The Multimodal Matrix as a Quantitative Ethnography Methodology

Buckingham Shum, S; Echeverria, V; Martinez-Maldonado, R

The Multimodal Matrix as a Quantitative Ethnography Methodology

Buckingham Shum, S

Echeverria, V

Martinez-Maldonado, R

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Publication Type:: Conference Proceeding
Citation:: Communications in Computer and Information Science, 2019, 1112 pp. 26 - 40
Issue Date:: 2019-01-01

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Field	Value	Language
dc.contributor.author	Buckingham Shum, S 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	Martinez-Maldonado, R	en_US
dc.date.issued	2019-01-01	en_US
dc.identifier.citation	Communications in Computer and Information Science, 2019, 1112 pp. 26 - 40	en_US
dc.identifier.isbn	9783030332310	en_US
dc.identifier.issn	1865-0929	en_US
dc.identifier.uri	http://hdl.handle.net/10453/138055
dc.description.abstract	© Springer Nature Switzerland AG 2019. This paper seeks to contribute to the emerging field of Quantitative Ethnography (QE) by demonstrating its utility to solve a complex challenge in Learning Analytics: the provision of timely feedback to collocated teams and their coaches. We define two requirements that extend the QE concept in order to operationalise it such a design process, namely, the use of co-design methodologies, and the availability of automated analytics workflow to close the feedback loop. We introduce the Multimodal Matrix as a data modelling approach that can integrate theoretical concepts about teamwork with contextual insights about specific work practices, enabling the analyst to map between higher order codes and low-level sensor data, with the option add the results of manually performed analyses. This is implemented in software as a workflow for rapid data modelling, analysis and interactive visualisation, demonstrated in the context of nursing teamwork simulations. We propose that this exemplifies how a QE methodology can underpin collocated activity analytics, at scale, with in-principle applications to embodied, collocated activities beyond our case study.	en_US
dc.relation.ispartof	Communications in Computer and Information Science	en_US
dc.relation.isbasedon	10.1007/978-3-030-33232-7_3	en_US
dc.title	The Multimodal Matrix as a Quantitative Ethnography Methodology	en_US
dc.type	Conference Proceeding
utslib.citation.volume	1112	en_US
utslib.for	1302 Curriculum and Pedagogy	en_US
utslib.for	0802 Computation Theory and Mathematics	en_US
utslib.for	0804 Data Format	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)
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	1112	en_US

Abstract:

© Springer Nature Switzerland AG 2019. This paper seeks to contribute to the emerging field of Quantitative Ethnography (QE) by demonstrating its utility to solve a complex challenge in Learning Analytics: the provision of timely feedback to collocated teams and their coaches. We define two requirements that extend the QE concept in order to operationalise it such a design process, namely, the use of co-design methodologies, and the availability of automated analytics workflow to close the feedback loop. We introduce the Multimodal Matrix as a data modelling approach that can integrate theoretical concepts about teamwork with contextual insights about specific work practices, enabling the analyst to map between higher order codes and low-level sensor data, with the option add the results of manually performed analyses. This is implemented in software as a workflow for rapid data modelling, analysis and interactive visualisation, demonstrated in the context of nursing teamwork simulations. We propose that this exemplifies how a QE methodology can underpin collocated activity analytics, at scale, with in-principle applications to embodied, collocated activities beyond our case study.

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http://hdl.handle.net/10453/138055