TY - CHAP
T1 - Reasoning About Data
AU - Biehler, Rolf
AU - Frischemeir, Daniel
AU - Reading, Christine
AU - Shaughnessy, J Michael
PY - 2018
Y1 - 2018
N2 - Many decisions in politics, economics, and society are based on data and statistics. In order to participate as a responsible citizen, it is essential to have a solid grounding in reasoning about data. Reasoning about data is a fundamental human activity; its components can be found in nearly every profession and in most school curricula in the world. This chapter reviews past and recent research on reasoning about data across all ages of learners from primary school to adults. Specifically in this chapter, the term reasoning about data is defined, the implementation of reasoning about data in the curricula of different countries is investigated, and research studies of learner reasoning about distribution, variation, comparing groups, and association, which are fundamental concepts when reasoning about data, are reviewed. The research review presented includes references to existing frameworks and taxonomies that can assess learner reasoning in regard to these concepts and discusses the influence of digital tools to enhance learner statistical reasoning. Finally, some insights for future directions in research about reasoning about data are provided.
AB - Many decisions in politics, economics, and society are based on data and statistics. In order to participate as a responsible citizen, it is essential to have a solid grounding in reasoning about data. Reasoning about data is a fundamental human activity; its components can be found in nearly every profession and in most school curricula in the world. This chapter reviews past and recent research on reasoning about data across all ages of learners from primary school to adults. Specifically in this chapter, the term reasoning about data is defined, the implementation of reasoning about data in the curricula of different countries is investigated, and research studies of learner reasoning about distribution, variation, comparing groups, and association, which are fundamental concepts when reasoning about data, are reviewed. The research review presented includes references to existing frameworks and taxonomies that can assess learner reasoning in regard to these concepts and discusses the influence of digital tools to enhance learner statistical reasoning. Finally, some insights for future directions in research about reasoning about data are provided.
KW - Mathematics and Numeracy Curriculum and Pedagogy
UR - https://nla.gov.au/anbd.bib-an61462127
U2 - 10.1007/978-3-319-66195-7
DO - 10.1007/978-3-319-66195-7
M3 - Chapter
SN - 9783319661957
SN - 9783319661933
T3 - Springer International Handbooks of Education
SP - 139
EP - 192
BT - International Handbook of Research in Statistics Education
A2 - Ben-Zvi, Dani
A2 - Makar, Katie
A2 - Garfield, Joan
PB - Springer
CY - Cham, Switzerland
ER -