The Effect of Role Predictability and Word Predictability on Sentence Comprehension
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초록
The purpose of this study was to investigate whether the degree of difficultyin the integration of a word into a sentence could be determined by not onlyhow likely the word would be for a given context but also how likely thethematic role associated with the word would be to occur. For our aim, we useddative sentences in Korean in which three arguments (i.e., agent, recipient, andpatient/theme) appeared prior to a sentence-final verb. We manipulated 1) thedegree of role predictability corresponding to the third argument by scramblingthe internal arguments that occurred after an agent and 2) the predictabilityof words corresponding to the third arguments that was either highly likelyor unlikely for a given context. A self-paced moving window reading with asecondary judgment task was conducted. A linear mixed-effect regressionson the reading times of the words corresponding to the third arguments wasrun while controlling for the effects of lexical frequencies and lengths onthe processing of target words. The results from the model revealed that thewords were read faster when they were highly likely for given contexts thanwhen they were unlikely, and importantly, that the words were read fasterwhen the roles associated with the words were strongly expected than whenthey were weakly expected. Our results showed that both role predictabilityand word predictability had independent effects on the processing of a wordin a sentence. We claim that a processing model should be loaded with at leasttwo components that take into account role predictability as well as word predictability.
Abstract
The purpose of this study was to investigate whether the degree of difficultyin the integration of a word into a sentence could be determined by not onlyhow likely the word would be for a given context but also how likely thethematic role associated with the word would be to occur. For our aim, we useddative sentences in Korean in which three arguments (i.e., agent, recipient, andpatient/theme) appeared prior to a sentence-final verb. We manipulated 1) thedegree of role predictability corresponding to the third argument by scramblingthe internal arguments that occurred after an agent and 2) the predictabilityof words corresponding to the third arguments that was either highly likelyor unlikely for a given context. A self-paced moving window reading with asecondary judgment task was conducted. A linear mixed-effect regressionson the reading times of the words corresponding to the third arguments wasrun while controlling for the effects of lexical frequencies and lengths onthe processing of target words. The results from the model revealed that thewords were read faster when they were highly likely for given contexts thanwhen they were unlikely, and importantly, that the words were read fasterwhen the roles associated with the words were strongly expected than whenthey were weakly expected. Our results showed that both role predictabilityand word predictability had independent effects on the processing of a wordin a sentence. We claim that a processing model should be loaded with at leasttwo components that take into account role predictability as well as word predictability.
참고문헌 (44)
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