Popis: |
Recent studies in statistical education have discussed the potential in using statistical data called big data – information from large databases that are frequently produced and have relative accessibility. However, the prescribed school curricula are not always in line with most recent recommendations of statistics education scholars, and implemented curricula also do not fully utilize elements that contribute to the learning of statistics, such as technological artefacts. This chapter discusses and compares explicit and implicit prescriptions related to the use of big data in statistics education in the basic education curricula of Brazil and Australia. The study used a qualitative documentary approach. The documentary artefacts used included guidelines and curricular programs available online. For the Brazilian context, the research was conducted online, collecting curriculum documents from 27 Brazilian states. Forty-five documents were selected and analysed in order to identify potentialities in the teaching of statistics for the secondary level of schooling. The content analysis indicated that only some curricular documents address the issue of big data, and even those documents did not explicitly refer to big data or open data. However, the documents analysed did discuss the use of Information and Communication Technologies. Such recommendations are still discussed in a general way and more focused on data handling. The analysis of the Australian curricula documents is of particular interest as the development of statistics education is a major area of research interest in Australia, and this has influenced recent Australian curricular reform. Therefore, we intend to examine Brazilian and Australian contexts in order to identify limits and possibilities for utilization of big data in school curriculum. The chapter concludes with suggestions for the development and inclusion of knowledge and practices for teaching big data in statistics, as well as a call for adding these elements to teacher-education programs, as current programs do not seem to explore these concerns. |