Rohloff, Tobias; Renz, Jan; Suarez, Gerardo Navarro; Meinel, Christoph
Digital Education: At the MOOC Crossroads Where the Interests of Academia and Business Converge (EMOOCs 2019)
Calise, Mauro; Delgado Kloos, Carlos; Reich, Justin; Ruiperez-Valiente, Jose A.; Wirsing, Martin
Springer International Publishing
As Massive Open Online Courses (MOOCs) generate a huge amount of learning activity data through its thousands of users, great potential is provided to use this data to understand and optimize the learning experience and outcome, which is the goal of Learning Analytics. But first, the data needs to be collected, processed, analyzed and reported in order to gain actionable insights. Technical concepts and implementations are rarely accessible and therefore this work presents an architecture how Learning Analytics can be implemented in a service-oriented MOOC platform. To achieve that, a service based on extensible schema-agnostic processing pipelines is introduced for the HPI MOOC platform. The approach was evaluated regarding its scalability, extensibility, and versatility with real-world use cases. Also, data privacy was taken into account. Based on five years of running the service in production on several platform deployments, six design recommendations are presented which can be utilized as best practices for platform vendors and researchers when implementing Learning Analytics in MOOCs.