Text input error categorisation: solving character level insertion ambiguities using Zero Time analysis

Authors:
Akiyo Kano;Janet C. Read
Affiliations:
University of Central Lancashire, Preston, England;University of Central Lancashire, Preston, England
Venue:
Proceedings of the 23rd British HCI Group Annual Conference on People and Computers: Celebrating People and Technology
Year:
2009

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Abstract

A review of literature on text input error categorisation revealed the need for a formal method to assist in solving ambiguities. This paper proposes a method of solving one such set of ambiguities, those caused by insertion of an extra letter. The method uses two rules: the Zero Time rule and Impossible NT/CT-Mu rule to establish whether the extra letter was inserted with another letter, or inserted individually. The method was applied to two large studies conducted to gather typing errors from students and children. The results show that the method is able to solve 100% of all insertion-only ambiguities and in doing so it helps reduce ambiguities in 75--85% of the remaining ambiguities.