Using fuzzy coding with qualitative data: example with subjective data in human-computer interaction

ABSTRACT

This article shows the role that fuzzy sets may play in the prospect of analysing qualitative data. To underline this role, a human-computer interaction (HCI) study is presented. The data coming from 20 experts concerns their judgment regarding 33 questions related to the use of HCI approaches in order to support interactive system development phases. Each response scale features three main modalities, that is Agree, Partially agree and Disagree. The dataset example is analysed using multiple correspondence analysis (MCA) with both crisp and fuzzy coding models where the intermediate modality, Partially agree, is removed and considered with ½ membership values to the two extreme modalities. A comparative analysis is performed and the discussion states the interest of fuzzy coding with several kinds of qualitative factors or measurement variables. With qualitative measurement variables (our example), the main drawback of fuzzy coding could be the information loss, which is counterbalanced by the possibility of having fewer modalities and therefore of simplifying the multivariate analysis.

KEYWORDS:

• Fuzzy sets
• multiple correspondence analysis
• questionnaire
• qualitative data
• human-computer interaction

Acknowledgements

The authors would like to acknowledge the financial support granted by CAPES – Science without Borders Program. They also thank the experts who participated in this study, and the anonymous reviewers for their constructive remarks.

Additional information

Notes on contributors

Pierre Loslever

Pierre Loslever has a Ph.D. degree in automatics for industrial and human systems from the Université Polytechnique Hauts-de-France (France) and is a Professor in Valenciennes at the engineering school ENSIAME. He is a member of the LAMIH (Laboratory of Industrial and Human-Automation, Mechanics, and Computer Science). He primarily teaches courses in data analysis related domains, such as Signals and Systems, Statistics, Maintenance or Quality management. His research focuses mainly on human component systems studies with aspects such as ergonomics or biomechanics.

Taisa Guidini Gonçalves

Taisa Guidini Gonçalves received her Ph.D. degree in computer science from the LAMIH CNRS UMR 8201—Université Polytechnique Hauts-de-France (France) in 2017, and her M.Sc. degree in computer science (software engineering) from the Federal University of Rio de Janeiro in 2014. She specializes in Human-Computer Interaction and integration of HCI models and tools in Software Engineering models, particularly in the CMMI-DEV model.

Káthia Marçal de Oliveira

Káthia Marçal de Oliveira is an associate professor at the Université Polytechnique Hauts-de-France (France) and a member of the ‘INTERaction and Agents’ research group in the LAMIH. She has a Ph.D. in software engineering focused on quality assurance. She works on the integration of Human-Computer Interaction and software engineering issues.

Christophe Kolski

Christophe Kolski is a Professor in computer science at the Université Polytechnique Hauts-de-France (France) and a member of the ‘INTERaction and Agents’ research group in the LAMIH. He specializes in human-computer interaction, software engineering for interactive system design and evaluation, and adaptive and tangible user interface.