TOM: tutor inteligente orientado a construção de mapas conceituais

• Ano de defesa: 2019
• Autor(a) principal: Boguski, Rodrigo Ruy
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Mestrado em Informática; Centro Tecnológico; UFES; Programa de Pós-Graduação em Informática
• Palavras-chave em Português: Intelligent systems; Concept maps; Data mining; Association rules; Assisted learning; Mapas conceituais; Tutor; Sistemas tutores inteligentes; Regras de associação; Aprendizagem assistida; Sistemas tutoriais inteligentes; Maquinas de ensinar; Mineração de dados (Computação); Aprendizagem; Ciência da Computação; 004
• Link de acesso: http://repositorio.ufes.br/handle/10/11201

Tutoring is a method for pedagogical interaction used for thousands of years. In this interaction, the tutor evaluates the student's learning during the course of the learning experiences, heals his doubts, follows his frequency, assists his motivation and provides support, usually in a timely manner, so that the cognitive overload resulting from the learning process itself is minimized, order to make that moment pleasant and satisfying. Having the knowledge of the needs of the students is still a great challenge for the teachers, because this is the first step to providing relevant help in order to contribute to their learning. From this perspective we develop a technique based on rules of association of data mining in order to identify the conceptual flaws in students so that, once this knowledge gap is known, it is filled in order to potentialize the cognitive process. In order to test these rules, we constructed an intelligent tutor system capable of using them and thus guide the student in the construction of conceptual maps from a proposed theme, having as main guideline the teacher's reference map and the respective rules of association that each concept of this map has. Thus, the missing information to the student is not presented in a destructured way, but with different levels of granularity, similarities and in the most appropriate sequence to catalyze learning. This method has as its underlying question a pedagogical approach that uses aspects of the theory of meaningful learning defended by Ausubel and complemented by Novak.