Word predictability depends on parafoveal preview validity in Chinese reading

ABSTRACT

Research with alphabetic scripts shows that providing an invalid parafoveal preview eliminates or diminishes effects of contextual predictability on word identification, revealing that such effects depend on the interplay between top-down contextual expectations and bottom-up perceptual information. Whether similar effects are observed in character-based scripts like Chinese is unknown. However, such knowledge would extend our understanding of contextual prediction in different writing systems. Accordingly, we conducted an eye movement experiment using the boundary paradigm to assess contextual predictability effects on the processing of target words with valid and invalid parafoveal previews. Interactions between predictability and preview validity were observed in early reading times but not word-skipping for targets. This suggests an interplay between top-down and bottom-up processes drives contextual processing in Chinese reading, but that word-skipping is not strongly mediated by contextual expectations in this script. We consider these findings in relation to differences between alphabetic and non-alphabetic writing systems.

KEYWORDS:

• Eye movements
• word predictability
• parafoveal preview
• Chinese reading

Acknowledgements

Min Chang, Kevin B. Paterson and Jingxin Wang designed the experiment. Min Chang and Lisha Hao collected the data. Min Chang analyzed the data and prepared the draft manuscript. Victoria A. McGowan and Kayleigh L. Warrington provided additional help with data analysis. Kevin B. Paterson and Sarah C. Gunn revised the manuscript. We thank Kuo Zhang, Lin Li, Xue Zhang, Sainan Zhao for additional help.

Data availability statement

Data files and related resources are available from the University of Leicester online Figshare repository: https://doi.org/10.25392/leicester.data.9795527.v1.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The research was supported by a grant from National Science Foundation of China to Jingxin Wang (81771823) and a 1000 Talents Visiting Professorship to Kevin B. Paterson.