Designing intuitive interactions: Exploring performance and reflection measures

Abstract

Intuitive interactions are supported by users' implicit and explicit learning experiences. But, determining user knowledge can be difficult. With many options available for eliciting that knowledge, we tested the effectiveness of two methods - performance and reflection. Users were presented with simple interactions that had varying levels of intuitiveness (affordance, convention, bias). They were asked to perform the interaction or to describe how the interaction should be designed. These methods of knowledge elicitation produced inconsistent results; sometimes they produced the same result (affordance-based interactions), sometimes the opposite (convention-based interactions). Furthermore, when both methods were used, results obtained from the second measure were often contaminated by completion of the first measure. Carryover effects were present regardless of which measure was completed first. These results indicate that the method used to elicit knowledge should be selected based on the type of interaction that is being investigated and multiple measures should be used with caution.