That dashboard looks nice, but what does it mean? towards making meaning explicit in learning analytics design

Gibson, A; Martinez-Maldonado, R

That dashboard looks nice, but what does it mean? towards making meaning explicit in learning analytics design

Gibson, A

Martinez-Maldonado, R

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Publication Type:: Conference Proceeding
Citation:: ACM International Conference Proceeding Series, 2017, pp. 528 - 532
Issue Date:: 2017-11-28

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Field	Value	Language
dc.contributor.author	Gibson, A https://orcid.org/0000-0003-4619-6515	en_US
dc.contributor.author	Martinez-Maldonado, R https://orcid.org/0000-0002-8375-1816	en_US
dc.date.issued	2017-11-28	en_US
dc.identifier.citation	ACM International Conference Proceeding Series, 2017, pp. 528 - 532	en_US
dc.identifier.isbn	9781450353793	en_US
dc.identifier.uri	http://hdl.handle.net/10453/127315
dc.description.abstract	© 2017 Association for Computing Machinery. All rights reserved. As learning analytics (LA) systems become more common, teachers and students are often required to not only make sense of the user interface (UI) elements of a system, but also to make meaning that is pedagogically appropriate to the learning context. However, we suggest that the dominant way of thinking about the relationship between representation and meaning results in an overemphasis on the UI, and that re-thinking this relationship is necessary to create systems that can facilitate deeper meaning making. We propose a conceptual view as a basis for discussion among the LA and HCI communities around a different way of thinking about meaning making, specifically that it should be explicit in the design process, provoking greater consideration of system level elements such as algorithms, data structures and information flow. We illustrate the application of the conceptualisation with two cases of LA design in the areas of Writing Analytics and Multi-modal Dashboards.	en_US
dc.relation.ispartof	ACM International Conference Proceeding Series	en_US
dc.relation.isbasedon	10.1145/3152771.3156171	en_US
dc.title	That dashboard looks nice, but what does it mean? towards making meaning explicit in learning analytics design	en_US
dc.type	Conference Proceeding
utslib.for	0803 Computer Software	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/DVC (Teaching and Learning)
pubs.organisational-group	/University of Technology Sydney/DVC (Teaching and Learning)/Connected Intelligence Centre
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

© 2017 Association for Computing Machinery. All rights reserved. As learning analytics (LA) systems become more common, teachers and students are often required to not only make sense of the user interface (UI) elements of a system, but also to make meaning that is pedagogically appropriate to the learning context. However, we suggest that the dominant way of thinking about the relationship between representation and meaning results in an overemphasis on the UI, and that re-thinking this relationship is necessary to create systems that can facilitate deeper meaning making. We propose a conceptual view as a basis for discussion among the LA and HCI communities around a different way of thinking about meaning making, specifically that it should be explicit in the design process, provoking greater consideration of system level elements such as algorithms, data structures and information flow. We illustrate the application of the conceptualisation with two cases of LA design in the areas of Writing Analytics and Multi-modal Dashboards.

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http://hdl.handle.net/10453/127315