Resume Introduction Alors que l’evaluation de l’experience utilisateur (UX) est au cœur des preoccupations dans le domaine des interactions homme–machine, aucun outil d’evaluation auto-administre valide de l’UX n’existe actuellement en langue francaise. Le questionnaire AttrakDiff 2 (Hassenzahl, Burmester, & Koller, 2003) est un outil d’evaluation de l’UX qui repose sur un modele theorique distinguant qualites pragmatiques et qualites hedoniques des systemes interactifs. Objectif Cet article decrit la traduction et la validation de la version francaise du questionnaire AttrakDiff 2 en vue de son utilisation sur des echantillons de population francophone. Methode Suivant la methodologie de validation transculturelle proposee par Vallerand (1989), le questionnaire a ete traduit par des chercheurs trilingues puis a fait l’objet d’un processus de traduction renversee et d’une validation par un comite d’experts. Un pretest a ete effectue sur 26 participants. Les caracteristiques de la version francaise de l’AttrakDiff 2 ont ensuite ete evaluees par une etude quantitative en ligne sur un echantillon de 381 utilisateurs. Resultats Les resultats des analyses effectuees confirment la structure factorielle attendue en 3 facteurs et une bonne consistance interne des sous-echelles. Les liens entre les facteurs sont consistants avec le modele theorique d’Hassenzahl (2003) ou attributs pragmatiques et hedoniques percus se combinent pour former un jugement d’attractivite. Conclusion La presente version francaise de l’AttrakDiff 2 est globalement conforme a la version initiale allemande de l’outil et presente des niveaux de validite et de fidelite satisfaisants.

Création et validation d’une version française du questionnaire AttrakDiff pour l’évaluation de l’expérience utilisateur des systèmes interactifs

Smart mobile devices have fostered new interaction scenarios that demand sophisticated interfaces. The main developers of operating systems for such devices provide APIs for developers to implement their own applications, including different solutions for graphical interfaces, sensor control, and voice interaction. Despite the usefulness of such resources, there are no strategies defined for coupling the multimodal interface with the possibilities that the devices offer to identify and adapt to the user needs, which is particularly important in domains such as Ambient Assisted Living. In this paper, we propose a framework that allows developing context-aware multimodal conversational agents that dynamically incorporate user-specific requirements and preferences as well as characteristics about the interaction environment, in order to improve and personalize the service that is provided. Our proposal integrates the facilities of the Android API in a modular architecture that emphasizes interaction management and context-awareness to build user-adapted, robust and maintainable applications. As a proof of concept, we have used the proposed framework to develop an Android app for older adults suffering from Alzheimer's. The app helps them to preserve their cognitive abilities and enhance their relationship with their environment.

Mobile Conversational Agents for Context-Aware Care Applications

This book presents (1) an exhaustive and empirically validated taxonomy of quality aspects of multimodal interaction as well as respective measurement methods, (2) a validated questionnaire specifically tailored to the evaluation of multimodal systems and covering most of the taxonomys quality aspects, (3) insights on how the quality perceptions of multimodal systems relate to the quality perceptions of its individual components, (4) a set of empirically tested factors which influence modality choice, and (5) models regarding the relationship of the perceived quality of a modality and the actual usage of a modality.

An Evaluation Framework for Multimodal Interaction: Determining Quality Aspects and Modality Choice

In this paper, we review three experiments with a mobile application that integrates graphical input with a touch-screen and a speech interface and develop a model for input modality choice in multimodal interaction. The model aims to enable simulation of multimodal human-computer interaction for automatic usability evaluation. The experimental results indicate that modality efficiency and input performance are important moderators of modality choice. Accordingly, we establish a utility-driven model that provides probability estimations of modality usage, based on the parameters of modality efficiency and input performance. Four variants of the model that differ in training data are fitted by means of Sequential Least Squares Programming. The analysis reveals a considerable fit regarding averaged modality usage. When applied to individual modality usage profiles, the accuracy decreases significantly. In an application example it is shown how the modality choice mechanism can be deployed for simulating interaction in the field of automatic usability evaluation. Results and possible limitations are discussed. Decreased input performance of a specific modality, decreases the usage of this modality.Decreased efficiency of the GUI, increases VUI usage.A model predicting modality choice is proposed.The model can be deployed for automatic usability evaluation.System designers are provided with working knowledge about expected modality usage.

Modeling input modality choice in mobile graphical and speech interfaces

Smart mobile devices have fostered new learning scenarios that demand sophisticated interfaces. Multimodal conversational agents have became a strong alternative to develop human-machine interfaces that provide a more engaging and human-like relationship between students and the system. The main developers of operating systems for such devices have provided application programming interfaces for developers to implement their own applications, including different solutions for developing graphical interfaces, sensor control and voice interaction. Despite the usefulness of such resources, there are no strategies defined for coupling the multimodal interface with the possibilities that these devices offer to enhance mobile educative apps with intelligent communicative capabilities and adaptation to the user needs. In this paper, we present a practical m-learning application that integrates features of Android application programming interfaces on a modular architecture that emphasizes interaction management and context-awareness to foster user-adaptively, robustness and maintainability.

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Incorporating android conversational agents in m-learning apps

Usability evaluation is an indispensable issue during the development of new interfaces and interaction paradigms [1]. Although a wide range of reliable usability evaluation methods exists for graphical user interfaces, mature methods are rarely available for speech-based interfaces [2]. When it comes to multimodal interfaces, no standardized approach has so far been established. In previous studies [3], it was shown that usability questionnaires initially developed for unimodal systems may lead to unreliable results when applied to multimodal systems. In the current study, we therefore used several data sources (direct and indirect measurements) to evaluate two unimodal versions and one multimodal version of an information system. We investigated, to which extent the different data showed concordance for the three system versions. The aim was to examine, if, and under which conditions, common and widely used methods originally developed for graphical user interfaces are also appropriate for speech-based and multimodal intelligent interfaces.

/pdf/reliable-evaluation-of-multimodal-dialogue-systems-4ffepi0gmk.pdf

Reliable Evaluation of Multimodal Dialogue Systems

Usability evaluation of multimodal systems is a complex issue. Multimodal systems provide multiple channels to communicate with the system. Thus, the single modalities as well as their combination have to be taken into account. This paper aims to investigate how ratings of single modalities relate to the ratings of their combination. Therefore a usability evaluation study was conducted testing an information system in two unimodal versions and one multimodal version. Multiple linear regression showed that for overall and global judgments ratings of the single modalities are very good predictors for the ratings of the multimodal system. For separate usability aspects (e.g. hedonic qualities) the prediction was less accurate.

/pdf/usability-evaluation-of-multimodal-interfaces-is-the-whole-gtr4z8vsao.pdf

Stefan Schaffer

Papers

Reliable Evaluation of Multimodal Dialogue Systems

Usability Evaluation of Multimodal Interfaces: Is the Whole the Sum of Its Parts?

Usability-Evaluation multimodaler Schnittstellen: Ist das Ganze die Summe seiner Teile?