It Does Not Fitts My Data! Analysing Large Amounts of Mobile Touch Data

Abstract : Touchscreens are the dominant input device for smartphones and learning about smartphone users’ touch behaviour became even more important. We developed a game for Android phones to collect a truly large amount of touch data from diverse devices and players. A part of the game is designed as what we expected to be a Fitts’ law task. By publishing the game in the Android Market we collected 5,359,650 micro tasks from 63,154 installations of the game. Using Fitts’ law to find a model for these tasks we found a very weak correlation and an implausible high index of performance across different devices. Further analysis shows a similar correlation between time and distance as with Fitts’ law but only a very weak correlation with the targets’ width.
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Communication dans un congrès
Pedro Campos; Nicholas Graham; Joaquim Jorge; Nuno Nunes; Philippe Palanque; Marco Winckler. 13th International Conference on Human-Computer Interaction (INTERACT), Sep 2011, Lisbon, Portugal. Springer, Lecture Notes in Computer Science, LNCS-6949 (Part IV), pp.564-567, 2011, Human-Computer Interaction – INTERACT 2011. 〈10.1007/978-3-642-23768-3_83〉
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Niels Henze, Susanne Boll. It Does Not Fitts My Data! Analysing Large Amounts of Mobile Touch Data. Pedro Campos; Nicholas Graham; Joaquim Jorge; Nuno Nunes; Philippe Palanque; Marco Winckler. 13th International Conference on Human-Computer Interaction (INTERACT), Sep 2011, Lisbon, Portugal. Springer, Lecture Notes in Computer Science, LNCS-6949 (Part IV), pp.564-567, 2011, Human-Computer Interaction – INTERACT 2011. 〈10.1007/978-3-642-23768-3_83〉. 〈hal-01596905〉

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