The co-emergence of aggregate and modelling reasoning1

Keren Aridor; Dani Ben-Zvi

doi:10.52041/serj.v16i2.184

The co-emergence of aggregate and modelling reasoning1

Keren Aridor, Dani Ben-Zvi

University of Haifa

Research output: Contribution to journal › Article › peer-review

Abstract

This article examines how two processes - reasoning with statistical modelling of a real phenomenon and aggregate reasoning - can co-emerge. We focus in this case study on the emergent reasoning of two fifth graders (aged 10) involved in statistical data analysis, informal inference, and modelling activities using TinkerPlotsTM. We describe nine phases of the students' articulations of aggregate and modelling reasoning as they explored a small sample, constructed a model and generated random samples from this model to examine its validity. These phases are distinguished by the students' views toward data, variability, and models. We discuss implications and limitations of the results. Despite the idiosyncrasy of the case, the lessons are important because they open a new direction for research about reasoning with data and models.

Original language	American English
Pages (from-to)	38-63
Number of pages	26
Journal	Statistics Education Research Journal
Volume	16
Issue number	2
DOIs	https://doi.org/10.52041/serj.v16i2.184
State	Published - 1 Nov 2017

Keywords

Aggregate reasoning
Exploratory data analysis
Informal statistical inference
Statistical model and modelling
Statistics education research

All Science Journal Classification (ASJC) codes

Statistics and Probability
Education

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10.52041/serj.v16i2.184

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title = "The co-emergence of aggregate and modelling reasoning1",

abstract = "This article examines how two processes - reasoning with statistical modelling of a real phenomenon and aggregate reasoning - can co-emerge. We focus in this case study on the emergent reasoning of two fifth graders (aged 10) involved in statistical data analysis, informal inference, and modelling activities using TinkerPlotsTM. We describe nine phases of the students' articulations of aggregate and modelling reasoning as they explored a small sample, constructed a model and generated random samples from this model to examine its validity. These phases are distinguished by the students' views toward data, variability, and models. We discuss implications and limitations of the results. Despite the idiosyncrasy of the case, the lessons are important because they open a new direction for research about reasoning with data and models.",

keywords = "Aggregate reasoning, Exploratory data analysis, Informal statistical inference, Statistical model and modelling, Statistics education research",

author = "Keren Aridor and Dani Ben-Zvi",

note = "Funding Information: This study was supported by the British Academy Small Research Grant Scheme (SG112288). The views expressed in this article do not necessarily reflect the views or policy of the British Academy. We deeply thank Cliff Konold, Janet Ainley, Dave Pratt and the Cool-Connections research group who participated in data analysis sessions of this research. We are grateful for the helpful comments of the anonymous reviewers of earlier versions of this manuscript. Publisher Copyright: {\textcopyright} International Association for Statistical Education (IASE/ISI), November, 2017.",

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N2 - This article examines how two processes - reasoning with statistical modelling of a real phenomenon and aggregate reasoning - can co-emerge. We focus in this case study on the emergent reasoning of two fifth graders (aged 10) involved in statistical data analysis, informal inference, and modelling activities using TinkerPlotsTM. We describe nine phases of the students' articulations of aggregate and modelling reasoning as they explored a small sample, constructed a model and generated random samples from this model to examine its validity. These phases are distinguished by the students' views toward data, variability, and models. We discuss implications and limitations of the results. Despite the idiosyncrasy of the case, the lessons are important because they open a new direction for research about reasoning with data and models.

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The co-emergence of aggregate and modelling reasoning1

Abstract

Keywords

All Science Journal Classification (ASJC) codes

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