The Strategy-Specific Nature of Improvement: The Power Law Applies by Strategy Within Task

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Abstract
If strategy shifts speed up performance, learning curves should show discontinuities where such shifts occur. Relatively smooth curves appear consistently in the literature, however. To explore this incongruity, we examined learning when multiple strategies were used. We plotted power law learning curves for aggregated data from four mental arithmetic experiments and then plotted similar curves separately for each participant and strategy. We then evaluated the fits achieved by each group of curves. In all four experiments, plotting separately by strategy produced significantly better fits to individual participants' data than did plotting a single power function. We conclude that improvement of solution time is better explained by practice on a strategy than by practice on a task, and that careful assessment of trial-by-trial changes in strategy can improve understanding of the effects of practice on learning.