Novice and Expert Performance of KeyScretch: A Gesture-Based Text Entry Method for Touch-Screens

Abstract

KeyScretch is a text entry method for devices equipped with touch-screens, based on a menu-augmented soft keyboard. In these keyboards, a menu containing a small number of frequent characters is shown, while a key is pressed, allowing further character entry by menu selection. KeyScretch improves the previously studied menu-based methods by enabling the interpretation of compound strokes, which allow the input of text chunks longer than two characters. The performance of the method is analyzed on different kinds of touch-screens: First, we present a 25-session user study on a stylus-based device, showing that an instance of the method optimized for Italian can be learned in a reasonable time by the users and significantly outperforms the traditional method based on the tapping interaction. Then, we define and validate a model for predicting expert text entry rates on finger-based devices. The predicted rates for instances of KeyScretch optimized for different Western languages vary from about 44-50 words/min on the Qwerty layout, enabling improvements in the range of 30-49% as compared with the traditional method.