Use Eye Movement Features to Explore the Impact of Language Features on Text Difficulty (85560)

Session Information:

Monday, 25 November 2024 15:50
Session: Poster Session 1
Room: Orion Hall (5F)
Presentation Type: Poster Presentation

All presentation times are UTC + 9 (Asia/Tokyo)

The concept of lifelong learning posits that learning should persist until the end of life. Indeed, reading can not only enrich the lives of the elderly, but also assist them in adapting to the aging process. Nevertheless, the process of ageing can result in a decline in cognitive abilities and an impairment of memory. It is therefore of significant importance to provide appropriate text materials for the elderly. In this context, numerous scholars have investigated the relationship between eye movement indicators and text difficulty. Nevertheless, previous research has not fully mapped eye movement indicators to linguistic features, which is an impediment to article writers in judging the difficulty of an article and writing it. Accordingly, this study employs an eye tracker to observe the reading behaviour of elders when reading texts of varying degrees of difficulty, and extracts eye movement indicators to examine the difficulties encountered by older individuals with differing reading abilities throughout the reading process. Finally, Chinese Readability Index Explorer employs computational linguistic analysis to examine the linguistic features of these sentences and words, and to elucidate the reasons why these linguistic features present reading challenges for elders. This study proposes a specific correlation between eye movement indicators and text difficulty and provides new perspectives and methodological support for future eye movement research. The findings of this study can be applied to the cognitive health management of the elderly, with the objective of improving the quality of life of this demographic and promoting lifelong learning.

Authors:
Yi-Ju Chan, National Taiwan University of Science and Technology, Taiwan
Hou-Chiang Tseng, National Taiwan University of Science and Technology and National Taiwan University of Science and Technology Empower Vocational Education Research Center, Taiwan
Yao-Ting Sung, National Taiwan Normal University, Taiwan


About the Presenter(s)
Yi Ju, Chan is currently a university postgraduate student in the department of Graduate Institude of Digital Learning annd Education, National Taiwan University of Science and Technology, Taiwan.

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Posted by Clive Staples Lewis

Last updated: 2023-02-23 23:45:00