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
ETL Tools in Enterprise Data Warehouse
A B S T R A C T An enterprise data warehouse (EDW) also known as Data warehouse (DW), is a system used for reporting and data analysis. DWs are central repositories of integrated data from one or more disparate sources. ExtractionTransformation-Loading (ETL) processes are responsible for all the operations taking place at the warehouse. These processes are performed by specialized tools known as ETL tools or also called as Data Integration tools. The ETL tools are available in the market either as closed source software or as open source software. An ETL tool from both these categories has their advantages and suffers from some limitations as well. The main objective of this paper is to highlight the importance of the data integration tools or also known as ETL tools in business intelligence environment.