ABSTRACT
Disabled individuals who cannot use a standard keyboard require a special interface in order to use a computer. The GOMS model is used here to quantitatively evaluate three interfaces currently used in computer access systems for handicapped people. Each interface uses a row/column scanning technique for letter selection, and two of the interfaces employ word prediction in an attempt to improve text input rate. Techniques for modeling these interfaces are presented, and the resulting predictions for performance time, learning time, and working memory requirements are discussed. The models predict that the systems with word prediction actually have lower performance than one that allows only single letter selections. Factors contributing to this result include additional mental operators required for use of the word predictive interfaces and an insufficient probability of successful word prediction.
