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Keith Knudsen

dblp:50/2591 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 1999
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Usability and user experience research · 87% User interface design and tools · 13%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Usability and user experience research › human performance modeling
predictive human performance modeling
0.011999
A Tool for Creating Predictive Performance Models from User Interface Demonstrations · ACM Symposium on User Interface Software and Technology 1999
Usability and user experience research › usability evaluation
usability evaluation tools
0.011999
A Tool for Creating Predictive Performance Models from User Interface Demonstrations · ACM Symposium on User Interface Software and Technology 1999

Methods — techniques the papers use, named apart from their topics

demonstration-based model generation · 0.0
YearPublicationVenuePosition
1999 A Tool for Creating Predictive Performance Models from User Interface Demonstrations
abstract
A central goal of many user interface development tools has been to make the construction of high quality interfaces easy enough that iterative design approaches could be a practical reality. In the last 15 years significant advances in this regard have been achieved. However, the evaluation portion of the iterative design process has received relatively little support from tools. Even though advances have also been made in usability evaluation methods, nearly all evaluation is still done “by hand,” making it more expensive and difficult than it might be. This paper considers a partial implementation of the CRITIQUE usability evaluation tool that is being developed to help remedy this situation by automating a number of evaluation tasks. This paper will consider techniques used by the system to produce predictive models (keystroke level models and simplified GOMS models) from demonstrations of sample tasks in a fraction of the time needed by conventional handcrafting methods. A preliminary comparison of automatically generated models with models created by an expert modeler show them to produce very similar predictions (within 2%). Further, because they are automated, these models promise to be less subject to human error and less affected by the skill of the modeler.
Scott E. Hudson, Bonnie E. John, Keith Knudsen, Michael D. Byrne
ACM Symposium on User Interface Software and Technology3