Teachers Analyzing Sampling With TinkerPlots

Autor: Maria Niedja Pereira Martins, Theodosia Prodromou, Carlos Augusto Monteiro
Rok vydání: 2017
Předmět:
Popis: The teaching of statistics at the secondary level should provide statistical literacy for students who interact with data in several everyday situations. Therefore, it is crucial that the teacher education can provide a wider variety of situations in which teachers can learn how to improve students' statistical literacy. The conceptualization of sampling is crucial to understand statistical data. However, this topic is not generally emphasized in school curriculum or in teacher education programs. This chapter discusses a study on how primary school teachers understand issues of size and representativeness of samples using TinkerPlots 2.0 software. The participants were four teachers from a public school in Brazil. The research protocol followed three phases: interviews to identify the teacher's profile and their statistical knowledge; a familiarization session with TinkerPlots; and a session to use the software to solve tasks involving sampling. The results showed that the teachers began to consider aspects of data variation to determine when representative samples were presented using TinkerPlots. The ability to select samples and analyze them seemed to contribute to improve their understanding about sample size and representativeness. Since the purpose of the study was to explore teacher education activities that could support development of aspects of statistical literacy, further analysis of findings from the study offered insights into design of tasks to help teachers teach sampling as part of statistical literacy. For example, the analysis suggested that the questions asked during the research sections should not only explore the participants´ knowledge on the sample size or the confidence level, but should also promote reflection on the meanings assigned to tasks, leading to discussion of the skills required for statistical literacy in the Big Data era.
Databáze: OpenAIRE