EAGER: Cognitive modeling of strategies for dealing with errors in mobile touch interfaces

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Touch interfaces on mobile phones and tablets are notoriously error prone. One plausible reason for slow progress in improving the usability of touchscreen devices is that research and design efforts in human-computer interaction take a relatively narrow focus on identifying, understanding, and eliminating human error, focusing primarily on the specific individual touch interactions rather than the broader task knowledge that a person needs to use a device to do a real-world task. This project takes a different perspective, suggesting that usage errors represent breakdowns in a person's efforts to adapt to the complexity of the tasks and devices, and that many of these problems can be traced to interface designers not inadequately considering the cognitive task knowledge that a user will need to do a task. Many touchscreen design guidelines are arbitrary and based on common practice and established user expectations. This project aims to change the shape of research and practice for touch interaction on mobile devices by introducing sound scientific principles of cognitive task analysis and error analysis to the design and analysis of such interfaces. This project could benefit society by dramatically improving the user interface design of touchscreen interfaces.The project will develop cognitive models, which are computer programs that behave in some way like humans. The project will specifically develop cognitive models of touch interaction that could be used by designers when designing new touchscreen interfaces, to identify where users are likely to encounter problems with the new interface. The project includes three stages. The first stage will develop a small set of instrumented interfaces on mobile platforms to collect human data for error-prone tasks. The experiments will examine the variation of the probability of error at specific points during a sequence, the visual feedback provided for specific actions, and the user knowledge of error recovery and avoidance actions. The second stage will follow other successful efforts in cognitive modeling to analyze user data from our exploratory experiment with the goal of developing a representation of the strategies we have observed. An automated process will explore a search space of plausible cognitive strategies to identify models that explain the performance data collected during the first stage. The third stage will validate the hypotheses pertaining to the cognitive strategies that contribute to the successful and unsuccessful use of touchscreen devices that are established during the first two stages. The results will have much wider implications than current models of touch accuracy (which produce little more than target size and spacing guidelines) by focusing on the bigger picture of expertise and failure. The project takes a large step into the cognitive modeling of pervasive but not-yet-unexplored interface problems.