Web-based interactive and visual data analysis for ubiquitous learning analytics

Benjamin Weyers, Christian Nowke, Torsten W. Kuhlen, Mouri Kousuke, Hiroaki Ogata

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)


Interactive visual data analysis is a well-established class of methods to gather knowledge from raw and complex data. A broad variety of examples can be found in literature presenting its applicability in various ways and different scientific domains. However, fully fledged solutions for visual analysis addressing learning analytics are still rare. Therefore, this paper will discuss visual and interactive data analysis for learning analytics by presenting best practices followed by a discussion of a general architecture combining interactive visualization employing the Information Seeking Mantra in conjunction with the paradigm of coordinated multiple views. Finally, by presenting a use case for ubiquitous learning analytics its applicability will be demonstrated with the focus on temporal and spatial relation of learning data. The data is gathered from a ubiquitous learning scenario offering information for students to identify learning partners and provides information to teachers enabling the adaption of their learning material.

Original languageEnglish
Pages (from-to)65-69
Number of pages5
JournalCEUR Workshop Proceedings
Publication statusPublished - 2016
Event1st International Workshop on Learning Analytics Across Physical and Digital Spaces, CrossLAK 2016 - Edinburgh, Scotland, United Kingdom
Duration: Apr 25 2016Apr 29 2016

All Science Journal Classification (ASJC) codes

  • General Computer Science


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