Objectives & Topics

We welcome high-quality papers about actual trends in (a) how education and learning takes advantage of the Web data, and (b) how principles for data sharing can benefit educational contexts. We will seek application-oriented, empirical, as well as more theoretical and position papers in the following, non-exhaustive list of topics:

  • Learning analytics & educational data mining in Web-based (informal & formal) learning
  • Understanding learning behavior through Web data
  • Open access to educational data and resources
  • Web mining and Web science in online learning
  • Analytics of pattern and notions of learning in the Social Web
  • Using the Web of Data for personalization and context-awareness in Web-based learning
  • Exploration of informal learning activities on the Web
  • Search As Learning (SAL): understanding learning during Web search
  • schema.org and LRMI for annotating and exploring educational related Web content
  • Understanding learning from user activity logs and behavioral traces
  • Visual analytics of educational data
  • Knowledge graphs and structured data for sharing and reusing learning and knowledge resources
  • Structured knowledge graphs for analyzing & interpreting learning activity and resource data
  • Entity-centric approaches for analyzing and understanding learning activities
  • Light-weight educational metadata schemas and vocabularies
  • Semantic & syntactic mappings between educational schemas and vocabularies
  • Controlled vocabularies, schemas and ontologies for Web-based learning
  • Linked Data and schema.org/Microdata in learning analytics and educational data mining
  • Using Web data and taxonomies to represent learning goals and organizational objectives
  • Collaborative learning on the Web of Data

 

 

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