O uso do R e RStudio para gráficos estatísticos na educação básica

Abstract

This study maps and analyzes the academic literature on the use of the R language in the teaching of Statistics in Basic Education, with an emphasis on the education of Mathematics teachers, and proposes an educational resourse that supports the autonomous use of R and the RStudio environment for the construction and analysis of statistical graphs. By situating the research in a data-oriented social context shaped by the digital revolution and the expansion of systems based on artificial intelligence, the study argues that statistical reasoning, literacy, and thinking require more than computation, as they involve formulating questions, organizing and representing information, interpreting results, sustaining arguments, and making evidencebased decisions. The study adopts the State of Knowledge methodology, combined with content analysis, to identify, systematize, and interpret studies found in databases such as Google Scholar and the CAPES Catalog of Theses and Dissertations, using descriptors related to Statistics, Mathematics, curriculum, teacher education, and curricular documents, including specific searches for RStudio and the R language. The analysis indicates a mismatch between the centrality assigned to Statistics in Brazil’s National Common Curricular Base and the way the field is realized in initial teacher education and in instructional materials, with a recurring emphasis on procedures and quick answers at the expense of critical and contextualized interpretation. The mapping also shows that teacher-education proposals involving software often privilege stepby-step replication, giving less attention to explicit criteria for choosing graphs, to the discussion of construction parameters, and to the development of teacher autonomy to adapt and design investigative learning situations. As a contribution, the study presents a digital manual, progressively organized, that guides installation and initial steps, data import, and the construction of bar charts, histograms, pie charts, line charts, and scatter plots using both base R functions and the ggplot2 package, as well as recommendations on reproducibility and on adapting scripts to different school contexts. It concludes that the autonomous appropriation of R and RStudio strengthens procedural transparency, traceability of choices, and didactic intentionality, fostering a more investigative and critical teaching of Statistics aligned with contemporary demands for reading and interpreting data.