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Human learning: Power laws or multiple characteristic time scales?

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Doi: 10.20982/tqmp.02.2.p066

Newell, Karl M. , Mayer-Kress, Gottfried , Liu, Yeou-The
Keywords: Power law , Superposition of exponential curves
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The central proposal of A. Newell and Rosenbloom (1981) was that the power law is the ubiquitous law of learning. This proposition is discussed in the context of the key factors that led to the acceptance of the power law as the function of learning. We then outline the principles of an epigenetic landscape framework for considering the role of the characteristic time scales of learning and an approach to system identification of the processes of performance dynamics. In this view, the change of performance over time is the product of a superposition of characteristic exponential time scales that reflect the influence of different processes. This theoretical approach can reproduce the traditional power law of practice – within the experimental resolution of performance data sets - but we hypothesize that this function may prove to be a special and perhaps idealized case of learning.

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