Consistency of Human-Computer Interface Design: Quantification and Validation

Abstract

Consistency in human-computer interaction tasks is usually considered in a transfer paradigm in which the higher the similarity between two tasks, the higher the transfer and consistency. In a different paradigm, when tasks are performed in alternating sequences, similarity of tasks means that the mapping of interface methods or rules to overall task goals will be varied. A neural network simulation demonstrated that the same two tasks could be considered consistent in a transfer paradigm but have low consistency when they are alternated. A model called text-editing method (TEM) was developed to quantify consistency between two tasks based upon replacement, insertion, or deletion of methods. Two experiments tested the predictions of the quantitative analyses of consistency for alternating tasks. The results confirmed that similarities of two tasks and, thus, variability in the mapping of methods to overall task goals could have a detrimental effect on performance when the two tasks were performed in an alternating sequence.