Data Models in Learning Analytics

نویسندگان

  • Vlatko Lukarov
  • Mohamed Amine Chatti
  • Hendrik Thüs
  • Fatemeh Salehian Kia
  • Arham Muslim
  • Christoph Greven
  • Ulrik Schroeder
چکیده

There are many different ways and models how to characterize usage data to enable representation of user actions across learning management system, and systems in general. Based on this data, learning analytics can perform different analysis and provide personalized and meaningful information to improve the learning and teaching processes. There is a variety of usage data formats that are already successfully used in exiting systems. These different usage data formats have their advantages and disadvantage that have to be considered when using them in the context of learning analytics. In this paper, several usage data formats are presented and analyzed in the context of learning analytics to help in choosing the best suiting usage data model.

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تاریخ انتشار 2014