Aplicação de Learning Analytics para avaliação do desempenho de tutores a distância

• Ano de defesa: 2016
• Autor(a) principal: Souza, Rafael Castro de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal Rural do Semi-Árido; Brasil; UFERSA; Programa de Pós-Graduação em Ciência da Computação
• Palavras-chave em Português: Learning Analytics; Avaliação de tutores; Indicadores de desempenho comportamental na educação; Tutors rating; Behavioral performance indicators in education; CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://repositorio.ufersa.edu.br/handle/tede/648

The growing evolution of technology in conjunction with its computing resources has provided new expectations in several areas of research such as industry, health and education. Such integration of technology in these environments combined with its widespread use has led to an increase in the volume of stored data. Therefore, researchers then realized the possibility of analyzing this large volume information in order to extract knowledge, so that this information can, for example, help to support on making decision. When applied in the education area, the collection, measurement and analysis of educational data to identify factors that may impact positively or negatively the teaching process are called Learning Analytics. Given this perspective, this work presents an assessment tool of behavioral actions of tutors teaching mode disciplines distance, so that through this be possible to evaluate the behavior of tutors and classes, as well as identify tutor behaviors that may or may not be related to the behavior of the class. With the information resulting from this work, one can better understand the impact of the behavior of tutors in the teaching mode groups at a distance, and enables pedagogical interventions guided in concise information in order to alleviate the problems faced by this type of education