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MODELING THE GROWTH OF STUDENTS’ COVARIATIONAL REASONING DURING AN INTRODUCTORY STATISTICS COURSE

Andrew Zieffler, Joan Garfield

2022Statistics Education Research Journal61 citationsDOIOpen Access PDF

Abstract

This study examined students’ development of reasoning about quantitative bivariate data during a one-semester university-level introductory statistics course. There were three research questions of interest: (1) What is the nature, or pattern of change in students’ development in reasoning throughout the course?; (2) Is the sequencing of quantitative bivariate data within the course associated with differences in the pattern of change in reasoning?; and (3) Are changes in reasoning about foundational concepts of distribution associated with differences in the pattern of change? Covariational and distributional reasoning were measured four times during the course, across four cohorts of students. A linear mixed-effects model was used to analyze the data, revealing some interesting trends and relationships regarding the development of covariational reasoning. First published May 2009 at Statistics Education Research Journal Archives

Topics & Concepts

Mathematics educationBivariate analysisProportional reasoningQualitative reasoningStatistics educationBivariate dataCourse (navigation)PsychologyStatisticsComputer scienceMathematicsArtificial intelligencePhysicsAstronomyStatistics Education and MethodologiesInnovations in Educational Methods
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