Evolution of Interests in the Learning Context Data Model

نویسندگان

  • Hendrik Thüs
  • Mohamed Amine Chatti
  • Roman Brandt
  • Ulrik Schroeder
چکیده

A key area of application for Learning Analytics (LA) and Educational Data Mining (EDM) is lifelong learner modeling. The aim is that data gathered from different learning environments would be fed into a personal lifelong learner model that can be used to foster personalized learning experiences. As learning is increasingly happening in open and networked environments beyond the classroom and access to knowledge in these environments is mostly context-sensitive and interest-driven, learner’s contexts and interests need to constitute important features to be modeled. The context data of a learner as it is already represented by the Learning Context Data Model (LCDM) specification, describes the learner’s activities, her biological conditions, as well as the characteristics of the learning environment. Towards a lifelong learner model, a model consisting of context data can further be refined with an evolving set of interests. This paper describes an approach to extend the existing LCDM specification with interests, taking into account the importance of the interests as well as their evolution over time.

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تاریخ انتشار 2015