The interactive effects of task demands and L2 proficiency on syntactic parsing: evidence from the grammatical aspectual processing by L2 Chinese learners
Abstract
The Shallow Structure Hypothesis and the good-enough processing account propose that L2 learners tend to rely on shallow or “good-enough” interpretations during online sentence comprehension. However, the interaction between task demands and L2 proficiency in modulating the depth of syntactic processing remains unclear. The present study explored the processing of Chinese grammatical aspect marker among L2 learners in Mandarin Chinese, employing two self-paced reading tasks: a grammaticality judgment task and a sentence-picture matching task. 40 Indo-European language-speaking L2 Chinese learners and 44 native Chinese speakers participated in the study. Experimental materials used an aspectual agreement paradigm involving the aspect marker “ guo (过)” and temporal adverbials. Results revealed that the native Chinese speakers took significantly longer to read the spillover region in incorrect sentences than correct ones, regardless of task demands. The relatively higher-proficiency L2 learners (within TOCFL Band A) exhibited online sensitivity to aspectual agreement violations only in the grammaticality judgment task, not in the sentence-picture matching task. Conversely, the relatively lower-proficiency L2 learners failed to exhibit such sensitivity in either task, highlighting the interaction between task demands and L2 proficiency in shaping the depth of syntactic parsing. These findings not only enhance the theoretical explanatory power of the Shallow Structure Hypothesis and the good-enough processing account, but also indicate that integrating explicit form-focused tasks in L2 instruction helps develop learners’ syntactic parsing mechanisms.
Fields of Study & Subjects
Neurobiology of Language and Bilingualism
Second Language Acquisition and Learning
Reading and Literacy Development
Publication details
- Journal / source
- Lingua
- Publisher
- Elsevier BV
- Volume
- 340
- Pages
- 104199–104199
- Publication date
- 19 May 2026
- Language
- EN