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An Information Taxonomy for Remotely-Accessible Engineering Instructional Laboratories

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2015 ASEE Annual Conference & Exposition


Seattle, Washington

Publication Date

June 14, 2015

Start Date

June 14, 2015

End Date

June 17, 2015





Conference Session

Emerging Computing and Information Technologies I

Tagged Division

Computing & Information Technology

Page Count


Page Numbers

26.188.1 - 26.188.19



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Paper Authors


Steven Walter Tuttle University of Technology Sydney

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Steve Tuttle was transplanted from Orange County California to Sydney Australia to chase his PhD in Software Engineering. In a parallel life, Steve builds web information systems for corporate clients, rides a kiteboard when the wind blows, juggles when it does not, and otherwise hangs out with his dog Lucie. The stuff one hears about the high quality of life in Sydney? All true!

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Bruce Moulton University of Technology Sydney


David Lowe The University of Sydney

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Professor David Lowe is Associate Dean (Education) and Professor of Software Engineering in the Faculty of Engineering and Information Technologies at The University of Sydney. Before this he was a Director of the Centre for Real-Time Information Networks (CRIN) - a designated research strength at the University of Technology, Sydney focused on blending embedded systems and telecommunications in addressing real-world problems. He is also the CEO of the not-for-profit organisation The LabShare Institute, and past President of the Global Online Laboratory Consortium. Professor Lowe has published widely during his more than 20 year teaching career, including three textbooks.

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An Information Taxonomy for Remote Engineering Instructional LaboratoriesThis paper introduces an information taxonomy for remote engineering instructionallaboratories. A taxonomy within some given domain organizes and clarifies the domaincontent and provides a common framework that supports and facilitates thinking, discussion,and communication about the domain in question. In this case, the taxonomy aims to supportthinking, discussion, and communication about remote engineering instructional laboratories.This taxonomy was emergent from peer-reviewed remote laboratories literature. Twenty-fivepapers were initially selected and close-read for terms which were characteristicallydescriptive of a remote engineering instructional laboratory. Over 1,000 such terms wereidentified. This number was reduced to some 800 through the elimination of duplicates andthe conflation of equivalents. These 800 were then examined, line-item by line-item andplaced into a containing category. If a an appropriate containing category did not exist, onewas created. In the end, there were 37 containing categories to hold all the terms.Five additional remote labs papers were then selected and close read for terms that weredescriptively characteristic of remote engineering instructional laboratories. As like before,these terms were then considered, line-item by line-item, an placed in a containing category.No additional containing categories were required during this follow on phase, indicating thatcategorical saturation was achieved. Four top level categories were added to the 37containers; effectively creating an information taxonomy for remote engineering instructionallaboratories. This taxonomy can then be used to foster thinking and discussioncommunication about these laboratories.Table 1: A Remote Laboratory Information TaxonomyTop Category Term Containeraccess access control access to people access to resources accessibilityorganizational administration change community enrollment expense income location sharingteaching and learning assessment collaboration communication data disciplines experiments learning aids pedagogy student benefits teacher benefits visualizationtechnical architecture booking capabilities devices equipment framework interface management safety scalability security software support technologies

Tuttle, S. W., & Moulton, B., & Lowe, D. (2015, June), An Information Taxonomy for Remotely-Accessible Engineering Instructional Laboratories Paper presented at 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.23527

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