A User-Adaptive Chart Editing System Based on User Modeling and Critiquing

Gutkauf, B.; Thies, Stefanie; Domik, Gitta

doi:10.1007/978-3-7091-2670-7_18

Cited by 11 publications

(6 citation statements)

References 8 publications

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“…Outside of a learning context, users are likely to hesitate to invest time in tests of knowledge or skill unless these can be presented in an enjoyable form (see, e.g., the color discrimination test used by Gutkauf, Thies, & Domik, 1997, to identify perceptual limitations relevant to the automatic generation of graphs). Trewin (2004) reports on experience with a brief typing test that was designed to identify helpful keyboard adaptations: Some users who turned out to require no adaptations were disappointed that their investment in the test had yielded no benefit.…”

Section: Responses To Test Itemsmentioning

confidence: 99%

Adaptive Interfaces and Agents

Jameson¹

2009

Human Factors and Ergonomics

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Section: Responses To Test Itemsmentioning

confidence: 99%

Adaptive Interfaces and Agents

Jameson¹

2009

Human Factors and Ergonomics

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“…Examples of perception issues include the ability to recognize color, the VISUALIZATIONS AND GROUP DECISION MAKING ability to distinguish and name different colors, preferences for font and character size, and the ability to accurately perceive lines. Cognition issues include the ability to mentally rotate representations of two-and threedimensional objects, the ability to recognize and understand patterns in the data, and the user's familiarity and experience with computer interaction (Gutkauf, Thies, & Domik, 1997).…”

Section: Perception and Cognitionmentioning

confidence: 99%

Effects of Data Visualizations on Group Decision Making.

Schatz¹,

Cannon‐Bowers²,

Bowers³

2006

Creating High-Tech Teams: Practical Guidance on Work Performance and Technology.

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In 1962, mathematician and computer scientist Richard Hamming observed that "the purpose of computing is insight, not numbers" (p. 1). Yet today, many computers are still used primarily to generate enormous quantities of impractical, difficult-to-decipher data. Even experts, such as statisticians and mathematicians, often struggle to comprehend and appreciate these masses of numbers, and nonspecialists are usually unable to do so at all. The obliqueness of these complex data burdens decision-making processes and strains team collaborations. However, complex numerical data can be represented in the form of visualizations, which people-specialists and nonspecialists alike-can glean insight from, use to make better decisions, and draw on to improve team interactions.In this chapter we present an overview of data visualizations and how they can enhance team task performance. In the first section, we provide a very brief overview of the form and function of visualizations; interested readers are encouraged to see Chen (2003) for a more detailed treatment of data visualizations. In the second section, we introduce the general benefits of, and problems with, data visualizations, and in the last section we discuss visualizations in the context of group performance and communication.

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“…Accelerated writing systems such as PAL (New ell et al 1995) and M essenger (Venkatagiri 1993), record a user' s frequently used words in order to improve the e ciency of word prediction. Gutkauf et al (1997) describe a user model incorporating information including colour perception, which is used to adapt the presentation of colour charts in literature published on the web. This paper describes evaluation of techniques for identifying the four major keyboard di culties described above, and generating a model of the user' s requirements for speci® c con® guration facilities.…”

Section: Introductionmentioning

confidence: 99%

A model of keyboard configuration requirements

Trewin¹,

Pain²

1999

Behaviour & Information Technology

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This paper presents a user model: a com puter program which examines the behaviour of a real com puter user. The model encom passes four aspects of keyboard use which can present di culties for people with motor disabilities. Where relevant keyboard con® guration options exist, the model chooses appropriate settings for these options. The model bases its recomm endations on observation of users typing free English text. It is intended to form part of a dynamic con® guration support tool. Empirical evaluation showed the model to be very accurate in identi® cation of a given user' s di culties. Where recom mended con® guration options were tried by the participants, high levels of error reduction and user satisfaction were found.

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A User-Adaptive Chart Editing System Based on User Modeling and Critiquing

Cited by 11 publications

References 8 publications

Adaptive Interfaces and Agents

Adaptive Interfaces and Agents

Effects of Data Visualizations on Group Decision Making.

A model of keyboard configuration requirements

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