東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Predicting user performance and erro...

Halbrugge, Marc.

Linked to FindBook

Google Book

Amazon

博客來

Predicting user performance and errors = automated usability evaluation through computational introspection of model-based user interfaces /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Predicting user performance and errors/ by Marc Halbrugge.
Reminder of title:	automated usability evaluation through computational introspection of model-based user interfaces /
Author:	Halbrugge, Marc.
Published:	Cham :Springer International Publishing : : 2018.,
Description:	xvi, 149 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer eBooks
Subject:	User interfaces (Computer systems) -
Online resource:	http://dx.doi.org/10.1007/978-3-319-60369-8
ISBN:	9783319603698

Predicting user performance and errors = automated usability evaluation through computational introspection of model-based user interfaces /
Halbrugge, Marc.

Predicting user performance and errorsautomated usability evaluation through computational introspection of model-based user interfaces /[electronic resource] :by Marc Halbrugge. - Cham :Springer International Publishing :2018. - xvi, 149 p. :ill., digital ;24 cm. - T-Labs series in telecommunication services,2192-2810. - T-Labs series in telecommunication services..

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.

ISBN: 9783319603698

Standard No.: 10.1007/978-3-319-60369-8doiSubjects--Topical Terms:

539550
User interfaces (Computer systems)

LC Class. No.: QA76.9.U83

Dewey Class. No.: 005.437

Predicting user performance and errors = automated usability evaluation through computational introspection of model-based user interfaces /
LDR:03195nmm a2200325 a 4500 001 2130678
003 DE-He213
005 20170720175802.0
006 m d
007 cr nn 008maaau
008 181005s2018 gw s 0 eng d
020 $a 9783319603698 $q (electronic bk.)
020 $a 9783319603681 $q (paper)
024 7 $a 10.1007/978-3-319-60369-8 $2 doi
035 $a 978-3-319-60369-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.U83
072 7 $a UYZG $2 bicssc
072 7 $a COM070000 $2 bisacsh
082 0 4 $a 005.437 $2 23
090 $a QA76.9.U83 $b H157 2018
100 1 $a Halbrugge, Marc. $3 3295496
245 1 0 $a Predicting user performance and errors $h [electronic resource] : $b automated usability evaluation through computational introspection of model-based user interfaces / $c by Marc Halbrugge.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2018.
300 $a xvi, 149 p. : $b ill., digital ; $c 24 cm.
490 1 $a T-Labs series in telecommunication services, $x 2192-2810
505 0 $a 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.
520 $a 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.
650 0 $a User interfaces (Computer systems) $3 539550
650 0 $a Human-computer interaction. $3 560071
650 1 4 $a Computer Science. $3 626642
650 2 4 $a User Interfaces and Human Computer Interaction. $3 892554
650 2 4 $a Signal, Image and Speech Processing. $3 891073
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a T-Labs series in telecommunication services. $3 1567837
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-60369-8
950 $a Engineering (Springer-11647)