Reinforcing students’ correlation comprehension

Li, Ken and Goos, Merrilyn (2011) Reinforcing students’ correlation comprehension. International Journal of Learning, 17 11: 261-274.

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Author Li, Ken
Goos, Merrilyn
Title Reinforcing students’ correlation comprehension
Journal name International Journal of Learning   Check publisher's open access policy
ISSN 1447-9494
Publication date 2011-01-01
Sub-type Article (original research)
Volume 17
Issue 11
Start page 261
End page 274
Total pages 14
Place of publication Altona, VIC, Australia
Publisher Common Ground Publishing
Language eng
Abstract Graphical presentation of data provides a fast way of extracting information from data and is the primary method for illustrating complicated data structure, and thus facilitates the process of data examination. The graphical representation of data provides valuable clues to what and how further statistical work ought to be carried out because technically correct statistical graphics disclose significant elements of the information they represent and also serve as an alternative means of effective communication. Even though students who know how to draw statistical graphs and charts often fail to present data in proper graphical format and are unable to convey their thoughts about their findings from their graphical displays of data to their audience because they have difficulty gaining insights and seeing hidden relationships of data. This hinders the development of students’ graphical understanding of scatterplots, a statistical topic taught in undergraduate study. In this paper we present a critical review of current research in this area from three different perspectives: pedagogy, statistics and cognitive psychology. Specifically, Curcio (1987) outlined a classification model of reading graphical data from a mathematics educator’s perspective; Cook and Weisberg (1997) advocated a model of statistical graphing based on the statistician’s viewpoint; while Carpenter and Shah (1998) developed their model of graphical comprehension and interpretation from a cognitive science position. Arising from our synthesis of this research we propose a cognitive model of correlation comprehension which helps statistics lecturers to structure undergraduate students’ thought so as to reinforce their graphing capabilities when teaching how to solve correlation problems.
Keyword Correlation
Cognitive model
Graphical comprehension
Visual chunk
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2012 Collection
Institute for Teaching and Learning Innovation Publications
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Created: Mon, 26 Sep 2011, 19:59:45 EST by Professor Merrilyn Goos on behalf of Teaching & Educational Development Institute