Exploring a Design Space of Graphical Adaptive Menus

Autor: Denis Chêne, Sara Bouzit, Gaëlle Calvary, Jean Vanderdonckt
Přispěvatelé: Université Catholique de Louvain = Catholic University of Louvain (UCL), Ingénierie de l’Interaction Homme-Machine (IIHM ), Laboratoire d'Informatique de Grenoble (LIG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Orange Labs [Meylan], Orange Labs, UCL - SSH/LouRIM - Louvain Research Institute in Management and Organizations, UCL - SST/ICTM/INGI - Pôle en ingénierie informatique
Rok vydání: 2019
Předmět:
Zdroj: ACM Transactions on Interactive Intelligent Systems
ACM Transactions on Interactive Intelligent Systems, Association for Computing Machinery (ACM), 2019, ⟨10.1145/3237190⟩
A C M Transactions on Interactive Intelligent Systems, Vol. 10, no. 1, p. Article 2 (January 2020)
ISSN: 2160-6463
2160-6455
DOI: 10.1145/3237190
Popis: Graphical Adaptive Menus are Graphical User Interface menus whose predicted items of immediate use can be automatically rendered in a prediction window. Rendering this prediction window is a key question for adaptivity to enable the end-user to efficiently differentiate predicted items from normal ones and to consequently select appropriate items. Adaptivity for graphical menus has been investigated more for normal screens, such as desktops, than for small screens, such as smartphones, where real estate imposes severe rendering constraints. To address this question, this article defines and explores a design space where graphical adaptive menus are structured based on Bertin’s eight visual variables (i.e., position, size, shape, value, color, orientation, texture, and motion) and their combination by comparing their rendering for small screens with respect to normal screens. Based on this design space, previously introduced graphical adaptive menus are revisited in terms of four stability properties (i.e., spatial, physical, format, and temporal), and new menu designs are introduced and discussed for both normal and small screens. The resulting set of graphical adaptive menu has been subject to a preference analysis from which a particular design emerged: the cloud menu, where predicted items are arranged in an adaptive tag cloud. We investigate empirically the effect of the cloud menu on the item selection time and the error rate with respect to a static menu and an adaptive linear menu. This article then suggests a set of usability guidelines for designers and practitioners to design graphical adaptive menus in general and cloud menus in particular.
Databáze: OpenAIRE