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Título: A CALL-based approach to optimizing reading-based vocabulary acquisition /
Autores: Ghadirian, Sina
Fecha: 2004
Publicador: McGill University - MCGILL
Fuente:
Tipo: Electronic Thesis or Dissertation
Tema: Education -- Data processing
Languages, Modern -- Study and teaching -- Foreign speakers
Descripción: This thesis considers the problem of how to bring foreign language students with a limited vocabulary knowledge, consisting mainly of high-frequency words, to the point where they are able to adequately comprehend authentic texts in a target domain or genre. It proposes bridging the vocabulary gap by first determining which word families account for 95% of the target domain's running words, and then having students learn these word families by reading texts in an order that allows for the incremental introduction of target vocabulary. This is made possible by a recently developed computer program that sorts through a collection of texts and (a) finds texts with a suitably high proportion of target words, (b) ensures that over the course of these texts, most or all target words are encountered five or more times, and (c) creates an order for reading these texts, such that each new text contains a reasonably small number of new target words and a maximum number of familiar words. A computer-based study, involving the sorting of 293 news texts, resulted in the finding that all three of these conditions could be met for the majority of texts tested, provided two key changes were first made to the sorting algorithm. A potential problem with the computerized approach is also addressed. The approach takes for granted that a reader must be familiar with 95% of a text's tokens in order to adequately comprehend the text, but a recently published study challenges this assumption by claiming that 98% is a more accurate figure. A close analysis of the study, however, points out a serious methodological flaw which undermines this result.
Idioma: en