Understanding the noticeability and distraction of interactive highlighting techniques
Thesis DisciplineComputer Science
Degree GrantorUniversity of Canterbury
Degree NameDoctor of Philosophy
Highlighting techniques are a diverse class of visual communication techniques that make users aware of salient information in a timely manner. Any visual effect can potentially be used and manipulated to create highlighting effects given the right context, making the design space for highlighting techniques broad and rich. Although highlighting techniques are a common and important part of user interfaces, there is a lack of understanding about how to select, apply, and control their effects for achieving the best results. For example, designers need to balance some fundamental tradeoffs between ensuring that important/urgent information is able to capture the user’s attention (i.e. desired noticeability of a stimulus), while reducing the risk that the user’s attention is needlessly diverted away from their task (i.e. undesired distraction). However, the lack of understanding of how noticeability and distraction relate to each other, along with not knowing how we can manipulate the techniques to affect the balance between these complicates the design process.
To address this knowledge gap, this thesis provides contributions in three key areas: 1) A structured design framework for describing highlighting techniques in terms of their construction and control; 2) An empirical method and two experiment protocols for measuring both noticeability and distraction; and 3) Empirical data about the noticeability and distraction effects of highlighting techniques.
The first part of this thesis reviews current understanding of highlighting techniques, their effects, prior methods of measuring those effects, and underlying human factors. It also presents our new structured design framework – Parametric Control and Construction of Highlights (PCCH) – for describing highlighting techniques in a concise and objective way, using parameters to accurately specify highlighting technique configurations.
The second part of this thesis presents an empirical method for measuring both noticeability and distraction. This method was validated by conducting two user studies. In the first experiment, participants performed an abstract visual search task where they had to quickly drag a disk onto a cued target in the presence of 0/1/2 instances of four commonly-used highlighting techniques presented in different configurations. The second experiment was a dual-attention task where participants performed a dot-following task while detecting the appearance of highlighting techniques (in the form of AnimatedWindowBorders). Task performance, eye tracking, and subjective experience data from these experiments are presented and analysed. Noticeability and Distraction metrics were computed from Task Performance data.