the next internet generation, the so-called ???Internet of Things???, leads to a comprehensive approach of personalized learning for very different target groups. Understanding the learner's profile and interests, learning goals and learning difficulties, ???intelligent agents??? accompany and guide the learner during the learning process in the future. In particular, for students with learning disabilities such as dyslexia and dyscalculia, the new development of ???learning analytics??? based on Big Data algorithms has a large potential. The goal is to overcome the severe gap between their existing intellectual potentials and their often unsuccessful learning biographies in schools and universities. The changes of daily environments towards a 4.0-Society, in particular through fully networked Smart Cities, result in an increasing number of data from very heterogeneous sources. Due to technologies such as, e.g., smart wearables combined with data generated through traffic and mobility or logistics, smart geographical places will be enabled to act as a basis for intelligent learning and evaluation mechanisms.
机译:在过去的十年中,互联网中越来越多的材料,媒体类型和软件工具为迈向更加个性化的学习方法奠定了第一步。然而,利用下一代互联网的基于大数据的算法的发展,即所谓的“物联网”,导致针对非常不同的目标群体的个性化学习的综合方法。理解智能体的学习者的概况和兴趣,学习目标和学习困难。在未来的学习过程中陪伴并指导学习者。特别是对于有阅读障碍和运动困难等学习障碍的学生,“学习分析”的新发展。基于大数据算法的潜力很大。目的是要克服他们现有的智力潜力和在学校和大学中常常不成功的学习经历之间的严重差距。日常环境向4.0社会的转变,特别是通过完全联网的智慧城市的转变,导致来自非常不同的来源的数据数量不断增加。由于诸如智能可穿戴设备之类的技术与通过交通和出行或物流产生的数据相结合,智能地理位置将成为智能学习和评估机制的基础。

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