DocumentCode
538613
Title
AQUIRE: Applied qualitative use of interrelated entities — Methodology for analysing qualitative data in HCI
Author
Tripathi, Shivendra
Author_Institution
ABB Corp. Res., Bangalore, India
fYear
2010
fDate
Nov. 29 2010-Dec. 1 2010
Firstpage
1
Lastpage
6
Abstract
Industrial software user experience research tends to use more qualitative research in order to gain much knowledge about their users. There are number of analysis techniques originated from other domains like social science and psychology, available to analyse the qualitative dataset gathered during field studies. Human Computer Interaction researchers have tried and using some or combination of those techniques. Since these techniques have evolved basically in academia research, it offers a rigorous process and needs certain level of expertise in using them. In industrial software user experience research, where research projects are very much applied in nature and having shorter project life cycle, often putting difficulties before the practitioners in using that rigorous analysis process. This paper presents an innovative, simple to use and systematic way of analyzing qualitative data set in shorter period of time. The presented methodology uses applied qualitative use of interrelated entities gathered in terms of narrative data set for analysing the results.
Keywords
data analysis; human computer interaction; AQUIRE; HCI; applied qualitative use of interrelated entities; human computer interaction; industrial software user experience research; qualitative data analysis; usability; Context; Data analysis; Human computer interaction; Interviews; Probes; Tagging; Usability; Analytical model; Data analysis; Human Computer Interaction; Human factors; Man machine system; User centred design;
fLanguage
English
Publisher
ieee
Conference_Titel
Power, Control and Embedded Systems (ICPCES), 2010 International Conference on
Conference_Location
Allahabad
Print_ISBN
978-1-4244-8543-7
Type
conf
DOI
10.1109/ICPCES.2010.5698678
Filename
5698678
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