Identifying Chinese Children with Dyslexia Using Machine Learning with Character Dictation

Autor/inn/en	Man Kit Lee, Stephen; Liu, Hey Wing; Tong, Shelley Xiuli
Titel	Identifying Chinese Children with Dyslexia Using Machine Learning with Character Dictation
Quelle	In: Scientific Studies of Reading, 27 (2023) 1, S.82-100 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Man Kit Lee, Stephen) ORCID (Liu, Hey Wing) ORCID (Tong, Shelley Xiuli)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1088-8438
DOI	10.1080/10888438.2022.2088373
Schlagwörter	Foreign Countries; Dyslexia; Disability Identification; Artificial Intelligence; Algorithms; Computation; Character Recognition; Clinical Diagnosis; Elementary School Students; Scoring; Chinese; Models; Hong Kong + Suchen Sie Ihr Suchwort? Ausland; Dyslexics; Legasthenie; Lese-Rechtschreib-Schwäche; Künstliche Intelligenz; Algorithm; Algorithmus; Bewertung; China; Chinesen; Analogiemodell; Hongkong
Abstract	Purpose: Dyslexia is characterized by its diverse causes and heterogeneous manifestations. Chinese children with dyslexia exhibit orthographic, phonological, and semantic deficits across character and radical levels when writing. However, whether character dictation can be used to distinguish children with dyslexia from their typically developing peers remains unexplored. Method: A dataset of written characters from 1,015 Chinese children with and without dyslexia from Grades 2-6 was used to train multiple machine models with different learning algorithms. Results: The multi-level multidimensional model reached a predictive accuracy of 78.0%, with stroke, grade, lexicality, and character configuration manifesting as the most predictive features. The accuracy of the model improved to 80.0% when only these features were included. Conclusion: These results not only provide evidence for the multidimensional causes of Chinese dyslexia, but also highlight the utility of machine learning in distinguishing children with dyslexia from their peers via Chinese dictation, which elucidates a promising area of future research. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01