An experience selecting quality features of apps for people with disabilities using abductive approach to explanatory theory generation

This study determines one of the most relevant quality factors of apps for people with disabilities utilizing the abductive approach to the generation of an explanatory theory. First, the abductive approach was concerned with the results’ description, established by the apps’ quality assessment, usi...

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Main Authors: Andres Larco, Carlos Montenegro, Cesar Yanez, Sergio Luján-Mora
Format: Article
Language:English
Published: PeerJ Inc. 2021-08-01
Series:PeerJ Computer Science
Subjects:
Online Access:https://peerj.com/articles/cs-595.pdf
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author Andres Larco
Carlos Montenegro
Cesar Yanez
Sergio Luján-Mora
author_facet Andres Larco
Carlos Montenegro
Cesar Yanez
Sergio Luján-Mora
author_sort Andres Larco
collection DOAJ
description This study determines one of the most relevant quality factors of apps for people with disabilities utilizing the abductive approach to the generation of an explanatory theory. First, the abductive approach was concerned with the results’ description, established by the apps’ quality assessment, using the Mobile App Rating Scale (MARS) tool. However, because of the restrictions of MARS outputs, the identification of critical quality factors could not be established, requiring the search for an answer for a new rule. Finally, the explanation of the case (the last component of the abductive approach) to test the rule’s new hypothesis. This problem was solved by applying a new quantitative model, compounding data mining techniques, which identified MARS’ most relevant quality items. Hence, this research defines a much-needed theoretical and practical tool for academics and also practitioners. Academics can experiment utilizing the abduction reasoning procedure as an alternative to achieve positivism in research. This study is a first attempt to improve the MARS tool, aiming to provide specialists relevant data, reducing noise effects, accomplishing better predictive results to enhance their investigations. Furthermore, it offers a concise quality assessment of disability-related apps.
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spelling doaj.art-fe7c55baf5aa4d1ea8ab3c19f457cc892022-12-21T23:33:19ZengPeerJ Inc.PeerJ Computer Science2376-59922021-08-017e59510.7717/peerj-cs.595An experience selecting quality features of apps for people with disabilities using abductive approach to explanatory theory generationAndres Larco0Carlos Montenegro1Cesar Yanez2Sergio Luján-Mora3Departamento de Informática y Ciencias de la Computación, Escuela Politécnica Nacional, Quito, Pichincha, EcuadorDepartamento de Informática y Ciencias de la Computación, Escuela Politécnica Nacional, Quito, Pichincha, EcuadorDepartamento de Informática y Ciencias de la Computación, Escuela Politécnica Nacional, Quito, Pichincha, EcuadorDepartment of Software and Computing Systems, Universidad de Alicante, Alicante, SpainThis study determines one of the most relevant quality factors of apps for people with disabilities utilizing the abductive approach to the generation of an explanatory theory. First, the abductive approach was concerned with the results’ description, established by the apps’ quality assessment, using the Mobile App Rating Scale (MARS) tool. However, because of the restrictions of MARS outputs, the identification of critical quality factors could not be established, requiring the search for an answer for a new rule. Finally, the explanation of the case (the last component of the abductive approach) to test the rule’s new hypothesis. This problem was solved by applying a new quantitative model, compounding data mining techniques, which identified MARS’ most relevant quality items. Hence, this research defines a much-needed theoretical and practical tool for academics and also practitioners. Academics can experiment utilizing the abduction reasoning procedure as an alternative to achieve positivism in research. This study is a first attempt to improve the MARS tool, aiming to provide specialists relevant data, reducing noise effects, accomplishing better predictive results to enhance their investigations. Furthermore, it offers a concise quality assessment of disability-related apps.https://peerj.com/articles/cs-595.pdfAbductionApps qualityData miningExplanatory theory generationPeople with disabilities
spellingShingle Andres Larco
Carlos Montenegro
Cesar Yanez
Sergio Luján-Mora
An experience selecting quality features of apps for people with disabilities using abductive approach to explanatory theory generation
PeerJ Computer Science
Abduction
Apps quality
Data mining
Explanatory theory generation
People with disabilities
title An experience selecting quality features of apps for people with disabilities using abductive approach to explanatory theory generation
title_full An experience selecting quality features of apps for people with disabilities using abductive approach to explanatory theory generation
title_fullStr An experience selecting quality features of apps for people with disabilities using abductive approach to explanatory theory generation
title_full_unstemmed An experience selecting quality features of apps for people with disabilities using abductive approach to explanatory theory generation
title_short An experience selecting quality features of apps for people with disabilities using abductive approach to explanatory theory generation
title_sort experience selecting quality features of apps for people with disabilities using abductive approach to explanatory theory generation
topic Abduction
Apps quality
Data mining
Explanatory theory generation
People with disabilities
url https://peerj.com/articles/cs-595.pdf
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