Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use

Autores
González, María Paula; Lorés, Jesús; Granollers, Antoni
Año de publicación
2008
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Usability is a software attribute usually associated with the "ease of use and to learn" of a given interactive system. Nowadays usability evaluation is becoming an important part of software development, providing results based on quantitative and qualitative estimations. In this context, qualitative results are usually obtained through a Qualitative Usability Testing process which includes a number of different methods focused on analyzing the interface of a particular interactive system. These methods become complex when a large number of interactive systems belonging to the same context of use have to be jointly considered to provide a general diagnosis, as a considerable amount of information must be visualized and treated simultaneously. However, diagnosing the most general usability problems of a context of use as a whole from a qualitative viewpoint is a challenge for UE nowadays. Identifying such problems can help to evaluate a new interface belonging to this context, and to prevent usability errors when a novel interactive system is being developed. From a quantitative viewpoint, condensing results in singles scores, metrics or statistical functions is an acceptable solution for processing huge amounts of usability related information. Nevertheless, QUT processes need to keep their richness by prioritizing the "what" over the "how much/how many" questions related to the detection of usability problems. To cope with the above situation, this paper presents a new approach in which two datamining techniques (association rules and decision trees) are used to extend the existing Qualitative Usability Testing process in order to provide a general usability diagnosis of a given context of use from a qualitative viewpoint. In order to validate our proposal, usability problems patterns belonging to academic webpages in Spanish-speaking countries are assessed by processing 3450 records which store qualitative information collected by means of a Heuristic Evaluation.
Fil: González, María Paula. Universidad de Lleida; España. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lorés, Jesús. Universidad de Lleida; España
Fil: Granollers, Antoni. Universidad de Lleida; España
Materia
Association Rules
Context of Use
Datamining
Decision Trees
Qualitative Usability Testing
Usability Engineering
Usability Problem Patterns
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/75666

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spelling Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of useGonzález, María PaulaLorés, JesúsGranollers, AntoniAssociation RulesContext of UseDataminingDecision TreesQualitative Usability TestingUsability EngineeringUsability Problem Patternshttps://purl.org/becyt/ford/2.2https://purl.org/becyt/ford/2Usability is a software attribute usually associated with the "ease of use and to learn" of a given interactive system. Nowadays usability evaluation is becoming an important part of software development, providing results based on quantitative and qualitative estimations. In this context, qualitative results are usually obtained through a Qualitative Usability Testing process which includes a number of different methods focused on analyzing the interface of a particular interactive system. These methods become complex when a large number of interactive systems belonging to the same context of use have to be jointly considered to provide a general diagnosis, as a considerable amount of information must be visualized and treated simultaneously. However, diagnosing the most general usability problems of a context of use as a whole from a qualitative viewpoint is a challenge for UE nowadays. Identifying such problems can help to evaluate a new interface belonging to this context, and to prevent usability errors when a novel interactive system is being developed. From a quantitative viewpoint, condensing results in singles scores, metrics or statistical functions is an acceptable solution for processing huge amounts of usability related information. Nevertheless, QUT processes need to keep their richness by prioritizing the "what" over the "how much/how many" questions related to the detection of usability problems. To cope with the above situation, this paper presents a new approach in which two datamining techniques (association rules and decision trees) are used to extend the existing Qualitative Usability Testing process in order to provide a general usability diagnosis of a given context of use from a qualitative viewpoint. In order to validate our proposal, usability problems patterns belonging to academic webpages in Spanish-speaking countries are assessed by processing 3450 records which store qualitative information collected by means of a Heuristic Evaluation.Fil: González, María Paula. Universidad de Lleida; España. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Lorés, Jesús. Universidad de Lleida; EspañaFil: Granollers, Antoni. Universidad de Lleida; EspañaElsevier Science2008-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/75666González, María Paula; Lorés, Jesús; Granollers, Antoni; Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use; Elsevier Science; Information And Software Technology; 50; 6; 5-2008; 547-5680950-5849CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.infsof.2007.06.001info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0950584907000614info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T11:03:37Zoai:ri.conicet.gov.ar:11336/75666instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 11:03:37.88CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use
title Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use
spellingShingle Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use
González, María Paula
Association Rules
Context of Use
Datamining
Decision Trees
Qualitative Usability Testing
Usability Engineering
Usability Problem Patterns
title_short Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use
title_full Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use
title_fullStr Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use
title_full_unstemmed Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use
title_sort Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use
dc.creator.none.fl_str_mv González, María Paula
Lorés, Jesús
Granollers, Antoni
author González, María Paula
author_facet González, María Paula
Lorés, Jesús
Granollers, Antoni
author_role author
author2 Lorés, Jesús
Granollers, Antoni
author2_role author
author
dc.subject.none.fl_str_mv Association Rules
Context of Use
Datamining
Decision Trees
Qualitative Usability Testing
Usability Engineering
Usability Problem Patterns
topic Association Rules
Context of Use
Datamining
Decision Trees
Qualitative Usability Testing
Usability Engineering
Usability Problem Patterns
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.2
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv Usability is a software attribute usually associated with the "ease of use and to learn" of a given interactive system. Nowadays usability evaluation is becoming an important part of software development, providing results based on quantitative and qualitative estimations. In this context, qualitative results are usually obtained through a Qualitative Usability Testing process which includes a number of different methods focused on analyzing the interface of a particular interactive system. These methods become complex when a large number of interactive systems belonging to the same context of use have to be jointly considered to provide a general diagnosis, as a considerable amount of information must be visualized and treated simultaneously. However, diagnosing the most general usability problems of a context of use as a whole from a qualitative viewpoint is a challenge for UE nowadays. Identifying such problems can help to evaluate a new interface belonging to this context, and to prevent usability errors when a novel interactive system is being developed. From a quantitative viewpoint, condensing results in singles scores, metrics or statistical functions is an acceptable solution for processing huge amounts of usability related information. Nevertheless, QUT processes need to keep their richness by prioritizing the "what" over the "how much/how many" questions related to the detection of usability problems. To cope with the above situation, this paper presents a new approach in which two datamining techniques (association rules and decision trees) are used to extend the existing Qualitative Usability Testing process in order to provide a general usability diagnosis of a given context of use from a qualitative viewpoint. In order to validate our proposal, usability problems patterns belonging to academic webpages in Spanish-speaking countries are assessed by processing 3450 records which store qualitative information collected by means of a Heuristic Evaluation.
Fil: González, María Paula. Universidad de Lleida; España. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Lorés, Jesús. Universidad de Lleida; España
Fil: Granollers, Antoni. Universidad de Lleida; España
description Usability is a software attribute usually associated with the "ease of use and to learn" of a given interactive system. Nowadays usability evaluation is becoming an important part of software development, providing results based on quantitative and qualitative estimations. In this context, qualitative results are usually obtained through a Qualitative Usability Testing process which includes a number of different methods focused on analyzing the interface of a particular interactive system. These methods become complex when a large number of interactive systems belonging to the same context of use have to be jointly considered to provide a general diagnosis, as a considerable amount of information must be visualized and treated simultaneously. However, diagnosing the most general usability problems of a context of use as a whole from a qualitative viewpoint is a challenge for UE nowadays. Identifying such problems can help to evaluate a new interface belonging to this context, and to prevent usability errors when a novel interactive system is being developed. From a quantitative viewpoint, condensing results in singles scores, metrics or statistical functions is an acceptable solution for processing huge amounts of usability related information. Nevertheless, QUT processes need to keep their richness by prioritizing the "what" over the "how much/how many" questions related to the detection of usability problems. To cope with the above situation, this paper presents a new approach in which two datamining techniques (association rules and decision trees) are used to extend the existing Qualitative Usability Testing process in order to provide a general usability diagnosis of a given context of use from a qualitative viewpoint. In order to validate our proposal, usability problems patterns belonging to academic webpages in Spanish-speaking countries are assessed by processing 3450 records which store qualitative information collected by means of a Heuristic Evaluation.
publishDate 2008
dc.date.none.fl_str_mv 2008-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/75666
González, María Paula; Lorés, Jesús; Granollers, Antoni; Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use; Elsevier Science; Information And Software Technology; 50; 6; 5-2008; 547-568
0950-5849
CONICET Digital
CONICET
url http://hdl.handle.net/11336/75666
identifier_str_mv González, María Paula; Lorés, Jesús; Granollers, Antoni; Enhancing usability testing through datamining techniques: A novel approach to detecting usability problem patterns for a context of use; Elsevier Science; Information And Software Technology; 50; 6; 5-2008; 547-568
0950-5849
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.infsof.2007.06.001
info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0950584907000614
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
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