Semantically enriched Massive Open Online Courses (MOOCs) platform

Massive Open Online Courses (MOOCs) are becoming an essential source of information for both students<br>and teachers. Noticeably, MOOCs have to adapt to the fast development of new technologies; they also<br>have to satisfy the current generation of online students. The current MOOCs’ Management Systems, such<br>as Coursera, Udacity, edX, etc., use content management platforms where content are organized in a<br>hierarchical structure. We envision a new generation of MOOCs that support interpretability with formal<br>semantics by using the SemanticWeb and the online social networks. Semantic technologies support<br>more flexible information management than that offered by the current MOOCs’ platforms. Annotated<br>information about courses, video lectures, assignments, students, teachers, etc., can be composed from<br>heterogeneous sources, including contributions from the communities in the forum space. These annotations,<br>combined with legacy data, build foundations for more efficient information discovery in MOOCs’<br>platforms. In this article we review various Collaborative Semantic Filtering technologies for building<br>Semantic MOOCs’ management system, then, we present a prototype of a semantic middle-sized platform<br>implemented at Western Kentucky University that answers these aforementioned requirements.

大规模开放在线课程（Massive Open Online Courses，MOOCs）正逐步成为学生与教师不可或缺的信息来源。
值得注意的是，MOOCs需要适配新技术的快速发展，同时也要满足当代在线学习者的需求。当前的MOOC管理系统（如Coursera、Udacity、edX等）均采用内容管理平台，其内容以层级结构进行组织。
我们构想了新一代MOOCs，其可通过语义网（Semantic Web）与在线社交网络实现基于形式化语义的可解释性支持。语义技术相较于当前MOOC平台所提供的方案，能够支持更为灵活的信息管理。
针对课程、视频讲座、作业、学习者与教师等对象的标注信息，可从包括论坛社区贡献在内的各类异构数据源中整合获取。这些标注信息与遗留数据相结合，可为MOOC平台内更高效的信息发现工作奠定基础。
本文首先综述了用于构建语义化MOOC管理系统的各类协同语义过滤技术，随后介绍了西肯塔基大学开发的一款语义化中型平台原型，该原型可满足前文所述的各项需求。