Taming Wild Behavior: The Input Observer for Obtaining Text Entry and Mouse Pointing Measures from Everyday Computer Use

We present the Input Observer, a tool that can run quietly in the background of users’ computers and measure their text entry and mouse pointing performance from everyday use. In lab studies, participants are presented with prescribed tasks, enabling easy identification of speeds and errors. In everyday use, no such prescriptions exist. We devised novel algorithms to segment text entry and mouse pointing input streams into “trials.” We are the first to measure errors for unprescribed text entry and mouse pointing. To measure errors, we utilize web search engines, adaptive offline dictionaries, an Automation API, and crowdsourcing. Capturing errors allows us to employ Crossman’s (1957) speed-accuracy normalization when calculating Fitts’ law throughputs. To validate the Input Observer, we compared its measures from 12 participants over a week of computer use to the same participants’ results from a lab study. Overall, in the lab and field, average text entry speeds were 74.47 WPM and 80.59 WPM, respectively. Average uncorrected error rates were near zero, at 0.12% and 0.28%. For mouse pointing, average movement times were 971 ms and 870 ms. Average pointing error rates were 4.42% and 4.66%. Average throughputs were 3.48 bits/s and 3.45 bits/s. Device makers, researchers, and assistive technology specialists may benefit from measures of everyday use. Author