Um framework conceitual para a concepção de ecossistemas inteligentes de aprendizagem

• Ano de defesa: 2022
• Autor(a) principal: Silveira, Pedro David Netto
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Doutorado em Ciência da Computação; Centro Tecnológico; UFES; Programa de Pós-Graduação em Informática
• Palavras-chave em Português: Ecossistema de aprendizagem; Smart learning environments; Framework; Cultura digital; Ontologia; subject.br-rjbn; Ciência da Computação
• Link de acesso: http://repositorio.ufes.br/handle/10/16345

With the digital culture advent from the advancement of technology, we have lived an opportune moment to make our interactions more flexible. In the educational context this is no different. Schools need mechanisms to enhance student learning, supporting the development of skills and attitudes in the application of the knowledge built. But this is not happening, since our educational system is still heavily based on the same traditional teaching methods and techniques. In this thesis we address part of the limits of the current school and its weaknesses to deal with the changes that education will undergo in this decade, given that personalization, collaboration and informal learning will play a prominent role in educational processes, which will be supported by information and communication technology and its ubiquity With this in mind, our research deals, among other things, with the promotion of interactions in learning ecosystems, valuing learning not only at school, but in different social contexts and throughout life, seeking a personalized and flexible learning process. This can be achieved with intelligent learning environments. Thus, the general objective of this work is the development of a conceptual framework for modeling these environments. In this way, we investigated how the promotion and management of interactions at learning ecosystems promote the construction of knowledge in different social contexts and throughout life, with a personalized and flexible learning process, and we concluded that this can be achieved with Smart Learning Environments. Thus, the general objective of this work is the development of a conceptual Framework for modeling these environments. The research was developed following the Design Science Research (DSR) methodology and our contribution includes: (i) the development of an ontology (reference and operational) for learning ecosystems in digital culture; (ii) a Framework to support the modeling of Smart Learning Environments; (iii) the implementation and testing of an intelligent environment designed with the Framework, as a proof of concept of the thesis. All these devices were evaluated and validated, so that the results indicate that they have successful applicability inside and outside the academic context.