Optimizing Usability Studies by Complementary Evaluation Methods

Martin Schmettow; Cedric Bach; Dominique Scapin

doi:10.14236/ewic/hci2014.12

Optimizing Usability Studies by Complementary Evaluation Methods

Martin Schmettow, Cedric Bach, Dominique Scapin

Faculty of Behavioural, Management and Social Sciences

Research output: Contribution to conference › Paper › peer-review

2 Citations (Scopus)

251 Downloads (Pure)

Abstract

This paper examines combinations of complementary evaluation methods as a strategy for efficient usability problem discovery. A data set from an earlier study is re-analyzed, involving three evaluation methods applied to two virtual environment applications. Results of a mixed-effects logistic regression suggest that usability testing and inspection discover rather disjunctive sets of problems. A resampling analysis reveals that mixing inspection and usability testing sessions in equal parts finds 20% more problems with the same number of sessions

Original language	English
Number of pages	10
DOIs	https://doi.org/10.14236/ewic/hci2014.12
Publication status	Published - 9 Sept 2014
Event	28th International BCS Human Computer Interaction Conference, HCI 2014: Sand, sea and Sky - Holiday HCI - Royal Clifton Hotel, Southport, United Kingdom Duration: 9 Sept 2014 → 12 Sept 2014 Conference number: 28

Conference

Conference	28th International BCS Human Computer Interaction Conference, HCI 2014
Abbreviated title	HCI
Country/Territory	United Kingdom
City	Southport
Period	9/09/14 → 12/09/14

Keywords

METIS-306375
IR-92518
usability evaluation
effectiveness
virtual environments
logistic regression
mixed-effects linear model

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10.14236/ewic/hci2014.12

Optimizing Usability StudiesFinal published version, 406 KB

Cite this

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title = "Optimizing Usability Studies by Complementary Evaluation Methods",

abstract = "This paper examines combinations of complementary evaluation methods as a strategy for efficient usability problem discovery. A data set from an earlier study is re-analyzed, involving three evaluation methods applied to two virtual environment applications. Results of a mixed-effects logistic regression suggest that usability testing and inspection discover rather disjunctive sets of problems. A resampling analysis reveals that mixing inspection and usability testing sessions in equal parts finds 20% more problems with the same number of sessions",

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author = "Martin Schmettow and Cedric Bach and Dominique Scapin",

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AU - Schmettow, Martin

AU - Bach, Cedric

AU - Scapin, Dominique

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N2 - This paper examines combinations of complementary evaluation methods as a strategy for efficient usability problem discovery. A data set from an earlier study is re-analyzed, involving three evaluation methods applied to two virtual environment applications. Results of a mixed-effects logistic regression suggest that usability testing and inspection discover rather disjunctive sets of problems. A resampling analysis reveals that mixing inspection and usability testing sessions in equal parts finds 20% more problems with the same number of sessions

AB - This paper examines combinations of complementary evaluation methods as a strategy for efficient usability problem discovery. A data set from an earlier study is re-analyzed, involving three evaluation methods applied to two virtual environment applications. Results of a mixed-effects logistic regression suggest that usability testing and inspection discover rather disjunctive sets of problems. A resampling analysis reveals that mixing inspection and usability testing sessions in equal parts finds 20% more problems with the same number of sessions

KW - METIS-306375

KW - IR-92518

KW - usability evaluation

KW - effectiveness

KW - virtual environments

KW - logistic regression

KW - mixed-effects linear model

U2 - 10.14236/ewic/hci2014.12

DO - 10.14236/ewic/hci2014.12

M3 - Paper

T2 - 28th International BCS Human Computer Interaction Conference, HCI 2014

Y2 - 9 September 2014 through 12 September 2014

ER -

Optimizing Usability Studies by Complementary Evaluation Methods

Abstract

Conference

Keywords

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