One Metric for All: Calculating Interaction Effort of Individual Widgets
- Autores
- Grigera, Julián; Gardey, Juan Cruz; Rodríguez, Andrés Santiago; Garrido, Alejandra; Rossi, Gustavo Héctor
- Año de publicación
- 2019
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Automating usability diagnose and repair can be a powerful assistance to usability experts and even less knowledgeable developers. To accomplish this goal, evaluating user interaction automatically is crucial, and it has been broadly explored. However, most works focus in long interaction sessions, which makes it difficult to tell how individual interface components influence usability. In contrast, this work aims to compare how different widgets perform for the same task, in the context of evaluating alternative designs for small components, implemented as refactorings. For this purpose, we propose a unified score to compare the widgets involved in each refactoring by the level of effort required by users to interact with them. This score is based on micro-measures automatically captured from interaction logs, so it can be automatically predicted. We show the results of predicting such score using a decision tree.
Laboratorio de Investigación y Formación en Informática Avanzada - Materia
-
Ciencias Informáticas
Web usability
Interactivity
Usability refactoring
A/B testing
User interaction metrics - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/119016
Ver los metadatos del registro completo
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One Metric for All: Calculating Interaction Effort of Individual WidgetsGrigera, JuliánGardey, Juan CruzRodríguez, Andrés SantiagoGarrido, AlejandraRossi, Gustavo HéctorCiencias InformáticasWeb usabilityInteractivityUsability refactoringA/B testingUser interaction metricsAutomating usability diagnose and repair can be a powerful assistance to usability experts and even less knowledgeable developers. To accomplish this goal, evaluating user interaction automatically is crucial, and it has been broadly explored. However, most works focus in long interaction sessions, which makes it difficult to tell how individual interface components influence usability. In contrast, this work aims to compare how different widgets perform for the same task, in the context of evaluating alternative designs for small components, implemented as refactorings. For this purpose, we propose a unified score to compare the widgets involved in each refactoring by the level of effort required by users to interact with them. This score is based on micro-measures automatically captured from interaction logs, so it can be automatically predicted. We show the results of predicting such score using a decision tree.Laboratorio de Investigación y Formación en Informática Avanzada2019-05info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/119016enginfo:eu-repo/semantics/altIdentifier/isbn/978-1-4503-5971-9info:eu-repo/semantics/altIdentifier/url/https://dl.acm.org/doi/10.1145/3290607.3312902info:eu-repo/semantics/altIdentifier/doi/10.1145/3290607.3312902info:eu-repo/semantics/altIdentifier/hdl/11746/10677info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:28:04Zoai:sedici.unlp.edu.ar:10915/119016Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:28:04.808SEDICI (UNLP) - Universidad Nacional de La Platafalse |
dc.title.none.fl_str_mv |
One Metric for All: Calculating Interaction Effort of Individual Widgets |
title |
One Metric for All: Calculating Interaction Effort of Individual Widgets |
spellingShingle |
One Metric for All: Calculating Interaction Effort of Individual Widgets Grigera, Julián Ciencias Informáticas Web usability Interactivity Usability refactoring A/B testing User interaction metrics |
title_short |
One Metric for All: Calculating Interaction Effort of Individual Widgets |
title_full |
One Metric for All: Calculating Interaction Effort of Individual Widgets |
title_fullStr |
One Metric for All: Calculating Interaction Effort of Individual Widgets |
title_full_unstemmed |
One Metric for All: Calculating Interaction Effort of Individual Widgets |
title_sort |
One Metric for All: Calculating Interaction Effort of Individual Widgets |
dc.creator.none.fl_str_mv |
Grigera, Julián Gardey, Juan Cruz Rodríguez, Andrés Santiago Garrido, Alejandra Rossi, Gustavo Héctor |
author |
Grigera, Julián |
author_facet |
Grigera, Julián Gardey, Juan Cruz Rodríguez, Andrés Santiago Garrido, Alejandra Rossi, Gustavo Héctor |
author_role |
author |
author2 |
Gardey, Juan Cruz Rodríguez, Andrés Santiago Garrido, Alejandra Rossi, Gustavo Héctor |
author2_role |
author author author author |
dc.subject.none.fl_str_mv |
Ciencias Informáticas Web usability Interactivity Usability refactoring A/B testing User interaction metrics |
topic |
Ciencias Informáticas Web usability Interactivity Usability refactoring A/B testing User interaction metrics |
dc.description.none.fl_txt_mv |
Automating usability diagnose and repair can be a powerful assistance to usability experts and even less knowledgeable developers. To accomplish this goal, evaluating user interaction automatically is crucial, and it has been broadly explored. However, most works focus in long interaction sessions, which makes it difficult to tell how individual interface components influence usability. In contrast, this work aims to compare how different widgets perform for the same task, in the context of evaluating alternative designs for small components, implemented as refactorings. For this purpose, we propose a unified score to compare the widgets involved in each refactoring by the level of effort required by users to interact with them. This score is based on micro-measures automatically captured from interaction logs, so it can be automatically predicted. We show the results of predicting such score using a decision tree. Laboratorio de Investigación y Formación en Informática Avanzada |
description |
Automating usability diagnose and repair can be a powerful assistance to usability experts and even less knowledgeable developers. To accomplish this goal, evaluating user interaction automatically is crucial, and it has been broadly explored. However, most works focus in long interaction sessions, which makes it difficult to tell how individual interface components influence usability. In contrast, this work aims to compare how different widgets perform for the same task, in the context of evaluating alternative designs for small components, implemented as refactorings. For this purpose, we propose a unified score to compare the widgets involved in each refactoring by the level of effort required by users to interact with them. This score is based on micro-measures automatically captured from interaction logs, so it can be automatically predicted. We show the results of predicting such score using a decision tree. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-05 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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eng |
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