Korean Journal of Cognitive Science (인지과학)

The Korean Society for Cognitive Science (한국인지과학회)
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Implicit Learning with Artificial Grammar : Simulations using EPAM IV

인공 문법을 사용한 암묵 학습: EPAM IV를 사용한 모사

  • Published : 2003.03.01
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Abstract

In implicit learning tasks, human participants learn grammatical letter strings better than random letter strings. After learning grammatical letter strings, participants were able to judge the grammaticality of new letter strings that they have never seen before. EPAM (Elementary Perceiver and Memorizer) IV, a rote learner without any rule abstraction mechanism, was used to simulate these results. The results showed that EPAM IV with a within-item chunking function was able to learn grammatical letter strings better than random letter strings and discriminate grammatical letter strings from non-grammatical letter strings. The success of EPAM IV in simulating human performance strongly indicated that recognition memory based on chunking plays a critical role in implicit learning.

본 연구에서는 EPAM(Elementary Perceiver and Memorizer) Ⅳ를 사용하여 인공 문법이 사용된 암묵적 학습에서의 인간 수행을 모사하였다. 암묵 학습(implicit learning) 과제에서 참가자들은 인공 문법(rtificial grammar)을 사용해 만들어진 '문법적' 문자열과 무선적으로 만들어진 '비문법적' 문자열을 학습하였는데, 이 때 비문법적 문자열보다 문법적 문자열의 학습이 더 우수하였다. 또한 참가자들은 이전에 본 적이 없었던 새로운 문자열에 대해서도 그 문법성을 판단할 수 있었다. 단순 기억 시스템인 EPAM Ⅳ에 항목 내 군집화(within-item chunking) 기능을 추가하여 암묵 학습 과제에서의 인간수행을 모사한 결과, EPAM Ⅳ 또한 무선적인 문자열보다 문법적인 문자열을 보다 잘 학습하였고, 비문법적 문자열과 문법적 문자열을 구별할 수 있었다. 이러한 결과는 인공 문법을 사용한 암묵 학습 과제에서의 수행이 규칙 추상화보다는 군집화(chunking)에 근거한 재인 기억을 바탕으로 이루어짐을 시사한다.

Keywords

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