«Svaret er 128 000, for verdien før er 64 000, og verdien doblar seg kvar gong x-aksen er forlenga» : Ein designstudie om eit tverrfagleg oppgåvesett i matematikk og samfunnskunnskap som støttar elevar si tolking av boblediagrammet til Gapminder

Abstract

The new Norwegian curriculum of 2020 has an increased focus on interdisciplinary education. In addition, numeracy is one of five basic skills all subjects are supposed to help the students develop. An important question is, therefore, how this interdisciplinarity should be implemented into the teaching. Therefore, I set my study at the crossroad of social studies and mathematics in high school, with the consideration that social and political decisions are increasingly based on data and the technological development enables us to collect and visualize massive sets of data, known as big data. This have led to a greater need for students to be able to read and interpret data visualizations regarding social issues.The data visualization central in my study is Gapminder’s bubble chart, which displays the changes in life expectancy, population and GDP per capita in all countries from 1800 to today. It is both dynamic and interactive. Consequently, its complexities require careful planning of teaching, in order to use it successfully in a classroom setting. In my research, I have sought to understand what characterizes an interdisciplinary set of tasks that enables students to read and interpret Gaminder’s bubble chart. In my study, I used an approach known as design research to develop lesson material. Startingfrom a study by Tønnessen (2020)regarding the same bubble chart, I have done multiple rounds of designing, testing and reviewing the set of tasks. The final set of tasks were tested through task-based interviews with two students attending first year of high school. Due to the corona crisis, a data collection within a school class was not feasible, but the small sample also yielded insightful results. When designing the tasks and analyzing students’ work with it, I made use of Curcio’s (1987)concepts: reading in, between and beyond the data.