Reinforcing Students’ Correlation Comprehension

By Ken Li and Merrilyn Goos.

Published by The Learner Collection

Format Price
Article: Print $US10.00
Article: Electronic $US5.00

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.

Keywords: Correlation, Cognitive Model, Graphical Comprehension, Scatterplot, Visual Chunk

The International Journal of Learning, Volume 17, Issue 11, pp.261-274. Article: Print (Spiral Bound). Article: Electronic (PDF File; 699.542KB).

Dr. Ken Li

Lecturer, Department of Information and Communications Technology, Hong Kong Institute of Vocational Education, Hong Kong

Dr. Ken W. LI is a lecturer teaching Statistics and IT. He has been teaching in tertiary institutions in Australia, Canada and Hong Kong for many years. His current research areas are in the use of IT in Education, Human-computer Interaction, and Computer Simulation. He has developed teaching models and instruments for assessing learning outcomes of students. He has published a textbook, a book chapter, journal articles as well as conference papers. He is a member of various referee panels, and organizing committees of conferences and competitions.

Merrilyn Goos

Professor, Teaching and Educational Development Institute, The University of Queensland, Brisbane, Queensland, Australia

Prof. Merrilyn Goos is the Director of Teaching and Educational Development Institute at the University of Queensland, President of Mathematics Education Research Group of Australasia.


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