Semantically enriched Massive Open Online Courses (MOOCs) platform

Computers in Human Behavior(2015)

引用 24|浏览22
暂无评分
摘要
We present collaborative semantic filtering technologies for building semantic MOOCs management system.We illustrate the methods of annotating information including contributions from the communities in the forum space.We present the implementation of a prototype of a semantic middle-sized platform.We propose a new generation of MOOCs that supports interpretability with formal semantics.We present the usage of SemanticWeb and online social networks within MOOCs. Massive Open Online Courses (MOOCs) are becoming an essential source of information for both students and teachers. Noticeably, MOOCs have to adapt to the fast development of new technologies; they also have to satisfy the current generation of online students. The current MOOCs' Management Systems, such as Coursera, Udacity, edX, etc., use content management platforms where content are organized in a hierarchical structure. We envision a new generation of MOOCs that support interpretability with formal semantics by using the SemanticWeb and the online social networks. Semantic technologies support more flexible information management than that offered by the current MOOCs' platforms. Annotated information about courses, video lectures, assignments, students, teachers, etc., can be composed from heterogeneous sources, including contributions from the communities in the forum space. These annotations, combined with legacy data, build foundations for more efficient information discovery in MOOCs' platforms. In this article we review various Collaborative Semantic Filtering technologies for building Semantic MOOCs' management system, then, we present a prototype of a semantic middle-sized platform implemented at Western Kentucky University that answers these aforementioned requirements.
更多
查看译文
关键词
Massive Open Online Courses (MOOCs),Collaborative semantic filtering techniques,Annotated information,Computing for Co-learning,Interpretability,SemanticWeb,Social networks
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要