This study has the potential to uncover the source of the difficulties in classifier learning, which could be a useful reference for the selection of teaching methods and textbook editing.Īnimacy is an important semantic assignment principle in both gender and numeral classifier systems. More importantly, the sequential mastery of different classifier types implies a universal sequence of acquiring classifiers, which presents a robust account for the weakness of L1 influence. Additionally, individual differences seem not to affect classifier acquisition as a whole (at least in this study). On top of the L1 effects, different types of tasks interact with the L1, which may shed new light on classifier proficiency from the perspective of language testing.
This study takes the position that albeit without statistical significance, similarities between L1 and L2 have the potential to promote L2 acquisition, whereas dissimilarities could hinder it. Results suggest that: 1) Although the statistical analysis suggests that L1 is not a significant predictor of test performance, the Japanese group numerically scored higher than the Arabic and the English groups on the test 2) the task types are a significant predictor of test performance, with a significant interaction found to occur between L1 and tasks 3) individual differences are not a significant predictor of test performance 4) there tends to be a sequential mastery of different types of classifiers. Statistical analysis was carried out by means of R Studio. A post-test questionnaire was conducted to gather demographic information of the participants and to explore individual differences on classifier acquisition such as learner beliefs and learning strategies. All were asked to take a Chinese language test that included three written tasks based on a picture description: composition, gap-fillings and multiple-choice questions. Participants were divided into two groups, non-classifier language speakers (Egyptian and Australian) and classifier language speakers (Japanese). Participants were 17 Arabic-, 15 English- and 18 Japanese-L1 students from Egypt, Australia and Japan respectively, who recently completed intermediate Chinese language courses at their home universities. This research explores crosslinguistic influence (CLI) on adult L2 learners’ acquisition of Chinese classifiers.
Moreover, our logistic model predicts different levels of accuracy for classifier use by type, which potentially suggests a developmental path of acquiring classifiers licensed by the most prominent noun feature they are associated with, with shape being the earliest, followed by animate, inanimate, and concept. Meanwhile, there was an interaction between L1 and task, suggesting that L1 influence may be conditioned by task type. The composition task was shown to be conducive to the use of test-taking strategies, and it revealed a higher classifier accuracy than the more constrained multiple-choice task. Although Japanese L1 participants performed numerically better than their Arabic and English counterparts, statistical analysis suggests that L1 was not a significant predictor of test performance. Participants were 50 Chinese L2 learners from Arabic, English, and Japanese L1 backgrounds.
#HAMMERSPOON CONFIG SEAL SPOON FREE#
We developed a picture-prompted test, including composition, free cloze, and multiple-choice cloze questions to elicit the use of classifiers. This study explores three potential factors that influence Chinese L2 learners’ classifier use in a classroom setting: L1 background, task, and classifier type. This study suggests that the differences identified in Experiments 1-4 have important implications for the likelihood of finding cognitive consequences. Finally, we present a fifth study investigating the impact of this variation on the cognitive consequences of classifier knowledge.
The data provide evidence that at least three forms of mental representation need to be distinguished. We then present four studies investigating potential variation in the mental representation of the classifier categories.
We first provide a taxonomy of 126 common classifiers and a large sample of the objects classified by each as a tool for this and future research. The current work evaluates both the mental representation of classifiers and potential cognitive consequences for speakers of Mandarin Chinese. Classifier languages are spoken by a large portion of the world's population, but psychologists have only recently begun to investigate the psychological reality of classifier categories and their potential for influencing non-linguistic thought.
0 kommentar(er)
