OS-2

Learning Analytics for Managing
Organizational and Individual Knowledge

Organizers: Kenji Hirata (Expert Science Institute, Japan) & Jon Mason (Charles Darwin University, Australia)

Abstract:
The tide of big data has come. Along the tide, various technologies and frameworks have been produced for this decade, and given huge impacts upon knowledge management. Types and feature of knowledge that organizations deal with and manage are changing. Former knowledge management focused on organizational rule, operation, and know-who and know-how, and set the importance of acquiring, sharing and delivering. Current knowledge management has to deal with knowledge having more situational aspect, more flexible, less stable and closer relation to strategy, and has functions of visualization, analysis and collaborative production. These functions break off the distance between knowledge management and learning in the workplace and educational institution. Contents for learning would be produced by these functions and also approach through these functions is learning itself.

For organizational and individual learning, there remain various issues in learning analytics (LA), Tore and Chen (2014) pointed following concerns out, (1) privacy, trust and control of data, (2) LA affordances and application domains, (3) LA context and learning activities, (4) legacy system interoperability – information model for LA data exchange, (5) LA implementation best practice guide. In this session, both conceptual and technological papers are welcome for solving above.

Related Topics:

  • Ubiquitous learning
  • Web intelligence
  • Web 2.0 and social computing for learning
  • Learning analytics
  • Semantic Web technology and Web analytics
  • Ontology for knowledge management and learning
  • Visualization
  • Computer Supported Collaborative Work and Learning (CSCW/L)
  • Data and text mining for learning and business performance
  • Framework and information model for E-learning and knowledge management
  • e-Testing and new test theories
  • Intelligent systems architecture
  • Knowledge modeling and representation
  • Knowledge and learning contents retrieval
  • Linked open data for learning
  • Open platforms, open educational resources (OERs), Massive Open Online Courses (MOOCs), and open learning methods
  • e-Profile and personalized learning systems
  • Recommender systems
  • Web and collective intelligence
  • Sensoring system
  • Social network and computing

Important Dates:

  • Full / Short Papers due: June 10, 2015 June 30, 2015
  • Poster Papers due: June 10, 2015 June 30, 2015
  • Notification (Full / Short / Poster papers): July 10, 2015 July 13, 2015
  • Camera-ready papers due: July 31, 2015 July 31, 2015

Submissions:
You must follow the submission instructions of the general session.