Predicting Interaction Effort in Web Interface Widgets

Autores
Gardey, Juan Cruz; Grigera, Julián; Rodríguez, Andrés; Rossi, Gustavo Héctor; Garrido, Alejandra
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The product of good design should render a tool invisible for a user who is executing a task. Unfortunately, web applications are often far from invisible to users, who struggle with poor design of websites and processes in them. We are particularly interested in web processes that involve form filling, so we have been studying how people interact with web forms. Besides cataloguing user interaction problems that are common in web forms, we have noticed that, in many cases, there is a single form element or widget to blame for a certain interaction problem, because such widget is not the most appropriate one for the required input in that particular context. This unfitness of the widget causes an extra burden to the user, which we call interaction effort. In this work we propose measuring the interaction effort of a widget with a unified score based on micro-measures automatically captured from interaction logs. We present the micromeasures that were found relevant to predict the interaction effort in 6 different types of web forms widgets. We describe a large data collection process and prediction models, showing that it is indeed possible to automatically predict a widget interaction effort score by learning from expert human ratings. We consequently believe that the interaction effort could be used as an effective metric to compare small variations in a design in terms of user experience.
Materia
Ciencias de la Computación e Información
Interactivity
User interaction metrics
User experience
Web usability
UX refactoring
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
CIC Digital (CICBA)
Institución
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
OAI Identificador
oai:digital.cic.gba.gob.ar:11746/11636

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repository_id_str 9441
network_name_str CIC Digital (CICBA)
spelling Predicting Interaction Effort in Web Interface WidgetsGardey, Juan CruzGrigera, JuliánRodríguez, AndrésRossi, Gustavo HéctorGarrido, AlejandraCiencias de la Computación e InformaciónInteractivityUser interaction metricsUser experienceWeb usabilityUX refactoringThe product of good design should render a tool invisible for a user who is executing a task. Unfortunately, web applications are often far from invisible to users, who struggle with poor design of websites and processes in them. We are particularly interested in web processes that involve form filling, so we have been studying how people interact with web forms. Besides cataloguing user interaction problems that are common in web forms, we have noticed that, in many cases, there is a single form element or widget to blame for a certain interaction problem, because such widget is not the most appropriate one for the required input in that particular context. This unfitness of the widget causes an extra burden to the user, which we call interaction effort. In this work we propose measuring the interaction effort of a widget with a unified score based on micro-measures automatically captured from interaction logs. We present the micromeasures that were found relevant to predict the interaction effort in 6 different types of web forms widgets. We describe a large data collection process and prediction models, showing that it is indeed possible to automatically predict a widget interaction effort score by learning from expert human ratings. We consequently believe that the interaction effort could be used as an effective metric to compare small variations in a design in terms of user experience.2022-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/11636enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.ijhcs.2022.102919info:eu-repo/semantics/altIdentifier/issn/1071-5819info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:40:22Zoai:digital.cic.gba.gob.ar:11746/11636Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-29 13:40:22.991CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse
dc.title.none.fl_str_mv Predicting Interaction Effort in Web Interface Widgets
title Predicting Interaction Effort in Web Interface Widgets
spellingShingle Predicting Interaction Effort in Web Interface Widgets
Gardey, Juan Cruz
Ciencias de la Computación e Información
Interactivity
User interaction metrics
User experience
Web usability
UX refactoring
title_short Predicting Interaction Effort in Web Interface Widgets
title_full Predicting Interaction Effort in Web Interface Widgets
title_fullStr Predicting Interaction Effort in Web Interface Widgets
title_full_unstemmed Predicting Interaction Effort in Web Interface Widgets
title_sort Predicting Interaction Effort in Web Interface Widgets
dc.creator.none.fl_str_mv Gardey, Juan Cruz
Grigera, Julián
Rodríguez, Andrés
Rossi, Gustavo Héctor
Garrido, Alejandra
author Gardey, Juan Cruz
author_facet Gardey, Juan Cruz
Grigera, Julián
Rodríguez, Andrés
Rossi, Gustavo Héctor
Garrido, Alejandra
author_role author
author2 Grigera, Julián
Rodríguez, Andrés
Rossi, Gustavo Héctor
Garrido, Alejandra
author2_role author
author
author
author
dc.subject.none.fl_str_mv Ciencias de la Computación e Información
Interactivity
User interaction metrics
User experience
Web usability
UX refactoring
topic Ciencias de la Computación e Información
Interactivity
User interaction metrics
User experience
Web usability
UX refactoring
dc.description.none.fl_txt_mv The product of good design should render a tool invisible for a user who is executing a task. Unfortunately, web applications are often far from invisible to users, who struggle with poor design of websites and processes in them. We are particularly interested in web processes that involve form filling, so we have been studying how people interact with web forms. Besides cataloguing user interaction problems that are common in web forms, we have noticed that, in many cases, there is a single form element or widget to blame for a certain interaction problem, because such widget is not the most appropriate one for the required input in that particular context. This unfitness of the widget causes an extra burden to the user, which we call interaction effort. In this work we propose measuring the interaction effort of a widget with a unified score based on micro-measures automatically captured from interaction logs. We present the micromeasures that were found relevant to predict the interaction effort in 6 different types of web forms widgets. We describe a large data collection process and prediction models, showing that it is indeed possible to automatically predict a widget interaction effort score by learning from expert human ratings. We consequently believe that the interaction effort could be used as an effective metric to compare small variations in a design in terms of user experience.
description The product of good design should render a tool invisible for a user who is executing a task. Unfortunately, web applications are often far from invisible to users, who struggle with poor design of websites and processes in them. We are particularly interested in web processes that involve form filling, so we have been studying how people interact with web forms. Besides cataloguing user interaction problems that are common in web forms, we have noticed that, in many cases, there is a single form element or widget to blame for a certain interaction problem, because such widget is not the most appropriate one for the required input in that particular context. This unfitness of the widget causes an extra burden to the user, which we call interaction effort. In this work we propose measuring the interaction effort of a widget with a unified score based on micro-measures automatically captured from interaction logs. We present the micromeasures that were found relevant to predict the interaction effort in 6 different types of web forms widgets. We describe a large data collection process and prediction models, showing that it is indeed possible to automatically predict a widget interaction effort score by learning from expert human ratings. We consequently believe that the interaction effort could be used as an effective metric to compare small variations in a design in terms of user experience.
publishDate 2022
dc.date.none.fl_str_mv 2022-08
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 https://digital.cic.gba.gob.ar/handle/11746/11636
url https://digital.cic.gba.gob.ar/handle/11746/11636
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ijhcs.2022.102919
info:eu-repo/semantics/altIdentifier/issn/1071-5819
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
eu_rights_str_mv openAccess
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dc.source.none.fl_str_mv reponame:CIC Digital (CICBA)
instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron:CICBA
reponame_str CIC Digital (CICBA)
collection CIC Digital (CICBA)
instname_str Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
instacron_str CICBA
institution CICBA
repository.name.fl_str_mv CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
repository.mail.fl_str_mv marisa.degiusti@sedici.unlp.edu.ar
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