Hugo Nicolau
Kyle Montague
Tiago Guerreiro
André Rodrigues
Vicki L. Hanson
ABSTRACT
Non-visual text-entry for people with visual impairments has focused mostly on the comparison of input techniques reporting on performance measures, such as accuracy and speed. While researchers have been able to establish that non-visual input is slow and error prone, there is little understanding on how to improve it. To develop a richer characterization of typing performance, we conducted a longitudinal study with five novice blind users. For eight weeks, we collected in-situ usage data and conducted weekly laboratory assessment sessions. This paper presents a thorough analysis of typing performance that goes beyond traditional aggregated measures of text-entry and reports on character-level errors and touch measures. Our findings show that users improve over time, even though it is at a slow rate (0.3 WPM per week). Substitutions are the most common type of error and have a significant impact on entry rates. In addition to text input data, we analyzed touch behaviors, looking at touch contact points, exploration movements, and lift positions. We provide insights on why and how performance improvements and errors occur. Finally, we derive some implications that should inform the design of future virtual keyboards for non-visual input.
- Azenkot S. et al. 2012. Input Finger Detection for nonvisual touch screen text entry in Perkinput. Proceedings of Graphics Interface (GI '12) (2012). Google Scholar
Digital Library
- Berry, D.A. 1987. Logarithmic transformations in ANOVA. Biometrics. (1987), 439--456.Google Scholar
- Bonner, M. et al. 2010. No-Look Notes: Accessible eyes-free multi-touch text entry. Pervasive Computing. (2010), 409--426. Google ScholarDigital Library
- Evans, A. and Wobbrock, J. 2012. Taming wild behavior: the input observer for obtaining text entry and mouse pointing measures from everyday computer use. Proceedings of the SIGCHI conference on human factors in computing systems (2012), 1947--1956. Google ScholarDigital Library
- Findlater, L. et al. 2011. Typing on flat glass: examining ten-finger expert typing patterns on touch surfaces. Proceedings of the 2011 annual conference on Human factors in computing systems (2011), 2453--2462. Google ScholarDigital Library
- Findlater, L. and Wobbrock, J.O. 2012. Personalized Input: Improving Ten-Finger Touchscreen Typing through Automatic Adaptation. Proceedings of the 2012 annual conference on human factors in computing systems (CHI'12). (2012). Google ScholarDigital Library
- Guerreiro, J. et al. 2015. TabLETS Get Physical: Non-Visual Text Entry on Tablet Devices. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2015). Google ScholarDigital Library
- Guerreiro, T. et al. 2008. From tapping to touching: Making touch screens accessible to blind users. IEEE MultiMedia. (2008), 48--50. Google ScholarDigital Library
- Hwang, F. et al. 2004. Mouse movements of motion-impaired users: a submovement analysis. Proceedings of the 6th international ACM SIGACCESS conference on Computers and accessibility (New York, NY, USA, 2004), 102--109. Google ScholarDigital Library
- Keates, S. and Trewin, S. 2005. Effect of age and Parkinson's disease on cursor positioning using a mouse. Proceedings of the 7th international ACM SIGACCESS conference on Computers and accessibility (2005), 68--75. Google ScholarDigital Library
- Kristensson, P.O. 2009. Five challenges for intelligent text entry methods. AI Magazine. 30, 4 (2009), 85.Google ScholarDigital Library
- MacKenzie, I.S. et al. 2001. Accuracy measures for evaluating computer pointing devices. Proceedings of the SIGCHI conference on Human factors in computing systems (2001), 9--16. Google ScholarDigital Library
- MacKenzie, I.S. and Soukoreff, R.W. 2002. A character-level error analysis technique for evaluating text entry methods. Proceedings of the second Nordic conference on Human-computer interaction (2002), 243--246. Google ScholarDigital Library
- MacKenzie, I.S. and Soukoreff, R.W. 2002. Text entry for mobile computing: Models and methods, theory and practice. Human-Computer Interaction. 17, 2 (2002), 147--198.Google ScholarCross Ref
- McCulloch, C.E. and Neuhaus, J.M. 2001. Generalized linear mixed models. Wiley Online Library.Google Scholar
- Nicolau, H. et al. 2014. B#: Chord-based Correction for Multitouch Braille Input. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (New York, NY, USA, 2014), 1705--1708. Google ScholarDigital Library
- Nicolau, H. and Jorge, J. 2012. Elderly Text-Entry Performance on Touchscreens. Proceedings of the 14th international ACM SIGACCESS conference on Computers and accessibility (2012). Google ScholarDigital Library
- Nicolau, H. and Jorge, J. 2012. Touch typing using thumbs: understanding the effect of mobility and hand posture. Proceedings of the 2012 ACM annual conference on Human Factors in Computing Systems, 2683--2686. Google ScholarDigital Library
- Oliveira, J. et al. 2011. Blind people and mobile touch-based text-entry: acknowledging the need for different flavors. The proceedings of the 13th international ACM SIGACCESS conference on Computers and accessibility (2011), 179--186. Google ScholarDigital Library
- Pasqual, P.T. and Wobbrock, J.O. 2014. Mouse pointing endpoint prediction using kinematic template matching. Proceedings of the 32nd annual ACM conference on Human factors in computing systems (2014), 743--752. Google ScholarDigital Library
- Soukoreff, R.W. and MacKenzie, I.S. 2003. Metrics for text entry research: an evaluation of MSD and KSPC, and a new unified error metric. Proceedings of the SIGCHI conference on Human factors in computing systems (2003), 113--120. Google ScholarDigital Library
- Southern, C. et al. 2012. An Evaluation of BrailleTouch: Mobile Touchscreen Text Entry for the Visually Impaired. Proceedings of the 14th International Conference on Human-computer Interaction with Mobile Devices and Services (New York, NY, USA, 2012), 317--326. Google ScholarDigital Library
- Tinwala, H. and MacKenzie, I.S. 2010. Eyes-free text entry with error correction on touchscreen mobile devices. Proceedings of the 6th Nordi CHI (2010), 511--520. Google ScholarDigital Library
- Verbeke, G. and Molenberghs, G. 2009. Linear mixed models for longitudinal data. Springer Science & Business Media.Google Scholar
- Wobbrock, J.O. 2007. Text Entry Systems: Mobility, Accessibility, Universality. I.S. MacKenzie and K. Tanaka-Ishii, eds. San Francisco: Morgan Kaufmann. 47--74. Google ScholarDigital Library
- Wobbrock, J.O. et al. 2009. The angle mouse: target-agnostic dynamic gain adjustment based on angular deviation. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (2009), 1401--1410. Google ScholarDigital Library
- Wobbrock, J.O. and Myers, B.A. 2006. Analyzing the input stream for character- level errors in unconstrained text entry evaluations. ACM TOCHI, 13, 4 (2006), 458--489. Google ScholarDigital Library
- Yfantidis, G. and Evreinov, G. 2006. Adaptive blind interaction technique for touchscreens. Universal Access in the Information Society. 4, 4 (2006), 328--337. Google ScholarDigital Library
Index Terms
- Typing Performance of Blind Users: An Analysis of Touch Behaviors, Learning Effect, and In-Situ Usage
Recommendations
Blind people and mobile touch-based text-entry: acknowledging the need for different flavors
ASSETS '11: The proceedings of the 13th international ACM SIGACCESS conference on Computers and accessibilityThe emergence of touch-based mobile devices brought fresh and exciting possibilities. These came at the cost of a considerable number of novel challenges. They are particularly apparent with the blind population, as these devices lack tactile cues and ...
Investigating Laboratory and Everyday Typing Performance of Blind Users
Special Issue (Part 2) of Papers from ASSETS 2015Over the last decade there have been numerous studies on touchscreen typing by blind people. However, there are no reports about blind users’ everyday typing performance and how it relates to laboratory settings. We conducted a longitudinal study ...
The gest-rest: a pressure-sensitive chairable input pad for power wheelchair armrests
ASSETS '14: Proceedings of the 16th international ACM SIGACCESS conference on Computers & accessibilityInteracting with touch screen-based computing devices can be difficult for individuals with mobility impairments that affect their hands, arms, neck, or head. These problems may be especially difficult for power wheelchair users, as the frame of their ...
Comments