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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© 2011 IFIP International Federation for Information Processing
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Henze, N., Boll, S. (2011). It Does Not Fitts My Data! Analysing Large Amounts of Mobile Touch Data. In: Campos, P., Graham, N., Jorge, J., Nunes, N., Palanque, P., Winckler, M. (eds) Human-Computer Interaction – INTERACT 2011. INTERACT 2011. Lecture Notes in Computer Science, vol 6949. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23768-3_83
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DOI: https://doi.org/10.1007/978-3-642-23768-3_83
Publisher Name: Springer, Berlin, Heidelberg
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