Applying Catastrophe Theory to an Information-Processing Model of Problem Solving in Science Education
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Stamovlasis, D.
(EN)
Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Χημείας
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Stamovlasis, D.
(EN)
In this study, we test an information-processing model (IPM) of problem solving in science education, namely the working memory overload model, by applying catastrophe theory. Changes in students' achievement were modeled as discontinuities within a cusp catastrophe model, where working memory capacity was implemented as asymmetry and the degree of field dependence/independence and logical thinking as bifurcation parameters. Data from achievement scores of high school students in nonalgorithmic problem solving (chemical, organic-synthesis problems) were used and analyzed, using dynamic difference equations and statistical regression techniques. The dependent measure was the score difference in problems of varying demand from M = 3 to M = 8. The cusp catastrophe models proved superior (R2 = .73.84) to the pre-post linear counterpart (R2 =.52-.66). The empirical evidence for the catastrophe effect supports the nonlinear model for the working memory overload hypothesis. The results add to research endeavors that built bridges between concepts of the theory of nonlinear dynamical systems and problem solving in science education, and to IPM as well. Finally, the theoretical and practical implications are discussed. (c) 2012 Wiley Periodicals, Inc. Sci Ed 96:392-410, 2012
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