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Designing Learning Analytics Experiences

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Learning Analytics

Abstract

With the increasing presence of digital devices and technology-mediated activities, the possibility of obtaining a detailed account of the events occurring in a learning experience is now a reality. Learning analytics is the discipline that uses this data to improve the overall effectiveness of the learning experience. The use of learning analytics can be divided into five stages: collect, analyze, predict, act, and refine. In this chapter an analysis of each of these stages and some of the solutions being used are discussed. An issue orthogonal to these steps is privacy and security. This chapter provides a discussion of the principles to take into account when approaching the design of a learning analytics experience, noting the dependencies between stages and what concerns might guide a decision to take a learning analytics platform from idea to execution.

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Author information

Authors and Affiliations

  1. School of Electrical and Information Engineering, The University of Sydney, Sydney, NSW, 2006, Australia

    Abelardo Pardo

Authors
  1. Abelardo Pardo
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Correspondence to Abelardo Pardo .

Editor information

Editors and Affiliations

  1. Center for Digital Data, Analytics and Adaptive Learning at Pearson, Boston, Massachusetts, USA

    Johann Ari Larusson

  2. Dept. of English, University of California Berkeley, Berkeley, California, USA

    Brandon White

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Pardo, A. (2014). Designing Learning Analytics Experiences. In: Larusson, J., White, B. (eds) Learning Analytics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3305-7_2

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