A Flexible and Extendable Learning Analytics Infrastructure

  • Tobias Hecking
  • Sven Manske
  • Lars Bollen
  • Sten Govaerts
  • Andrii Vozniuk
  • H. Ulrich Hoppe
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8613)

Abstract

Currently architectures for learning analytics infrastructures are being developed in different contexts. While some approaches are designed for specific types of learning environments like learning management systems (LMS) or are restricted to specific analysis tasks, general solutions for learning analytics infrastructures are still underrepresented in current research. This paper describes the design of a flexible and extendable architecture for a learning analytics infrastructure which incorporates different analytics aspects such as data storage, feedback mechanisms, and analysis algorithms. The described infrastructure relies on loosely coupled software agents that can perform different analytics task independently. Hence, it is possible to extend the analytic functionality by just adding new agent components. Furthermore, it is possible for existing analytics systems to access data and use infrastructure components as a service. As a case study, this paper describes the application of the proposed infrastructure as part of the learning analytics services in a large scale web-based platform for inquiry-based learning with online laboratories.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Tobias Hecking
    • 1
  • Sven Manske
    • 1
  • Lars Bollen
    • 2
  • Sten Govaerts
    • 3
  • Andrii Vozniuk
    • 3
  • H. Ulrich Hoppe
    • 1
  1. 1.University of Duisburg-EssenGermany
  2. 2.Universtiy of TwenteThe Netherlands
  3. 3.École polytechnique fédérale de LausanneSwitzerland

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