Exploring influential factors of shape classifier comprehension and production in Mandarin-speaking children

Abstract

Mandarin classifiers are a complex system, but little is known about how Mandarin-speaking children manage to learn the system. Based on the extant literature, we explored potential factors influencing the comprehension and production of Mandarin shape classifiers, including classifier-based semantic categorization and errors pertaining to the semantic strategies, input frequency of classifier-noun combinations, and vocabulary knowledge. In total, 138 typically developing monolingual Mandarin-speaking children between ages 4;1 and 6;5 completed an object categorization task, shape classifier comprehension and production tasks, and a vocabulary test. The results showed that classifier-based categorization did not significantly relate to classifier knowledge, but children’s comprehension errors were mostly selecting an object that is perceptually similar to the target object. Estimated input frequency of classifier-noun combinations was significantly related to classifier comprehension, and there was differential accuracy for different classifier-noun combinations, which may indicate item-by-item learning of individual classifier-noun pairings. Mandarin-speaking children may take a combined approach by sorting semantic features for different classifiers and learning individual classifier-noun combinations. The interplay of the two approaches can be very complex and should be further investigated in future studies. Vocabulary knowledge was significantly related to classifier comprehension and production, indicating common traits between classifier learning and noun learning.