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Designing expressive interaction techniques for novices inspired by expert activities : the case of musical practice

As interactive systems are now used to perform a variety of complex tasks, users need systems that are at the same time expressive, efficient and usable. Although simple interactive systems can be easily usable, interaction designers often consider that only expert practitioners can benefit from the expressiveness of more complex systems. Our approach, inspired by studies in phenomenology and psychology, underscores that non-experts have sizeable knowledge and advanced skills related to various expert activities having a social dimension -such as artistic activities-, which they gain implicitly through their engagement as perceivers. For example, we identify various music-related skills mastered by non-musicians, which they gain when listening to music or attending performances. We have two main arguments. First, interaction designers can reuse such implicit knowledge and skills to design interaction techniques that are both expressive and usable by novice users. Second, as expert artifacts and expert learning methods have evolved over time and have shown efficient to overcome the complexity of expert activities, they can be used as a source of inspiration to make expressive systems more easily usable by novice users. We provide a design framework for studying the usability and expressiveness of interaction techniques as two new aspects of the user experience, and explore this framework with three projects. In the first project we study the use of rhythmic patterns as an input method, and show that novice users are able to reproduce and memorize large vocabularies of patterns. This is made possible by the natural abilities of non-musicians to perceive, reproduce and make sense of rhythmic structures. We define a method to create expressive vocabularies of patterns, and show that novice users are able to efficiently use them as command triggers. In the second project, we study the design and learning of chording gestures on multitouch screens. We introduce design guidelines to create expressive chord vocabularies taking the mechanical constraints and the degrees of freedom of the human hand into account. We evaluate the usability of such gestures in an experiment and we present an adapted learning method inspired by the teaching of chords in music. We show that novice users are able to reproduce and memorize our vocabularies of chording gestures, while our learning method can improve long-term memorization. The final project focuses on music software used for live performances and proposes a framework for designing "instrumental" software allowing expert musical playing and having its elementary functionalities accessible to novices, as it is the case with acoustic instruments (for example, one can easily play a few chords on a piano without practice). We define a design framework inspired by a functional decomposition of acoustic instruments and present an adapted software architecture, both aiming to ease the design of such software and to make it match with instrument-making. These projects show that, in these cases: (i) the implicit knowledge novices have about some expert activities can be reused for interaction; (ii) expert learning methods can inspire ways to make expressive systems more usable novices; (iii) taking expert artifacts as a source of inspiration can help creating usable and expressive interactive systems. In this dissertation, we propose the study of usability as an alternative to the focus on immediacy that characterizes current commercial interactive systems. We also propose methods to benefit from the richness of expert activities and from the implicit knowledge of non-experts to design interactive systems that are at the same time expressive and usable by novice users.

Identiferoai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-00839850
Date17 December 2012
CreatorsGhomi, Emilien
PublisherUniversité Paris Sud - Paris XI
Source SetsCCSD theses-EN-ligne, France
LanguageEnglish
Detected LanguageEnglish
TypePhD thesis

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