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Visual Learning Analytics for a Better Impact of Big Data

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Radical Solutions and Learning Analytics

Part of the book series: Lecture Notes in Educational Technology ((LNET))

Abstract

Visual learning analytics is an emerging research field in the intersection of visual analytics and learning analytics that is suited to address the many challenges that big data brings to the education domain. Although recent research endeavours have approached the analysis of educational processes through visual analytics, the theoretical foundations of both fields have remained mainly within their boundaries. This chapter aims at mitigating this problem by describing a reference model for visual learning analytics that can guide the design and development of successful systems. A discussion of data, methods, users and objectives’ implications within the frame of the reference model highlights why visual learning analytics is regarded as a particularly promising technology to improve educational processes.

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Author information

Authors and Affiliations

  1. Computer Science Department, GRIAL Research Group, Research Institute for Educational Sciences, University of Salamanca, Salamanca, Spain

    Roberto Therón

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  1. Roberto Therón
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Correspondence to Roberto Therón .

Editor information

Editors and Affiliations

  1. Research Institute for Innovation & Technology in Education (UNIR iTED), Universidad Internacional de La Rioja (UNIR), Logroño, La Rioja, Spain

    Daniel Burgos

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Therón, R. (2020). Visual Learning Analytics for a Better Impact of Big Data. In: Burgos, D. (eds) Radical Solutions and Learning Analytics. Lecture Notes in Educational Technology. Springer, Singapore. https://doi.org/10.1007/978-981-15-4526-9_7

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  • DOI: https://doi.org/10.1007/978-981-15-4526-9_7

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-4525-2

  • Online ISBN: 978-981-15-4526-9

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