A2LS 2013 - 1st International Workshop On Analytics & Awareness Learning Services (A2LS-2013)

Data Analysis is a cornerstone of online learning environments. Since the first conception of e-learning and collaborative systems to support learning and teaching, data analysis has been employed to support learners, teachers, researchers, managers and policy makers with useful information on learning activities and learning design. While data analysis originally employed mainly statistical techniques due to the modest amounts and varieties of data being gathered, with the rapid development of internet technologies and increasingly sophisticated online learning environments, increasing volumes and varieties of data are being generated and data analysis has moved to more complex analysis techniques such as educational data mining and, most recently, learning analytics. Now powered by cloud technologies, online learning environments are capable of gathering and storing massive amounts of data of various formats, and tracking user-system and user-user interactions as well as rich contextual information in such systems. This has led to the need to address the definition, modelling, development and deployment of sophisticated learning services offering analytics and context awareness information to all participants and stakeholders in online learning. This workshop seeks original research contributions in analytics and context awareness in learning systems, driven by service-based architectures and cloud technologies.
The workshop seeks original contributions in all relevant areas, including but not limited to the following topics.
Topics of interest
Learning analytics services
Awareness services for learners and teachers
Analytics and awareness services for group learning
Modelling knowledge domains, learner modelling
Interaction analysis
Event-based awareness services
Event detection, processing and semantic enrichment
Data querying, filtering, transformation, integration, visualisation
Scalable data mining for analytics and awareness
Services for large-scale text analysis and mining
Description and composition of learning services
Schema and metadata models for indexing services
Services for metadata management, provenance, trust
Analytics for Massive Open Online Courses (MOOCs)
Cloud, P2P and Social Networking for learning services
Emerging trends in learning analytics and awareness services
Performance metrics, benchmarks and data sets
Evaluation methodologies
Case studies and applications