4.6 Article

UTiLearn: A Personalised Ubiquitous Teaching and Learning System for Smart Societies

期刊

IEEE ACCESS
卷 5, 期 -, 页码 2615-2635

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2017.2668840

关键词

Big data; computational and artificial intelligence; distance learning; high performance computing; Internet of Things

资金

  1. Deanship of Scientific Research, King Abdulaziz University, Jeddah, Saudi Arabia [1437/611/715]

向作者/读者索取更多资源

The education industry around the globe is undergoing major transformations. Organizations, such as Coursera are advancing new business models for education. A number of major industries have dropped degrees from the job requirements. While the economics of higher education institutions are under threat in a continuing gloomy global economy, digital and lifelong learners are increasingly demanding new teaching and learning paradigms from educational institutions. There is an urgent need to transform teaching and learning landscape in order to drive global economic growth. The use of distance eTeaching and eLearning (DTL) is on the rise among digital natives alongside our evolution toward smart societies. However, the DTL systems today lack the necessary sophistication due to several challenges including data analysis and management, learner-system interactivity, system cognition, resource planning, agility, and scalability. This paper proposes a personalised Ubiquitous eTeaching & eLearning (UTiLearn) framework that leverages Internet of Things, big data, supercomputing, and deep learning to provide enhanced development, management, and delivery of teaching and learning in smart society settings. A proof of concept UTiLearn system has been developed based on the framework. A detailed design, implementation, and evaluation of the UTiLearn system, including its five components, are provided using 11 widely used datasets.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据