Gregory Francis1, Claire Oxtoby. 1. Department of Psychological Sciences, Purdue University, West Lafayette, Indiana 47907-2004, USA. gfrancis@psych.purdue.edu
Abstract
OBJECTIVE: We explore how to optimally design systems for information input. BACKGROUND: As computers are introduced into ever more devices with new methods of inputting information, there is a need for specialized systems that are optimally designed for their particular use. METHOD: The study demonstrates how to use a model of text entry times to build optimized keyboards for specific sets of text. The technique is demonstrated by using Fitts' law to model text entry times. Alphabet letters are assigned to keys in a way that minimizes predicted entry time for the specified set of text. The predicted entry times are validated by an experiment in which two keyboards are optimized for different sets of text. RESULTS: Text entry is faster for the keyboard optimized for that text compared with the keyboard optimized for the other text. Learning to use the keyboards is fairly quick, with significant learning being observed after only one half-hour session. CONCLUSION: There is a need and an ability to design specialized keyboards for some situations. The study demonstrates that optimization of keyboards can decrease text entry times. APPLICATION: This research shows how to design optimized keyboards for many different situations. The approach should be useful for aviation, medical, industrial, and other specialized situations in which normal keyboard designs cannot be used.
OBJECTIVE: We explore how to optimally design systems for information input. BACKGROUND: As computers are introduced into ever more devices with new methods of inputting information, there is a need for specialized systems that are optimally designed for their particular use. METHOD: The study demonstrates how to use a model of text entry times to build optimized keyboards for specific sets of text. The technique is demonstrated by using Fitts' law to model text entry times. Alphabet letters are assigned to keys in a way that minimizes predicted entry time for the specified set of text. The predicted entry times are validated by an experiment in which two keyboards are optimized for different sets of text. RESULTS: Text entry is faster for the keyboard optimized for that text compared with the keyboard optimized for the other text. Learning to use the keyboards is fairly quick, with significant learning being observed after only one half-hour session. CONCLUSION: There is a need and an ability to design specialized keyboards for some situations. The study demonstrates that optimization of keyboards can decrease text entry times. APPLICATION: This research shows how to design optimized keyboards for many different situations. The approach should be useful for aviation, medical, industrial, and other specialized situations in which normal keyboard designs cannot be used.