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Predictive Ability in the Processing of Korean Classifier Constructions

이온순
한국언어과학회 (The Korean Association Of Language Sciences)|2022.05|언어과학 (Journal of Language Sciences)|제29권 제2호|pp. 171-195|DOI http://dx.doi.org/10.14384/kals.2022.29.2.171

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참고문헌

키워드

Korean한국어분류사예측sentence processing문장이해predictionclassifierslanguage comprehensionartificial grammar learning task실시간 문장처리인공문법학습과제
주제분류언어학

초록

The role of prediction in language comprehension has been tested in few languages, and how much prediction has been used across different language groups remains unclear. This study therefore expands the investigation of the role of prediction by examining the relation between performance on an artificial grammar learning task with an adjacent dependency rule and performance on a Korean self-paced reading task including a predictive relation between classifiers and their associated nouns. Forty-two Korean native speakers took part in the experiment. Results show a significant relation between scores on the two tasks. These results suggest that better ability to make predictions, as measured by the artificial grammar learning task, facilitates comprehension of the predictive dependency between preposed Korean classifiers and the following associated nouns. Moreover, different degrees of predictive ability may help explain individual differences in language processing.

Abstract

The role of prediction in language comprehension has been tested in few languages, and how much prediction has been used across different language groups remains unclear. This study therefore expands the investigation of the role of prediction by examining the relation between performance on an artificial grammar learning task with an adjacent dependency rule and performance on a Korean self-paced reading task including a predictive relation between classifiers and their associated nouns. Forty-two Korean native speakers took part in the experiment. Results show a significant relation between scores on the two tasks. These results suggest that better ability to make predictions, as measured by the artificial grammar learning task, facilitates comprehension of the predictive dependency between preposed Korean classifiers and the following associated nouns. Moreover, different degrees of predictive ability may help explain individual differences in language processing.

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