A Corpus-Based Multifactorial Study of Help/help to Alternation in Learners’ Language: From the Perspective of Probabilistic Grammar

Menglan Wang, Guiying Jiang and Yan Cheng

SAGE Open, 2024, vol. 14, issue 4, 21582440241293535

Abstract: This corpus-based multifactorial study delves deeper into the well-known alternation between bare and full infinitive complements, specifically regarding the help concordances. It extends the line of research to learners’ language productions with a focus on comparing and contrasting the probabilistic grammatical knowledge reflected in the help / help to choices, which are constrained by a complex network of factors. Regression modeling indicates that constraints such as the horror aequi and certain morphological forms of the verb help are comparatively stable among groups of Chinese English language learners and native English speakers. Therefore, the principle of cognitive complexity and the avoidance strategy fueling infinitive variations are further tested. While the object typology differs in effect strength, it also prompts consideration of cultural influences on the part of Chinese English learners. In addition, two different patterns of interaction effects are explored in each dataset, which implies that learners’ language choice is usage-based, determined by an unconscious assessment of multiple clues that are learned from language input and shaped by language experiences.

Keywords: help/help to alternation; probabilistic grammar; learner corpus; multifactorial study; usage-based (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:sae:sagope:v:14:y:2024:i:4:p:21582440241293535

DOI: 10.1177/21582440241293535

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