Multifaceted Open Social Learner Modelling

  • Lei Shi
  • Alexandra I. Cristea
  • Suncica Hadzidedic
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8613)


Open social learner modelling (OSLM) approaches are promoted in order to assist learners in self-directed and self-determined learning in a social context. Still, most approaches only focus on visualising learners’ performance, or providing complex tools for social navigation. Our proposal, additionally, emphasises the importance of visualising both learners’ performance and their contribution to a learning community. We seek also to seamlessly integrate OSLM with learning contents, in order for the multifaceted OSLM’s prospect for ubiquity and context-awareness to enrich the adaptive potential of social e-learning systems. This paper thus presents the design of multifaceted OSLM by introducing novel, personalised social interaction features into Topolor, a social personalised adaptive e-learning environment. The umbrella target is to create and study aspects of open social learner models. An experimental study is conducted to analyse the impact of the newly introduced features. The results are finally concluded to suggest future research and further improvements.


Learning Content Metacognitive Activity Quiz Score Profile Page Social Navigation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Lei Shi
    • 1
  • Alexandra I. Cristea
    • 1
  • Suncica Hadzidedic
    • 1
  1. 1.Department of Computer ScienceUniversity of WarwickCoventryUnited Kingdom

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