Um processo analítico de dados educacionais: uma abordagem baseada nos dados socioeconômicos e educacionais dos alunos

• Ano de defesa: 2019
• Autor(a) principal: Brasil, Pedrina Célia
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Brasil; UFRN; PROGRAMA DE PÓS-GRADUAÇÃO EM INOVAÇÃO EM TECNOLOGIAS EDUCACIONAIS
• Palavras-chave em Português: Learning analytics; Ambientes virtuais de aprendizagem; IFRN; CNPQ::CIENCIAS HUMANAS::EDUCACAO
• Link de acesso: https://repositorio.ufrn.br/jspui/handle/123456789/28336

The Federal Institute of Education, Science and Technology of Rio Grande do Norte (IFRN) has as mission the social transformation of the region in which it operates, contributing to the economic development of the country. According to its Political-Pedagogical Project (PPP), any action related to IFRN courses must be broadly integrated. However, the heterogeneity and the high number of students in class, allied to the lack of time and tools that help the pedagogical decision-making process, corroborate with a closed curricular organization that ignores the students' social context and favors the achievement. of standardized actions. Thus, this research aims to propose an analytical process that helps the teacher to interpret their learning context from the analysis of socioeconomic and educational data of the students of the institution. This work consists of an explanatory work, and applied results to the context of the IFRN. The Knowledge Discovery in Database (KDD) approach was used as inspiration to define the activities of this research, divided here in three stages: preproduction, production and postproduction. The preproduction stage involved discovery and interpretation activities of the problem. This was a systematic review of the literature in order to identify how the learning analysis is applied in teaching environments of Brazilian institutions and characterized the domain of this proposal. In the production stage a process was created for extracting, transforming and loading IFRN data. Through this process, data from the institution's system (Public Administration Unified System, SUAP) were dynamically preprocessed and loaded onto an online dimensional basis capable of supporting the functionality of an analytical data processing system without compromising the organization's daily transactions. The post-production stage involved evaluation and evolution activities of this work. In this was developed the SUAP-BI tool that promotes teachers descriptive and predictive analysis of student performance, relating this to the social context of students.