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Reading between the lines: linguistic properties as cues for word segmentation in Chinese sentence reading

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posted on 2024-01-25, 01:25 authored by Xin Yi Yap

A major feature that distinguishes Chinese writing from the alphabetic system is that words are not separated by spaces in Chinese sentences. It thus remains a puzzle how Chinese readers segment and identify words in sentences in order to read efficiently. The present study investigated whether and how Chinese readers use the morphological structure of words as a cue to guide their word segmentation and identification process. Two-character target words varying in morphological complexity (monomorphemic versus compound words) were embedded in sentences, and colour (Experiment 1) and word space (Experiment 2) manipulations were introduced to create a congruent or incongruent segmentation of the target words. Experiment 1 showed a slowdown to monomorphemic words when segmentation was incongruent, relative to the non-coloured control condition, providing some support for utilising morphological cues for word segmentation; however, the results of Experiment 2 were less clear.

History

Table of Contents

Reading between the lines: linguistic properties as cues for word segmentation in Chinese sentence reading -- Experiment 1: alternate coloured text -- Experiment 2: spaced text -- Discussion -- References -- Appendix A: list of sentence frames and target words -- Appendix B: participant information and consent form (English version) -- Appendix C: participant information and consent form (Chinese version) -- Appendix D: ethics approval from the Macquarie University Human Sciences Subcommittee

Awarding Institution

Macquarie University

Degree Type

Thesis MRes

Degree

Master of Research

Department, Centre or School

School of Psychological Sciences

Year of Award

2023

Principal Supervisor

Lili Yu

Additional Supervisor 1

Sachiko Kinoshita

Rights

Copyright: The Author Copyright disclaimer: https://www.mq.edu.au/copyright-disclaimer

Language

English

Extent

67 pages

Former Identifiers

AMIS ID: 283837