PROMOTING MODELING AND COVARIATIONAL REASONING AMONG SECONDARY SCHOOL STUDENTS IN THE CONTEXT OF BIG DATA

Authors

  • EINAT GIL University of Toronto and Levinsky College of Education
  • ALISON L. GIBBS University of Toronto

DOI:

https://doi.org/10.52041/serj.v16i2.189

Keywords:

Statistics education research, Statistical modeling, Design of learning environment, Representational gestures

Abstract

In this study, we follow students’ modeling and covariational reasoning in the context of learning about big data. A three-week unit was designed to allow 12th grade students in a mathematics course to explore big and mid-size data using concepts such as trend and scatter to describe the relationships between variables in multivariate settings. Students’ emergent ideas were followed along a varied learning trajectory that included computer-supported collaborative and inquiry-based approaches, using visualization tools and statistical software to explore data and fit a suitable trend, and student presentations of investigations. Findings show progress in some components of students’ reasoning and modeling of covariation, and indicate which features of the unit design might contribute to it.

First published November 2017 at Statistics Education Research Journal Archives

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Published

2022-06-15

Issue

Vol. 16 No. 2 (2017): SPECIAL ISSUE: STATISTICAL REASONING ABOUT MODELS AND MODELLING IN THE CONTEXT OF INFORMAL STATISTICAL INFERENCE

Section

Regular Articles