Towards Proximity Tracking and Sensemaking for Supporting Teamwork and Learning

Martinez-Maldonado, R; Yacef, K; Santos, ADPD; Shum, SB; Echeverria, V; Santos, OC; Pechenizkiy, M

Towards Proximity Tracking and Sensemaking for Supporting Teamwork and Learning

Martinez-Maldonado, R

Yacef, K Santos, ADPD Shum, SB

Echeverria, V

Santos, OC Pechenizkiy, M

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Publication Type:: Conference Proceeding
Citation:: Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017, 2017, pp. 89 - 91
Issue Date:: 2017-08-03

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Field	Value	Language
dc.contributor.author	Martinez-Maldonado, R https://orcid.org/0000-0002-8375-1816	en_US
dc.contributor.author	Yacef, K	en_US
dc.contributor.author	Santos, ADPD	en_US
dc.contributor.author	Shum, SB https://orcid.org/0000-0002-6334-7429	en_US
dc.contributor.author	Echeverria, V https://orcid.org/0000-0002-2022-9588	en_US
dc.contributor.author	Santos, OC	en_US
dc.contributor.author	Pechenizkiy, M	en_US
dc.date.issued	2017-08-03	en_US
dc.identifier.citation	Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017, 2017, pp. 89 - 91	en_US
dc.identifier.isbn	9781538638705	en_US
dc.identifier.uri	http://hdl.handle.net/10453/126834
dc.description.abstract	© 2017 IEEE. A large number of learning tools offering some sort of personalisation features rely mainly on the analysis of logged interactions between students and particular user interfaces. Much less attention has been given to the analysis of physical aspects so often present in 'traditional' intellectual tasks, although these are both important in the full development of a life-long learner. This paper (1) discusses existing literature focused on supporting learning using proximity and location analytics and sensors, and, based on this, (2) illustrates the feasibility and potential of these analytics for teaching and learning through an study in the context of proximity and location analytics in a team-based health simulation classroom.	en_US
dc.relation.ispartof	Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017	en_US
dc.relation.isbasedon	10.1109/ICALT.2017.79	en_US
dc.title	Towards Proximity Tracking and Sensemaking for Supporting Teamwork and Learning	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0806 Information Systems	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	closed_access
pubs.publication-status	Published	en_US

Abstract:

© 2017 IEEE. A large number of learning tools offering some sort of personalisation features rely mainly on the analysis of logged interactions between students and particular user interfaces. Much less attention has been given to the analysis of physical aspects so often present in 'traditional' intellectual tasks, although these are both important in the full development of a life-long learner. This paper (1) discusses existing literature focused on supporting learning using proximity and location analytics and sensors, and, based on this, (2) illustrates the feasibility and potential of these analytics for teaching and learning through an study in the context of proximity and location analytics in a team-based health simulation classroom.

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http://hdl.handle.net/10453/126834