A Ubiquitous Learning Analytics Architecture for a Service-Oriented MOOC Platform
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.
Towards a Better Understanding of Mobile Learning in MOOCs
The pervasive presence of mobile devices and growing trends like ubiquitous learning make new demands on Massive Open Online Courses (MOOCs). Users learn increasingly on the go and with multiple devices, instead of being tied to a fixed workstation. However, there is a lack of research how the usage of mobile devices influences the learning behavior and outcome in MOOCs. Thus, this paper presents a first quantitative study to examine this question. To enable a statistical analysis, a proof-of-concept implementation outline is presented, which enhances the Learning Analytics capabilities of the openHPI MOOC platform with contextual data to process various learning behavior metrics. Based on an analysis of four courses, it was found that users who additionally learnt with mobile applications showed a higher engagement with the learning material and completed the course more often. Nevertheless, the reasoning must be addressed with qualitative analyses in future, to better support their learning process and success on mobile and stationary devices.Keywords-Mobile Learning, Learning Analytics, MOOCs
Participants' Perceptions of Learning and Networking in Connectivist MOOCs
Massive open online courses (MOOCs) are growing exponentially in higher education. They have attracted the attention of higher education institutions, course designers, and policy makers. They challenge the mainstream of higher education and provide global learning opportunities to a huge number of students so they can learn anytime and anywhere. The value and applicability of the MOOC model in the current era of higher education and the nature of learning in such an open online format need to be investigated. This study focused on participants' experiences and perceived value of participation in connectivist MOOCs (cMOOCs) in terms of dealing with an abundance of resources and tools, learning activities, and network engagement. The results suggest a high extent of technology deployment for learning and interactions by the participants in cMOOCs. Creating networks and developing professional connections through networking technologies are advantages of participating in cMOOCs. The study's findings contribute to a better understanding of the nature of learning and participation in MOOCs from the perspective of students, who are the main stakeholders of such new learning experiences.