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RETROSPECTIVE CODING OF THE UX DESIGN PROCESS FOR UX DESIGN ENHANCEMENT IN DESIGN AGENCIES

Published online by Cambridge University Press:  19 June 2023

Benoît Dabouis ,
Vincent Boccara  and
Bernard Yannou
Benoît Dabouis*
Affiliation:
Style & Design, Maurepas, France; Université Paris-Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique, Orsay, France; Université Paris-Saclay, CentraleSupélec, Laboratoire Genie Industriel, Gif-sur-Yvette, France
Vincent Boccara
Affiliation:
Université Paris-Saclay, CNRS, Laboratoire Interdisciplinaire des Sciences du Numérique, Orsay, France;
Bernard Yannou
Affiliation:
Université Paris-Saclay, CentraleSupélec, Laboratoire Genie Industriel, Gif-sur-Yvette, France
*
Dabouis, Benoît, Style & Design, France, [email protected]

Abstract

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User Experience is becoming an increasing centre of interest both in the academic and industrial worlds. Design agencies are no strangers to this phenomenon and are willing to shift from product-oriented design toward user experience design. However, their design process is often loose which may explain a lack of final UX quality or proof of quality, and does not allow to diagnose misuses and improvement opportunities due to a lack of UX formulation and traceability. We propose in this paper to retrospectively represent a design project and its specified, designed and validated UX, in the perspective to conduct a posterior collective diagnosis of UX design in a design agency. The proposed representation model is used to analyse one design project. Results show that only a few UX traces are found in the presented project, and that many dimensions are not considered (like perceptions or affects). Finally, we discuss the next steps of this tool's deployment to create a shared mental model of the design process among the design players.

Keywords

Design processProcess representation modelExperience designDesign practice
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 3105 - 3114
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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