Model-Based Self-Explanatory UIs for free, but are they valuable?

Part 1: Long and Short Papers (Continued)International audienceModel-Driven Engineering (MDE) has been extensively used for generating User Interfaces (UIs) from models. As long as these models are kept alive at runtime, the UIs are capable of adapting to variations of the context of use. This paper investigates a potentially powerful side effect: the possibility of enriching the UIs with explanations directly generated from these models. This paper first describes a software infrastructure that supports this generation of explanations. It then reports on a user study that evaluates the added value of such model based self-explanations

Explanations In Contextual Graphs: A Solution To Accountability In Knowledge Based Systems

In order for intelligent systems to be a viable and utilized tool, a user must be able to understand how the system comes to a decision. Without understanding how the system arrived at an answer, a user will be less likely to trust its decision. One way to increase a user\u27s understanding of how the system functions is by employing explanations to account for the output produced. There have been attempts to explain intelligent systems over the past three decades. However, each attempt has had shortcomings that separated the logic used to produce the output and that used to produce the explanation. By using the representational paradigm of Contextual Graphs, it is proposed that explanations can be produced to overcome these shortcomings. Two different temporal forms of explanations are proposed, a pre-explanation and a post-explanation. The pre-explanation is intended to help the user understand the decision making process. The post-explanation is intended to help the user understand how the system arrived at a final decision. Both explanations are intended to help the user gain a greater understanding of the logic used to compute the system\u27s output, and thereby enhance the system\u27s credibility and utility. A prototype system is constructed to be used as a decision support tool in a National Science Foundation research program. The researcher has spent the last year at the NSF collecting the knowledge implemented in the prototype system

Quality of Human-Computer Interaction : Self-Explanatory User Interfaces by Model-Driven Engineering

In Human-Computer Interaction, quality is an utopia. Despite all the design efforts, there are always uses and situations for which the user interface is not perfect. This thesis investigates self-explanatory user interfaces for improving the quality perceived by end users. The approach follows the principles of model-driven engineering. It consists in keeping the design models at runtime so that to dynamically enrich the user interface with a set of possible questions and answers. The questions are related to usage (for instance, "What's the purpose of this button?", "Why is this action not possible"?) as well as to design rationale (for instance, "Why are the items not alphabetically ordered?"). This thesis proposes a software infrastructure UsiExplain based on the UsiXML metamodels. An evaluation conducted on a case study related to a car shopping webiste confirms that the approach is relevant especially for usage questions. Design rationale will be further explored in the future.STAREn Interaction Homme-Machine, la qualité est une utopie : malgré toutes les précautions prises en conception, il existe toujours des utilisateurs et des situations d'usage pour lesquels l'Interface Homme-Machine (IHM) est imparfaite. Cette thèse explore l'auto-explication des IHM pour améliorer la qualité perçue par les utilisateurs. L'approche s'inscrit dans une Ingénierie Dirigée par les Modèles. Elle consiste à embarquer à l'exécution les modèles de conception pour dynamiquement augmenter l'IHM d'un ensemble de questions et de réponses. Les questions peuvent être relatives à l'utilisation de l'IHM (par exemple, "A quoi sert ce bouton ?", "Pourquoi telle action n'est pas possible ?) et à sa justification (par exemple, "Pourquoi les items ne sont-ils pas rangés par ordre alphabétique ?"). Cette thèse propose une infrastructure logicielle UsiExplain basée sur les méta-modèles UsiXML. L'évaluation sur un cas d'étude d'achat de voitures montre que l'approche est pertinente pour les questions d'utilisation de l'IHM. Elle ouvre des perspectives en justification de conception