Predicting User Performance and Errors [electronic resource] : Automated Usability Evaluation Through Computational Introspection of Model-Based User Interfaces / by Marc Halbrügge.

Por: Halbrügge, Marc [author.]Colaborador(es): SpringerLink (Online service)Tipo de material: TextoTextoSeries T-Labs Series in Telecommunication ServicesEditor: Cham : Springer International Publishing : Imprint: Springer, 2018Edición: 1st ed. 2018Descripción: XVI, 149 p. 44 illus., 17 illus. in color. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783319603698Tema(s): User interfaces (Computer systems) | Signal processing | Image processing | Speech processing systems | User Interfaces and Human Computer Interaction | Signal, Image and Speech ProcessingFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 005.437 | 4.019 Clasificación LoC:QA76.9.U83QA76.9.H85Recursos en línea: Libro electrónicoTexto
Contenidos:
Introduction -- Part I Theoretical Background and Related Work: Interactive Behavior and Human Error -- Model-Based UI Development (MBUID) -- Automated Usability Evaluation (AUE) -- Part II Empirical Results and Model Development: Introspection-Based Predictions of Human Performance -- Explaining and Predicting Sequential Error in HCI With Cognitive User Models -- The Competent User: How Prior Knowledge Shapes Performance and Errors -- A Deeply Integrated System for Introspection-Based Error Prediction -- The Unknown User: Does Optimizing for Errors and Time Lead to More Likable Systems?- General Discussion and Conclusion.
En: Springer Nature eBookResumen: 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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Acceso multiusuario

Introduction -- Part I Theoretical Background and Related Work: Interactive Behavior and Human Error -- Model-Based UI Development (MBUID) -- Automated Usability Evaluation (AUE) -- Part II Empirical Results and Model Development: Introspection-Based Predictions of Human Performance -- Explaining and Predicting Sequential Error in HCI With Cognitive User Models -- The Competent User: How Prior Knowledge Shapes Performance and Errors -- A Deeply Integrated System for Introspection-Based Error Prediction -- The Unknown User: Does Optimizing for Errors and Time Lead to More Likable Systems?- General Discussion and Conclusion.

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.

UABC ; Temporal ; 01/01/2021-12/31/2023.

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