Modelagem de dados abertos governamentais da educação baseada em redes: projeto escolas similares

Abstract

The implementation of the Open Data Policy and Plan of the National Institute of Educational Studies and Research Anísio Teixeira (INEP), ratified by ordinance nº 380, dated June 15, 2020, is founded on the principles of increasing the availability of information about governmental activities and disseminating data sets on Brazilian education to society. In this context, this study primarily aims to develop a knowledge construction model based on complex networks, fueled by open government data, to identify similarities between schools, which will be named the Similarity Networks Model (SNM), to depict connections, and potential connections, among schools in the microregion of Salvador (Bahia). Therefore, the goal is to identify schools with similar features to foster collaboration and knowledge dissemination among them, aiming for collective problem-solving. The SNM was crafted using data gathered from the School Censuses from 2019 to 2021 and the Basic Education Development Index (IDEB) results from 2019 to 2021, collected by the Brazilian Basic Education Evaluation System (SAEB), affiliated with the National Institute of Educational Studies and Research Anísio Teixeira (INEP). Thus, a knowledge modeling based on the FAIR (Findable, Accessible, Interoperable, Reusable) principles was developed for the application of data sets disseminated by the SAEB system. The exploratory research merges qualitative and quantitative approaches, adopting documentary research and Social Network Analysis (SNA) as its methodology to represent and establish connections between similar schools. The research outcomes are showcased through the development of the "School Similar" framework, used for network processing, and the Open Government Data Lab of Education (LABDAGE) platform for data sharing and visualization by the community. The identification of school profiles is displayed to enable its replication in other Brazilian microregions. In conclusion, the study indicates the optimization of data disseminated by SAEB, whether for scientific research or to underpin evidence-based policy actions. Furthermore, the study underscores the significance of developing models that enable researchers, public managers, and the community to recognize, access, use, and reuse information for the development of actions within public education networks.