Biblio

In this work we explore how different cognitive processes affected typing patterns through a computer game we call The Typing Game. By manipulating the players' familiarity with the words in our game through their similarity to dictionary words, and by allowing some players to replay rounds, we found that typing speed improves with familiarity with words, and also with practice, but that these are independent of the number of mistakes that are made when typing. We also found that users who had the opportunity to replay rounds exhibited different typing patterns even before replaying the rounds.

In this work we explore how different cognitive processes affected typing patterns through a computer game we call The Typing Game. By manipulating the players' familiarity with the words in our game through their similarity to dictionary words, and by allowing some players to replay rounds, we found that typing speed improves with familiarity with words, and also with practice, but that these are independent of the number of mistakes that are made when typing. We also found that users who had the opportunity to replay rounds exhibited different typing patterns even before replaying the rounds.

Typing is a human activity that can be affected by a number of situational and task-specific factors. Changes in typing behavior resulting from the manipulation of such factors can be predictably observed through key-level input analytics. Here we present a study designed to explore these relationships. Participants play a typing game in which letter composition, word length and number of words appearing together are varied across levels. Inter-keystroke timings and other higher order statistics (such as bursts and pauses), as well as typing strategies, are analyzed from game logs to find the best set of metrics that quantify the effect that different experimental factors have on observable metrics. Beyond task-specific factors, we also study the effects of habituation by recording changes in performance with practice. Currently a work in progress, this research aims at developing a predictive model of human typing. We believe this insight can lead to the development of novel security proofs for interactive systems that can be deployed on existing infrastructure with minimal overhead. Possible applications of such predictive capabilities include anomalous behavior detection, authentication using typing signatures, bot detection using word challenges etc.