Movement model, hits distribution and learning in virtual keyboarding

Zhai, Shumin; Sue, Alison; Accot, Johnny

doi:10.1145/503380.503381

Cited by 14 publications

(19 citation statements)

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“…We have revised and applied the ERI method in two studies, one on learning stylus tapping (Zhai et al, 2002b) and the other on learning sokgraphs (Zhai and Kristensson, 2003). An important modification we made to ERI was to make it adaptive to user's learning speed.…”

Section: Learning Methodsmentioning

confidence: 99%

“…For example, in Zhai et al (2002b), our algorithm scheduled the reappearance of each training item (a letter, a digraph, or a word) with a gradually increasing interval. The interval for each item was increased only when the participant learned the item well enough to type it without spending a significant portion of the total typing time searching for the keys.…”

Section: Learning Methodsmentioning

confidence: 99%

“…See MacKenzie (1992) for a general review, and Zhai (2002, 2003), McGuffin and Balakrishnan (2002) and for recent developments in the context of HCI. In the case of stylus keyboarding, by analyzing the Gaussian hits distribution of the stylus tip, we have shown that the users do effectively use the virtual keys as Fitts' law assumes-they could control their normally distributed hit points 'tightly' enough to be within the key size, but also sufficiently 'loosely' to utilize the given surface of the keys (Zhai et al, 2002b).…”

Section: Optimization Of Stylus Keyboardmentioning

confidence: 99%

“…More recently, Zhai et al (2002b) estimated the values of a and b in Fitts' law in the context of stylus typing which involves a relatively small range of index of difficulty formed by tightly packed targets, the use of stylus, and visual recognition of a series of intended target letters (but excluding visual search needed by the novice users of stylus keyboards) in varied directions. Their results were a ¼ 0:083; b ¼ 0:127 s, or IP ¼ 1=b ¼ 7:9 bps.…”

Section: Optimization Of Stylus Keyboardmentioning

confidence: 99%

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In search of effective text input interfaces for off the desktop computing

Zhai¹,

Kristensson²,

Smith³

2005

Interacting with Computers

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It is generally recognized that today's frontier of HCI research lies beyond the traditional desktop computers whose GUI interfaces were built on the foundation of display-pointing device-full keyboard. Many interface challenges arise without such a physical UI foundation. Text writingranging from entering URLs and search queries, filling forms, typing commands, to taking notes and writing emails and chat messages-is one of the hard problems awaiting for solutions in off-desktop computing. This paper summarizes and synthesizes a research program on this topic at the IBM Almaden Research Center. It analyzes various dimensions that constitute a good text input interface; briefly reviews related literature; discusses the evaluation methodology issues of text input; presents the major ideas and results of two systems, ATOMIK and SHARK; and points out current and future directions in the area from our current vantage point. q

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Section: Learning Methodsmentioning

confidence: 99%

Section: Learning Methodsmentioning

confidence: 99%

Section: Optimization Of Stylus Keyboardmentioning

confidence: 99%

Section: Optimization Of Stylus Keyboardmentioning

confidence: 99%

See 2 more Smart Citations

In search of effective text input interfaces for off the desktop computing

Zhai¹,

Kristensson²,

Smith³

2005

Interacting with Computers

Self Cite

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“…The time to press a key is logarithmically proportional to the distance to that key while logarithmically inversely proportional to width of the target key (big keys close to the starting point are fastest targets to hit). The constants a and b have to be derived experimentally for a given device, for comparison with work of others we used the figures a=0.083 and b=0.127 [2,32] in our studies despite their being derived for stylusbased keyboarding. To calculate the average time per keystroke, a weighted average is used based on the probability of bigrams in the language, so that key combinations that are struck more commonly (e.g.…”

Section: Fitts' Law Speed Calculationsmentioning

confidence: 99%

Multidimensional pareto optimization of touchscreen keyboards for speed, familiarity and improved spell checking

Dunlop

Levine

2012

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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This paper presents a new optimization technique for keyboard layouts based on Pareto front optimization. We used this multifactorial technique to create two new touchscreen phone keyboard layouts based on three design metrics: minimizing finger travel distance in order to maximize text entry speed, a new metric to maximize the quality of spell correction by reducing tap ambiguity, and maximizing familiarity through a similarity function with the standard Qwerty layout. The paper describes the optimization process and resulting layouts for a standard trapezoid shaped keyboard and a more rectangular layout. Fitts' law modelling shows a predicted 11% improvement in entry speed without taking into account the significantly improved error correction potential and the subsequent effect on speed. In initial user tests typing speed dropped from approx. 21 wpm with Qwerty to 13 wpm (64%) on first use of our layout but recovered to 18 wpm (85%) within four short trial sessions, and was still improving. NASA TLX forms showed no significant difference on load between Qwerty and our new layout use in the fourth session. Together we believe this shows the new layouts are faster and can be quickly adopted by users.

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Cyber Swarm optimization for general keyboard arrangement problem

Yin

2011

International Journal of Industrial Ergonomics

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Movement model, hits distribution and learning in virtual keyboarding

Cited by 14 publications

References 0 publications

In search of effective text input interfaces for off the desktop computing

In search of effective text input interfaces for off the desktop computing

Multidimensional pareto optimization of touchscreen keyboards for speed, familiarity and improved spell checking

Cyber Swarm optimization for general keyboard arrangement problem

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