Modeling the growth of students' covariational reasoning during an introductory statistics course

Andrew S Zieffler, Joan B Garfield

Research output: Contribution to journalArticlepeer-review

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.
Original languageEnglish (US)
Pages (from-to)7-31
Number of pages25
JournalStatistics Education Research Journal
Volume8
Issue number1
StatePublished - 2009

Keywords

  • also referred to
  • as covariational reasoning
  • between two variables
  • covariation
  • data
  • growth modeling
  • involves knowing how to
  • or reasoning about bivariate
  • or relationship
  • reasoning about association
  • statistics education research
  • the importance of understanding
  • topic sequencing

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