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Enhancement of automatization through vocabulary learning using CALL: Can prompt language processing lead to better comprehension in L2 reading?

Published online by Cambridge University Press:  13 February 2013

Takeshi Sato ,
Mitsuyasu Matsunuma  and
Akio Suzuki
Takeshi Sato
Affiliation:
Tokyo University of Agriculture and Technology, Japan (email: tsato@cc.tuat.ac.jp)
Mitsuyasu Matsunuma
Affiliation:
Shizuoka University, Japan (email: ommatun@ipc.shizuoka.ac.jp)
Akio Suzuki
Affiliation:
Toyo University, Japan (email: suzukiakio@toyo.jp)
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Abstract

Our study aims to optimize a multimedia application for vocabulary learning for English as a Foreign Language (EFL). Our study is based on the concept that difficulty in reading a text in a second language is due to the need for more working memory for word decoding skills, although the working memory must also be used for text comprehension skills. This implies that the automatization of word decoding to free the working memory is indispensable. Therefore, developing a multimedia application for vocabulary learning with a time-control function, our study hypothesizes that vocabulary learning with this function brings about the automatization of word decoding or faster recall of the meanings, and, as a result of freeing more working memory, better comprehension of text. According to our research, multimedia application users not only retained more words and recalled their meanings more quickly but also obtained higher scores on reading comprehension tests that contained the words learned through the application. From this result, we conclude that multimedia vocabulary learning with a time-control function can automatize word decoding skills and therefore free more working memory, thereby leading to better comprehension of the text.

Keywords

L2 readingworking memoryautomatizationvocabulary learningtime-control functiontext comprehension.
Type
Research Article
Information
ReCALL , Volume 25 , Issue 1 , January 2013 , pp. 143 - 158
Copyright
Copyright © European Association for Computer Assisted Language Learning 2013

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