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.
Research Trends in Massive Open Online Course (MOOC) Theses and Dissertations: Surfing the Tsunami Wave
Massive Open Online Courses (MOOCs) have attracted a great deal of attention by higher education and private enterprises. MOOCs have evolved considerably since their emergence in 2008, all the while given rise to academic discussions on MOOC impact, design and reach. In an effort to understand MOOCs more comprehensively, this study analyzes theses and dissertations (N = 51) related to MOOCs and published between 2008 and 2015, identifying research trends from these academic documents. Theses and dissertations within this research scope were gathered through a comprehensive search in multiple academic databases. For the purposes of the study, the research employed a systematic review approach. In order to reveal trends in research themes, emphasize theoretical/conceptual backgrounds, research designs and models, first a document analysis was used to collect data and this was followed by a content analysis. Our research findings indicate that MOOC research is generally derived from education, engineering and computer science, as well as information and communication technology related disciplines. Qualitative methodology linked to a case study research model is most common, and the theoretical/conceptual backgrounds are usually distance education related. Remarkably, nearly half of the studies didn’t benefit from any theoretical or conceptual perspectives. In sum, this study presents an evaluation regarding research trends derived from MOOC theses and dissertations, and provides directions for future MOOC research.
Application of attribute recognition method for evaluating on sustained developmental degree of water resource systems.
Taking Ping Ba area as an example, this paper explores the method of comprehensive evaluation on sustained developmental extent of water resources systems and sets up an evaluation model by applying the attribute recognition theoretical model The result shows that it is coherence to the result of the fuzzy comprehensive evaluation method, meanwhile, this method is easy and understood, and it suit for evaluating on system quality with standardsKey words: water resources systems; attribute recognition theoretical model; fuzzy comprehensive evaluation method