The power law repealed: The case for an exponential law of practice

By Andrew Heathcote, Scott D. Brown, D. Mewhort. Psychonomic Bulletin & Review, 2000

726 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Developmental and Educational Psychology, Experimental and Cognitive Psychology

View Paper: https://www.semanticscholar.org/paper/3b9b728a846035240921c10ce8cf67f8a8946108

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In Cognitive Neuroscience

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Citations in the corpus

Word learning emerges from the interaction of online referent selection and slow associative learning (2012, background): “This pattern is commonly seen in power law or exponential decay function in the literature on general learning principles and has appeared in a variety of motor and cognitive learning tasks (Anderson, 1982; Heathcote et al., 2000; Logan, 1992; Newell & Rosenbloom, 1981; Wifall et al., 2012), suggest”
Practice and Forgetting Effects on Vocabulary Memory: An Activation-Based Model of the Spacing Effect (2005, background): “Although some have argued that a power function characterizes practice data (e.g., Logan, 1992; Newell & Rosenbloom, 1981) and forgetting data (Wixted & Ebbesen, 1997), others have questioned whether a power function is satisfactory and have suggested that exponential functions are more suitable for”
Default Bayes factors for ANOVA designs (2012, background): “Prior to the work of Heathcote et al. (2000), it was generally accepted that learning followed a power law with practice (e.g., Newell & Rosenbloom, 1981), and this power law speed up was explained by a straightforward race-among-exemplars process (Logan, 1988, 1992).”
Reading development in an orthographically regular language: effects of length, frequency, lexicality and global processing ability (2009, background): “distribution better. It must be pointed out that studies on learning curves characteristically examine individual participants longitudinally ( Heathcote, Brown, & Mewhort, 2000 ).”
Consequences of the Now-or-Never bottleneck for signed versus spoken languages (2015, background): “As with other skills (e.g., Heathcote et al. 2000; Newell & Rosenbloom 1981), there will be practice effects, where the repeated use of a given chunk results in faster processing and reduced demands on cognitive resources, and with sufficient use, leading to a high degree of automaticity (e.g.,…”
When Do You Need Billions of Words of Pretraining Data? (2020, methodology): “We use a four-parameter exponential learning curve used to capture diminishing improvement in performance as a function of the number of practice trials (Heathcote et al., 2000; Leibowitz et al., 2010):”
An introduction to Bayesian hierarchical models with an application in the theory of signal detection (2005, background): “Aggregate learning curves may be more graded than those of individuals, leading researchers to misdiagnose underlying mechanisms (Haider & Frensch, 2002; Heathcote, Brown, & Mewhort, 2000 ).”
An instance theory of attention and memory. (2002, background): “Heathcote, Brown, and Mewhort (2000) argued that it is an artifact of averaging item-level exponentialfunction learning curves (but see Myung, Kim, & Pitt, 2000).”
Use of Response Time for Measuring Cognitive Ability (2016, neutral): “An example is individual acquisition and decay rates based on the ubiquitous power law of practice [73–75].”
A cognitive latent variable model for the simultaneous analysis of behavioral and personality data. (2014, background): “Jöreskog (1969) and Loken (2005) discuss and review further sufficient requirements.”
Task-Based Core-Periphery Organization of Human Brain Dynamics (2012, background): “Several functional forms have been suggested for the fit of MT [78,79], and the exponential (plus constant) is viewed as the most statistically robust choice [79].”