2018
DOI: 10.1017/s0142716418000450
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Japanese EFL learners’ sentence processing of conceptual plurality: An analysis focusing on reciprocal verbs

Abstract: This study aimed to investigate how Japanese learners of English as a foreign language, whose first language does not have obligatory morphological number marking, process conceptual plurality. The targeted structure was reciprocal verbs, which require conceptual plurality to interpret their meanings correctly. The results of a sentence completion task confirmed that participants could use reciprocal verbs reciprocally in English. In a self-paced reading experiment, participants read sentences with reciprocal … Show more

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Cited by 3 publications
(2 citation statements)
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“…However, Shantz investigated the effect of grammaticality on four-word sequences, not single words like the present study. Furthermore, when length has been shown to be a significant RT predictor, such as in Tamura et al (2019), the effect has not been as strong as in the present study. Although syllable length was controlled for in the present study, our results highlight the importance of controlling for letter length in L2 behavioral research, either at the item design stage or as a fixed effect in regression models.…”
Section: Discussioncontrasting
confidence: 94%
“…However, Shantz investigated the effect of grammaticality on four-word sequences, not single words like the present study. Furthermore, when length has been shown to be a significant RT predictor, such as in Tamura et al (2019), the effect has not been as strong as in the present study. Although syllable length was controlled for in the present study, our results highlight the importance of controlling for letter length in L2 behavioral research, either at the item design stage or as a fixed effect in regression models.…”
Section: Discussioncontrasting
confidence: 94%
“…The current study illustrates the benefits of log transformations, but adds the caveat that such transformations potentially affect the structure of the data and the corresponding effect sizes. If RT distributions are inherently nonnormally distributed and require transformations to meet linearity assumptions, perhaps analyses that do not assume linear distributions, such as GLMEs, should be considered instead (see Baayen, 2008; Tamura, Fukuta, Nishimura, Harada, Hara, & Kato, 2019).…”
Section: Future Researchmentioning
confidence: 99%