Storyboard-Based Empirical Modeling of Touch Interface Performance

Alix Goguey (1) , Géry Casiez (2, 3, 4) , Andy Cockburn (5) , Carl Gutwin (1)

1 U of S - University of Saskatchewan [Saskatoon, Canada]
2 CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189
3 Université de Lille
4 LOKI - Technology and knowledge for interaction
5 University of Canterbury [Christchurch]

Touch interactions are now ubiquitous, but few tools are available to help designers quickly prototype touch interfaces and predict their performance. For rapid prototyping, most applications only support visual design. For predictive modelling, tools such as CogTool generate performance predictions but do not represent touch actions natively and do not allow exploration of different usage contexts. To combine the benefits of rapid visual design tools with underlying predictive models, we developed the Storyboard Empirical Modelling tool (StEM) for exploring and predicting user performance with touch interfaces. StEM provides performance models for mainstream touch actions, based on a large corpus of realistic data. Our tool provides new capabilities for exploring and predicting touch performance, even in the early stages of design. This is the demonstration of our accompanying paper.

Mots clés: Touch interaction; Modelling; Performance prediction

Domaines: Interface homme-machine [cs.HC]

Alix Goguey, Géry Casiez, Andy Cockburn, Carl Gutwin. Storyboard-Based Empirical Modeling of Touch Interface Performance. Adjunct Proceedings of the ACM Conference on Human Factors in Computing Systems (CHI 2018), Demonstration, Apr 2018, Montreal, Canada. ⟨10.1145/3170427.3186479⟩. ⟨hal-01736699⟩