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• W2577303772 abstract "A Fresh Look at Vocabulary Spurts Frederic Dandurand (frederic.dandurand@gmail.com) Department of Psychology, Universite de Montreal, 90 ave. Vincent-d'Indy Montreal, QC H2V 2S9 Canada Thomas R. Shultz (thomas.shultz@mcgill.ca) Department of Psychology and School of Computer Science, McGill University, 1205 Penfield Avenue Montreal, QC H3A 1B1 Canada Abstract There is currently rather little agreement about the existence of, and explanation for, a vocabulary spurt in children during the second year. Here we apply a Functional Data Analysis- based technique called Automatic Maxima Detection to the problem of finding vocabulary spurts in a sample of 20 children. Even with considerable smoothing of the data, children were found to exhibit multiple vocabulary spurts of varying intensity and location. These results should provide a clearer target for researchers interested in detecting and explaining these deviations from linear growth. Keywords: vocabulary spurts; functional data analysis; automatic maxima detection. Vocabulary Spurts The psychological literature on vocabulary spurts in children is in an interesting state of turmoil. The spurt is usually taken to mean a sharp increase in vocabulary acquisition in the second year of life. There are at least eight different explanations of the vocabulary spurt with rather little consensus on which is the right explanation, and there is disagreement about whether a spurt even exists in most children. Here, we apply a new statistical methodology to the problem of detecting spurts and find evidence for a surprisingly larger number of vocabulary spurts in most children. Other endogenous factors emphasize leveraging techniques, such that known words facilitate learning of new words. These leveraging methods include mutual exclusivity (Markman, Wasow, & Hanson, 2003), syntactic bootstrapping (Gleitman & Gleitman, 1992), and word segmentation (Plunkett, 1993; Walley, 1993). A third kind of explanation does not emphasize the child, but rather the statistical properties of word distributions in the child’s language environment. Assuming due to the central limit theorem that word-learning difficulty is normally distributed and that words are learned in parallel, computer simulations show that an early vocabulary spurt is mathematically inevitable (McMurray, 2007). The same result was obtained with several other distributions of word difficulty (Mitchell & McMurray, 2008). Most of these explanations have been disputed, including this last one. Under alternate assumptions that all words are equally difficult to learn and their frequencies are distributed under Zipf’s law, simulations show that word acquisition is linear rather than spurt-like (Mayor & Plunkett, 2010). In a Zipf distribution, item frequency is inversely proportional to its rank (Zipf, 1949). This distribution is characteristic of word learning and many other phenomena such as city populations (Itti & Baldi, Methods of Spurt Detection Explanations of the Vocabulary Spurt The assertion that there is a substantial and reliable vocabulary spurt during the second year has been repeated so often that most developmental psychologists readily accept it. This apparent consensus on an interesting phenomenon has led to a variety of explanations. Most of these explanations emphasize factors endogenous to the child, some based on sudden developmental changes and others based on leveraging of previous learning. Among the sudden developmental changes are realizing that things have names (Dore, Franklin, Miller, & Ramer, 1976; Goldfield & Reznick, 1990; McShane, 1979; Reznick & Goldfield, 1992), ability to categorize (Bates, Benigni, Bretherton, Camaioni, & Volterra, 1979; Gopnik & Meltzoff, 1987; Lifter & Bloom, 1989; Mervis & Bertrand, 1994; Nazzi & Bertoncini, 2003; Poulin-Dubois, Graham, & Sippola, 1995), pragmatic skill (Ninio, 1995), and hemispheric specialization (Mills, Coffey-Corina, & Neville, 1993). Four techniques have been used to assess the vocabulary spurt. The simplest is to calculate a ratio of vocabulary size to age and argue whether it is large enough to be a spurt (Schafer & Plunkett, 1998). This method is not particularly convincing as it does not assess change or rate of change. The most common approach is to specify a certain number of words that must be learned in a given time period (Goldfield & Reznick, 1990; Gopnik & Meltzoff, 1987; Lifter & Bloom, 1989; Mervis & Bertrand, 1994; Ninio, 1995; Poulin-Dubois, et al., 1995; Reznick & Goldfield, 1992). A third approach is to plot vocabulary growth over age and visually judge whether a spurt is present (Dromi, All three of these techniques use subjective and arbitrary specifications, and it is not too surprising that values are chosen in a way that guarantees that the expected spurt is found. Moreover, none of these methods distinguish a true spurt from a gradual continuous increase in words (Bloom," @default.
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• W2577303772 title "A Fresh Look at Vocabulary Spurts" @default.
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