Purpose: The purpose of this study was to compare the novel word learning skills between Cantonese-English bilingual children at risk for developmental language disorder (DLD) and their typically developing (TD) peers.
Method: Participants were 24 Cantonese-English bilingual preschool children at risk for DLD and 38 TD children. Each participant was presented with eight novel words in Cantonese (first language [L1]) and eight in English (second language [L2]) over eight weekly sessions. Children's existing lexical knowledge was measured using the moving-average number of different words in language samples in L1 and L2.
Results: Bilingual children at risk for DLD were scored lower than their TD peers for both languages over time. The role of lexical knowledge in children's word learning differed between the TD and DLD groups: Lexical knowledge in L1 was a predictor of L1 word learning in TD children, while lexical knowledge in L2 predicted L2 word learning in children at risk for DLD. In addition, significant cross-linguistic effects were found from L2 to L1 for both groups.
Conclusions: This study underscores the complexity of novel word learning in bilingual children at risk for DLD. Clinically, these findings suggest the value of tracking learning trajectories in bilingual children across both languages.
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http://dx.doi.org/10.1044/2024_AJSLP-23-00489 | DOI Listing |
Behav Res Methods
December 2024
Department of Education Studies, Hong Kong Baptist University, Kowloon Tong, Kowloon, Hong Kong.
The absence of explicit word boundaries is a distinctive characteristic of Chinese script, setting it apart from most alphabetic scripts, leading to word boundary disagreement among readers. Previous studies have examined how this feature may influence reading performance. However, further investigations are required to generate more ecologically valid and generalizable findings.
View Article and Find Full Text PDFBehav Res Methods
December 2024
ETSI de Telecomunicación, Universidad Politécnica de Madrid, Avenida Complutense, 30, 28040, Madrid, Spain.
This study investigates the potential of large language models (LLMs) to estimate the familiarity of words and multi-word expressions (MWEs). We validated LLM estimates for isolated words using existing human familiarity ratings and found strong correlations. LLM familiarity estimates performed even better in predicting lexical decision and naming performance in megastudies than the best available word frequency measures.
View Article and Find Full Text PDFBehav Res Methods
December 2024
Department of Psychology, University of Milano-Bicocca, P.zza dell'Ateneo Nuovo, 1, 20126, Milano, Italy.
Despite being largely spoken and studied by language and cognitive scientists, Italian lacks large resources of language processing data. The Italian Crowdsourcing Project (ICP) is a dataset of word recognition times and accuracy including responses to 130,465 words, which makes it the largest dataset of its kind item-wise. The data were collected in an online word knowledge task in which over 156,000 native speakers of Italian took part.
View Article and Find Full Text PDFJ Am Med Inform Assoc
December 2024
Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA 30322, United States.
Objective: To detect and classify features of stigmatizing and biased language in intensive care electronic health records (EHRs) using natural language processing techniques.
Materials And Methods: We first created a lexicon and regular expression lists from literature-driven stem words for linguistic features of stigmatizing patient labels, doubt markers, and scare quotes within EHRs. The lexicon was further extended using Word2Vec and GPT 3.
Disabil Rehabil Assist Technol
December 2024
New Technologies Platform, Raymond Poincaré Hospital, APHP. Université Paris Saclay, Garches, France.
Purpose: Information and communication technologies are crucial for social and professional integration, but access to technology can be difficult for people with physical impairments. Text entry can be slow and tiring. We developed a free and open-source module called for use with AAC (augmentative/alternative communication) software in French language.
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