Adding Context to Automated Text Input Error Analysis with Reference to Understanding How Children Make Typing Errors.
Doctoral thesis, University of Central Lancashire.
Despite the enormous body of literature studying the typing errors of adults, children's typing errors remain an understudied area. It is well known in the field of Child-Computer Interaction that children are not 'little adults'. This means findings regarding how adults make typing mistakes cannot simply be transferred into how children make typing errors, without first understanding the differences.
To understand how children differ from adults in the way they make typing mistakes, typing data were gathered from both children and adults. It was important that the data collected from the contrasting participant groups were comparable. Various methods of collecting typing data from adults were reviewed for suitability with children. Several issues were identified that could create a bias towards the adults. To resolve these issues, new tools and methods were designed, such as a new phrase set, a new data collector and new computer experience questionnaires.
Additionally, there was a lack of an analysis method of typing data suitable for use with both children and adults. A new categorisation method was defined based on typing errors made by both children and adults. This categorisation method was then adapted into a Java program, which dramatically reduced the time required to carry out typing categorisation.
Finally, in a large study, typing data collected from 231 primary school children, aged between 7 and 10 years, and 229 undergraduate computing students were analysed. Grouping the typing errors according to the context in which they occurred allowed for a much more detailed analysis than was possible with error rates. The analysis showed children have a set of errors they made frequently that adults rarely made. These errors that are specific to children suggest that differences exist between the ways the two groups make typing errors. This finding means that children's typing errors should be studied in their own right.
|Item Type:||Thesis (Doctoral)|
|Additional Information:||Kano, A. (2005). Evaluating Phrase Sets for Use with Text Entry Method Evaluation with Dyslexic Participants. Workshop on Improving and Assessing Pen-Based Input Techniques at HCI 2005, Edinburgh, UK.
Kano, A., Horton, M. and Read, J. C. (2010). Thumbs-up Scale and Frequency of Use Scale for Use in Self Reporting of Children's Computer Experience. NordiCHI 2010, Reykjavik, Iceland. ACM.
Kano, A., Read, J. C. and Dix, A. (2006). Children's Phrase Set for Text Input Method Evaluations. Proceedings of the Fourth Nordic Conference on Human-Computer Interaction - NordiCHI, Oslo, Norway. ACM Press.
Kano, A., Read, J. C., Dix, A. and Mackenzie, I. S. (2007). Expect: An Expanded Error Categorisation Method for Text Input. HCI 2007, Lancaster, UK.
|Uncontrolled Keywords (separate with ;):||Typing; Typing Error; Typing Error Categorisation; Children’s Typing; Adults’ Typing; Computer Experience; Phrase Set; Phrase-Copying Task; Error Rates|
|Subjects:||A General Works > AI Indexes (General)|
L Education > L Education (General)
Q Science > Q Science (General)
T Technology > T Technology (General)
|Schools:||School of Computing Engineering & Physcial Sciences|
Khalil Ahmed Patel
|Deposited On:||08 Jun 2012 15:45|
|Last Modified:||11 Feb 2014 15:00|
Repository Staff Only: item control page