Web-Based Recommendation System Architecture for Knowledge Reuse in MOOCs Ecosystems

With the success of MOOCs (Massive Open Online Courses) in recent years and the emergence of several courses in these environments, students face difficulties in choosing the best materials, modules or courses. Some recommendation systems have come up to address such problem. However, they provide recommendation limited to a specific MOOC provider. This work proposes an architecture of a web-based recommendation system to support students in finding suitable courses or materials to reach their interests. In addition, this work will raise the fundamental actors and roles of an underlying software ecosystem (SECO) and relate them to those involved in MOOCs ecosystems. The main motivation is that several elements of such ecosystems derive from virtual learning community ecosystems, failing to reproduce particularities of MOOCs learning community ecosystem. Therefore, the system resulting from this architecture also aims to achieve the knowledge reuse in these MOOCs ecosystems, i.e., demands, improvements and software sharing over the platforms.