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Predicting User Performance and Errors - Automated Usability Evaluation Through Computational Introspection of Model-Based User Interfaces (Hardcover, 1st ed. 2018)
Loot Price: R2,961
Discovery Miles 29 610
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Predicting User Performance and Errors - Automated Usability Evaluation Through Computational Introspection of Model-Based User Interfaces (Hardcover, 1st ed. 2018)
Series: T-Labs Series in Telecommunication Services
Expected to ship within 10 - 15 working days
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This book proposes a combination of cognitive modeling with
model-based user interface development to tackle the problem of
maintaining the usability of applications that target several
device types at once (e.g., desktop PC, smart phone, smart TV).
Model-based applications provide interesting meta-information about
the elements of the user interface (UI) that are accessible through
computational introspection. Cognitive user models can capitalize
on this meta-information to provide improved predictions of the
interaction behavior of future human users of applications under
development. In order to achieve this, cognitive processes that
link UI properties to usability aspects like effectiveness (user
error) and efficiency (task completion time) are established
empirically, are explained through cognitive modeling, and are
validated in the course of this treatise. In the case of user
error, the book develops an extended model of sequential action
control based on the Memory for Goals theory and it is confirmed in
different behavioral domains and experimental paradigms. This new
model of user cognition and behavior is implemented using the MeMo
workbench and integrated with the model-based application framework
MASP in order to provide automated usability predictions from early
software development stages on. Finally, the validity of the
resulting integrated system is confirmed by empirical data from a
new application, eliciting unexpected behavioral patterns.
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