{"pk":49166,"title":"Reading instruction and individual differences in a computational model of Chinese character reading","subtitle":null,"abstract":"Adopting effective reading instruction is vital for educators and novice readers. In modern Chinese, approximately 80% of the characters are phonetic-semantic compounds. Orthographic knowledge training is one of the efficient training methods among fluency, working memory, phonological, orthographic, and morphological training in literacy development. However, the comparative effectiveness of orthographic knowledge training within phonics-based versus meaning-based instruction has received limited attention. Such comparisons have been shown to be vital for understanding effective reading instruction and individual differences in English reading. By developing a series of triangle models of Chinese character reading, this study aimed to investigate the influence of instructional methods on individual differences in reading. Specifically, the models were trained with sound-focused, meaning-focused, or even (mixed) instructional schemes. We employed semantic reliance (SR), which measures the relative reliance on orthography-to-phonology and orthography-to-semantics pathways, to assess individual reading differences across various training conditions. The simulation results demonstrated that SR scores varied across instructional methods, with the highest scores observed in the meaning-focused condition, followed by the even condition, and then the sound-focused condition. Furthermore, across all instructional conditions, the orthography-to-phonology pathway played a greater role in the reading-aloud task. These simulation results align with findings from studies of English reading. While the models successfully captured a range of typical reading effects in Chinese reading-aloud tasks, the presence of radical consistency effects also depended on various instructional methods.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[],"section":"Papers with Oral Presentation","is_remote":true,"remote_url":"https://escholarship.org/uc/item/5w21p31d","frozenauthors":[{"first_name":"Ching-En","middle_name":"","last_name":"Kuo","name_suffix":"","institution":"National Cheng Kung University","department":""},{"first_name":"Ya-Ning","middle_name":"","last_name":"Chang","name_suffix":"","institution":"Miin Wu School of Computing, National Cheng Kung University","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2025-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/49166/galley/37127/download/"},{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/49166/galley/38672/download/"}]}