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020 _a9783319603698
_9978-3-319-60369-8
024 7 _a10.1007/978-3-319-60369-8
_2doi
050 4 _aQA76.9.U83
050 4 _aQA76.9.H85
072 7 _aUYZ
_2bicssc
072 7 _aCOM070000
_2bisacsh
072 7 _aUYZ
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082 0 4 _a005.437
_223
082 0 4 _a004.019
_223
100 1 _aHalbrügge, Marc.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_961922
245 1 0 _aPredicting User Performance and Errors
_h[electronic resource] :
_bAutomated Usability Evaluation Through Computational Introspection of Model-Based User Interfaces /
_cby Marc Halbrügge.
250 _a1st ed. 2018.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2018.
300 _aXVI, 149 p. 44 illus., 17 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aT-Labs Series in Telecommunication Services,
_x2192-2829
505 0 _aIntroduction -- 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 _aThis 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 _aUser interfaces (Computer systems).
_911681
650 0 _aHuman-computer interaction.
_96196
650 0 _aSignal processing.
_94052
650 1 4 _aUser Interfaces and Human Computer Interaction.
_931632
650 2 4 _aSignal, Speech and Image Processing .
_931566
710 2 _aSpringerLink (Online service)
_961923
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319603681
776 0 8 _iPrinted edition:
_z9783319603704
776 0 8 _iPrinted edition:
_z9783319868493
830 0 _aT-Labs Series in Telecommunication Services,
_x2192-2829
_961924
856 4 0 _uhttps://doi.org/10.1007/978-3-319-60369-8
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c80857
_d80857