Modeling First: Applying Learning Science to the Teaching of Introductory Statistics

Students learn many concepts in the introductory statistics course, but even our most successful students end up with rigid, ritualized knowledge that does not transfer easily to new situations. In this article we describe our attempt to apply theories and findings from learning science to the desig...

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Bibliographic Details
Main Authors: Ji Y. Son, Adam B. Blake, Laura Fries, James W. Stigler
Format: Article
Language:English
Published: Taylor & Francis Group 2020-10-01
Series:Journal of Statistics Education
Subjects:
Online Access:http://dx.doi.org/10.1080/10691898.2020.1844106
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spelling doaj-4f4d4699a4024cd593d130dbd3d15e7c2020-11-25T04:09:17ZengTaylor & Francis GroupJournal of Statistics Education1069-18982020-10-010012310.1080/10691898.2020.18441061844106Modeling First: Applying Learning Science to the Teaching of Introductory StatisticsJi Y. Son0Adam B. Blake1Laura Fries2James W. Stigler3California State UniversityUniversity of CaliforniaUniversity of CaliforniaUniversity of CaliforniaStudents learn many concepts in the introductory statistics course, but even our most successful students end up with rigid, ritualized knowledge that does not transfer easily to new situations. In this article we describe our attempt to apply theories and findings from learning science to the design of a statistics course that aims to help students build a coherent and interconnected representation of the domain. The resulting practicing connections approach provides students with repeated opportunities to practice connections between core concepts (especially the concepts of statistical model, distribution, and randomness), key representations (R programming language and computational techniques such as simulation and bootstrapping), and real-world situations statisticians face as they explore variation, model variation, and evaluate and compare statistical models. We provide a guided tour through our curriculum implemented in an interactive online textbook (CourseKata.org) and then provide some evidence that students who complete the course are able to transfer what they have learned to the learning of new statistical techniques.http://dx.doi.org/10.1080/10691898.2020.1844106statistical modelpracticing connectionstransferintroductory statisticssimulationlearning sciences
collection DOAJ
language English
format Article
sources DOAJ
author Ji Y. Son
Adam B. Blake
Laura Fries
James W. Stigler
spellingShingle Ji Y. Son
Adam B. Blake
Laura Fries
James W. Stigler
Modeling First: Applying Learning Science to the Teaching of Introductory Statistics
Journal of Statistics Education
statistical model
practicing connections
transfer
introductory statistics
simulation
learning sciences
author_facet Ji Y. Son
Adam B. Blake
Laura Fries
James W. Stigler
author_sort Ji Y. Son
title Modeling First: Applying Learning Science to the Teaching of Introductory Statistics
title_short Modeling First: Applying Learning Science to the Teaching of Introductory Statistics
title_full Modeling First: Applying Learning Science to the Teaching of Introductory Statistics
title_fullStr Modeling First: Applying Learning Science to the Teaching of Introductory Statistics
title_full_unstemmed Modeling First: Applying Learning Science to the Teaching of Introductory Statistics
title_sort modeling first: applying learning science to the teaching of introductory statistics
publisher Taylor & Francis Group
series Journal of Statistics Education
issn 1069-1898
publishDate 2020-10-01
description Students learn many concepts in the introductory statistics course, but even our most successful students end up with rigid, ritualized knowledge that does not transfer easily to new situations. In this article we describe our attempt to apply theories and findings from learning science to the design of a statistics course that aims to help students build a coherent and interconnected representation of the domain. The resulting practicing connections approach provides students with repeated opportunities to practice connections between core concepts (especially the concepts of statistical model, distribution, and randomness), key representations (R programming language and computational techniques such as simulation and bootstrapping), and real-world situations statisticians face as they explore variation, model variation, and evaluate and compare statistical models. We provide a guided tour through our curriculum implemented in an interactive online textbook (CourseKata.org) and then provide some evidence that students who complete the course are able to transfer what they have learned to the learning of new statistical techniques.
topic statistical model
practicing connections
transfer
introductory statistics
simulation
learning sciences
url http://dx.doi.org/10.1080/10691898.2020.1844106
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