"Chinese character recognition among native speakers as well as L2 learners"

"Chinese character recognition among native speakers as well as L2 learners"
Yang Cao

PhD student

Cognitive control communication and perception group,

Institute of Cognitive Neuroscience HSE

Moscow time

Many studies have drawn conclusions that in English word recognition, native adult speakers tend to adopt the holistic processing strategy and a switch from analytic processing strategy to holistic one among children was also detected. Considering the huge differences between logographic Chinese characters and alphabetical English series of letters, it would be interesting to discuss – How does the Chinese native speakers process Chinese characters? Since the majority of Chinese characters is compound characters, composed with two or more single characters (e.g. 妈 is composed with 女 and 马, both of which are independent characters), the processing strategy of Chinese characters may not be the same as that of alphabetical languages. Furthermore, it is also interesting to know how the L2 learners of Chinese process characters. The presentation is therefore aiming to introduce some studies about L1 and L2 character processing, focusing on the paper by Jiang, N., Hou and Jiang, X.(2020) Analytic Versus Holistic Recognition of Chinese Words Among L2 Learners. The paper argued that Chinese native speakers adopt a holistic strategy while L2 learners tend to use the analytic method. However, the study presented only a few behavior findings of a lexical decision-making task, which may look rather superficial and not so reliable. Limitations of the study will also be discussed, whereas, the study compared directly the performance of L2 learners and native Chinese speakers, which is rather rare to be found among the papers on Chinese word recognition. Therefore, even though lots of doubts may be raised about this study, it is still fascinating if it could trigger some discussions or brainstorms and obtain some attention and new fancy ideas to this very topic.


Please, find attached the main relevant paper by Jiang, N., Hou and Jiang, X.(2020)