Subventions et des contributions :

Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023)

The long-term goal of this research program is to dramatically improve user performance with touch interfaces . Touch interaction is now ubiquitous, but current touch interfaces are severely limited in their support for expertise - unlike more traditional settings that provide shortcuts like hotkeys or command languages. Touch is easy for novices to learn, but the range and expressiveness of touch interfaces is less than traditional desktop systems. The problem is that current touch interfaces have a strong focus on visual direct manipulation; and although this approach has good explorability, it has a low performance ceiling. Therefore, as users become increasingly familiar with the interface, they must continue to work in a "beginner mode" interface designed for novices. As computation increasingly moves to touch-based interfaces, and as applications on touch devices become more complex (e.g., full office suites, 3D modeling tools, real-time multi-player games), it is critical to address the limitations of current interfaces and raise the performance ceiling for touch – enabling expert interaction and greatly increasing user performance and satisfaction. We propose three main objectives:
Objective 1 : Understand Expertise by quantifying the role of task, guidance, and usage context on performance with expert interaction techniques and touch devices.
Studies of expert interaction techniques typically do not include real-world factors in performance evaluations, leading to a limited understanding of the comparative performance of different techniques and different approaches to supporting transitions from novice to expert. We will carry out several studies to test the effects of three important factors (task differences, guidance during initial use, and usage context) on expertise development and performance ceilings in realistic use.
Objective 2 : Predict Expertise by developing predictive models of touch performance and expertise development.
Predictive models play a valuable role in HCI – they allow researchers to explore much larger areas of a design space and they enable new techniques that exploit the model. We will develop models of touch expertise in three areas: models of performance and retention of multitouch commands; models of errors in spatial touch techniques; and models of user willingness to use expert techniques.
Objective 3 : Exploit Expertise by developing and evaluating specific techniques with higher performance ceilings.
There is great potential for new techniques that exploit the approaches proposed above to raise performance ceilings for touch interaction. We will develop several new techniques that combine touch input with other modalities, and that increase the expressive power of touch using spatial organization. These techniques will be evaluated in a variety of task and usage scenarios to fully explore their capabilities and limitations.