TTracker: Using finger detection to improve touch typing training

Kollie, Elvin, Loizides, Fernando ORCID: https://orcid.org/0000-0003-0531-6760, Hartley, Thomas and Worrallo, Adam 2017. TTracker: Using finger detection to improve touch typing training. Presented at: 16th IFIP TC 13 International Conference, Mumbai, India, 25-29 September 2017. Published in: Bernhaupt, R., Dalvi, G., Joshi, A., Balkrishan, D.K., O’Neill, J. and Winckler, M. eds. Human-Computer Interaction – INTERACT 2017. Lecture Notes in Computer Science , vol.10516 Cham: Springer, pp. 469-472. 10.1007/978-3-319-68059-0_53

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Abstract

Touch typing software teaches a user to use the correct finger combinations with the correct keyboard buttons. The ultimate goal is to teach the typist to type faster, more accurately and ergonomically correct. Our research presents the working prototype of a software and hardware setup that tracks not only the speed and accuracy of the correct buttons being pressed but also which fingers are used to press them; a dimension of training that has previously not been integrated into touch typing tutorials. We use novel technology (leap motion) to detect the accurate interaction between the user and the keyboard, giving precise feedback to the user in order for him or her to improve.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	Springer
ISBN:	978-3-319-68059-0
ISSN:	0302-9743
Last Modified:	23 Oct 2022 12:46
URI:	https://orca.cardiff.ac.uk/id/eprint/108657

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