An Entropic Approach to Technology Enable Learning and Social Computing
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10174/33044 https://doi.org/10.3233/FAIA220436 |
Resumo: | Understanding one’s own behavior is challenging in itself; understanding a group of different individuals and the many relationships between these individuals is even more complex. Imagine the amazing complexity of a large system made up of thousands of individuals and hundreds of groups, with countless relationships between those individuals and groups. However, despite this difficulty, organizations must be managed. Indeed, ultimately the organization's work is done by people, individually or collectively, alone or in combination with technology. Therefore, organizational behavior management is the central task of management work – it involves understanding the behavior patterns of individuals, groups, and organizations, predicting what behavioral reactions will be elicited by various managerial actions and finally applying this understanding. Undeniably, society's work is often done by organizations, and the role of management is to make organizations do that work. Without it, our entire society would quickly stop operating. Not only would the products you have come to know and love swiftly to evaporate from store shelves; food itself would suddenly become scarce, having drastic effects on huge numbers of people. To this end, the term Technology-Enhanced Learning is used to support workers’ learning about technology; the gap between what is understood to be satisfactory and the current level of knowledge of the workforce is addressed by a Logic-programming-based Social Computing Framework entitled An Entropic Approach to Knowledge Representation and Reasoning, which relies on computational structures built on Artificial Neural Networks and Cases-based Thinking, as well as predictions and/or assessments, to empower the level of knowledge of the employees, here in technology, later in other areas. |
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An Entropic Approach to Technology Enable Learning and Social ComputingEntropyTechnology Enable LearningSocial ComputingArtificial Neural NetworksCase-based ReasoningComputational SustainabilityUnderstanding one’s own behavior is challenging in itself; understanding a group of different individuals and the many relationships between these individuals is even more complex. Imagine the amazing complexity of a large system made up of thousands of individuals and hundreds of groups, with countless relationships between those individuals and groups. However, despite this difficulty, organizations must be managed. Indeed, ultimately the organization's work is done by people, individually or collectively, alone or in combination with technology. Therefore, organizational behavior management is the central task of management work – it involves understanding the behavior patterns of individuals, groups, and organizations, predicting what behavioral reactions will be elicited by various managerial actions and finally applying this understanding. Undeniably, society's work is often done by organizations, and the role of management is to make organizations do that work. Without it, our entire society would quickly stop operating. Not only would the products you have come to know and love swiftly to evaporate from store shelves; food itself would suddenly become scarce, having drastic effects on huge numbers of people. To this end, the term Technology-Enhanced Learning is used to support workers’ learning about technology; the gap between what is understood to be satisfactory and the current level of knowledge of the workforce is addressed by a Logic-programming-based Social Computing Framework entitled An Entropic Approach to Knowledge Representation and Reasoning, which relies on computational structures built on Artificial Neural Networks and Cases-based Thinking, as well as predictions and/or assessments, to empower the level of knowledge of the employees, here in technology, later in other areas.IOS Press2022-12-29T17:01:44Z2022-12-292022-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/33044http://hdl.handle.net/10174/33044https://doi.org/10.3233/FAIA220436engAlves, V., Miranda, J., Dawa, H., Fernandes, F., Pombal, F., Ribeiro, J., Fdez-Riverola, F., Analide, C., Vicente, H. & Neves, J., An Entropic Approach to Technology Enable Learning and Social Computing. Frontiers in Artificial Intelligence and Applications, 360: 140–153, 2022.0922-6389 (paper)1879-8314 (electronic)https://ebooks.iospress.nl/volumearticle/61891REQUIMTE/LAQVvitoralves@estg.ipvc.ptjose.luis.miranda@sapo.pthdawa@yahoo.comfernandes.filipe.fa@gmail.comfernanda.goncalves@ipsn.cespu.ptjribeiro@estg.ipvc.ptriverola@uvigo.esanalide@di.uminho.pthvicente@uevora.ptjneves@di.uminho.ptAlves, VitorMiranda, JoséDawa, HossamFernandes, FilipePombal, FernandaRibeiro, JorgeFdez-Riverola, FlorentinoAnalide, CesarVicente, HenriqueNeves, Joséinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:33:57Zoai:dspace.uevora.pt:10174/33044Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:21:47.587319Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
An Entropic Approach to Technology Enable Learning and Social Computing |
title |
An Entropic Approach to Technology Enable Learning and Social Computing |
spellingShingle |
An Entropic Approach to Technology Enable Learning and Social Computing Alves, Vitor Entropy Technology Enable Learning Social Computing Artificial Neural Networks Case-based Reasoning Computational Sustainability |
title_short |
An Entropic Approach to Technology Enable Learning and Social Computing |
title_full |
An Entropic Approach to Technology Enable Learning and Social Computing |
title_fullStr |
An Entropic Approach to Technology Enable Learning and Social Computing |
title_full_unstemmed |
An Entropic Approach to Technology Enable Learning and Social Computing |
title_sort |
An Entropic Approach to Technology Enable Learning and Social Computing |
author |
Alves, Vitor |
author_facet |
Alves, Vitor Miranda, José Dawa, Hossam Fernandes, Filipe Pombal, Fernanda Ribeiro, Jorge Fdez-Riverola, Florentino Analide, Cesar Vicente, Henrique Neves, José |
author_role |
author |
author2 |
Miranda, José Dawa, Hossam Fernandes, Filipe Pombal, Fernanda Ribeiro, Jorge Fdez-Riverola, Florentino Analide, Cesar Vicente, Henrique Neves, José |
author2_role |
author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Alves, Vitor Miranda, José Dawa, Hossam Fernandes, Filipe Pombal, Fernanda Ribeiro, Jorge Fdez-Riverola, Florentino Analide, Cesar Vicente, Henrique Neves, José |
dc.subject.por.fl_str_mv |
Entropy Technology Enable Learning Social Computing Artificial Neural Networks Case-based Reasoning Computational Sustainability |
topic |
Entropy Technology Enable Learning Social Computing Artificial Neural Networks Case-based Reasoning Computational Sustainability |
description |
Understanding one’s own behavior is challenging in itself; understanding a group of different individuals and the many relationships between these individuals is even more complex. Imagine the amazing complexity of a large system made up of thousands of individuals and hundreds of groups, with countless relationships between those individuals and groups. However, despite this difficulty, organizations must be managed. Indeed, ultimately the organization's work is done by people, individually or collectively, alone or in combination with technology. Therefore, organizational behavior management is the central task of management work – it involves understanding the behavior patterns of individuals, groups, and organizations, predicting what behavioral reactions will be elicited by various managerial actions and finally applying this understanding. Undeniably, society's work is often done by organizations, and the role of management is to make organizations do that work. Without it, our entire society would quickly stop operating. Not only would the products you have come to know and love swiftly to evaporate from store shelves; food itself would suddenly become scarce, having drastic effects on huge numbers of people. To this end, the term Technology-Enhanced Learning is used to support workers’ learning about technology; the gap between what is understood to be satisfactory and the current level of knowledge of the workforce is addressed by a Logic-programming-based Social Computing Framework entitled An Entropic Approach to Knowledge Representation and Reasoning, which relies on computational structures built on Artificial Neural Networks and Cases-based Thinking, as well as predictions and/or assessments, to empower the level of knowledge of the employees, here in technology, later in other areas. |
publishDate |
2022 |
dc.date.none.fl_str_mv |
2022-12-29T17:01:44Z 2022-12-29 2022-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10174/33044 http://hdl.handle.net/10174/33044 https://doi.org/10.3233/FAIA220436 |
url |
http://hdl.handle.net/10174/33044 https://doi.org/10.3233/FAIA220436 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Alves, V., Miranda, J., Dawa, H., Fernandes, F., Pombal, F., Ribeiro, J., Fdez-Riverola, F., Analide, C., Vicente, H. & Neves, J., An Entropic Approach to Technology Enable Learning and Social Computing. Frontiers in Artificial Intelligence and Applications, 360: 140–153, 2022. 0922-6389 (paper) 1879-8314 (electronic) https://ebooks.iospress.nl/volumearticle/61891 REQUIMTE/LAQV vitoralves@estg.ipvc.pt jose.luis.miranda@sapo.pt hdawa@yahoo.com fernandes.filipe.fa@gmail.com fernanda.goncalves@ipsn.cespu.pt jribeiro@estg.ipvc.pt riverola@uvigo.es analide@di.uminho.pt hvicente@uevora.pt jneves@di.uminho.pt |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
IOS Press |
publisher.none.fl_str_mv |
IOS Press |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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