Modelo do estudante baseado em emoções e perfis de personalidade para recomendação de estratégias pedagógicas personalizadas

Emotions affect directly in the learning process. Students who are in a harmful emotion to learning can not assimilate in the best possible way, the content that is offered. Thus, this research proposes a student model based on emotions and personality profiles for the purpose of developing the stud...

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Detalles Bibliográficos
Autor: Melo, Sara Luzia de
Tipo de recurso: tesis de maestría
Estado:Versión publicada
Fecha de publicación:2016
País:Brasil
Institución:Universidade Federal de Uberlândia (UFU)
Repositorio:Repositório Institucional da UFU
Idioma:portugués
OAI Identifier:oai:repositorio.ufu.br:123456789/18280
Acceso en línea:https://repositorio.ufu.br/handle/123456789/18280
http://doi.org/10.14393/ufu.di.2016.517
Access Level:acceso abierto
Palabra clave:Computação
Personalidade
Inteligência emocional
Emoções
Modelo do estudante
Computação afetiva
Student model
Affective computing
Emotional inteligence
Personality
Emtions
CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
Descripción
Sumario:Emotions affect directly in the learning process. Students who are in a harmful emotion to learning can not assimilate in the best possible way, the content that is offered. Thus, this research proposes a student model based on emotions and personality profiles for the purpose of developing the student affective profile in a Virtual Learning Environment. For a computational validation modeling the classification of Personality profiles and Prediction of Pedagogical Strategies were developed. The classification of personality profiles was performed by an Artificial Neural Network. Furthermore, an experimental analysis to verify the most appropriate training basis from three sets of training was carried out, as well as simulations with different architectures of Neural Network. As a result, there were an accuracy of 97.28 % for general recognition of the nine personality profiles. The definition of pedagogical strategies was conducted by the association of basics emotions with the advice to the proposed educator in Personality Profiles theory. Was used the Decision Tree technique to induce classification rules in order to determine the most appropriate teaching strategies every Personality Profile. Thus, if a harmful emotion to learning is detected, the pedagogical module executes instructions through the information contained in the custom Student Model providing the stimulus student and/or motivation according to their individual characteristics and thus bring it emotion that promotes the learning.