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Dimitrios
STAMOVLASIS and Georgios TSAPARLIS
ABSTRACT: This work examines the role of working-memory capacity in problem solving in chemistry, and in particular it re-examines the validity of the Johnstone-El Banna predictive model, by employing non-linear methods. The study correlates the students' information- processing capacity with their performance, by using fractal geometry adapted for treating problem-solving data. The rank order of the subjects' achievement scores and their working-memory capacities were treated as dynamic flows and found to possess different geometric characteristics depending on the complexity of the problem and the method of marking. The classification and interpretation of these characteristics were made using concepts from complexity theory, such as correlation exponents, fractal dimensions and entropy. The findings support the hypothesis that long-range correlations exist between the rank order of the subjects' achievement scores and their working-memory capacity, and are in agreement with the Johnstone-El Banna model. [Chem. Educ. Res. Pract. Eur.: 2000, 1, 375-380] KEY WORDS: problem-solving; Johnstone-El Banna predictive model; working memory capacity; mental-demand of a problem; complexity theory; working-memory random walk; Hurst exponent; long-range correlations; order
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