Purpose: This study examined dimensions of written composition by using multiple evaluative approaches such as an adapted 6 + 1 trait scoring, syntactic complexity measures, and productivity measures. It further examined unique relations of oral language and literacy skills to the identified dimensions of written composition.
Method: A large sample of 1st-grade students (N = 527) was assessed on their language, reading, spelling, letter writing automaticity, and writing in the spring. Data were analyzed using a latent variable approach, including confirmatory factor analysis and structural equation modeling.
Results: The seven traits in the 6 + 1 trait system were best described as two constructs: substantive quality and spelling and writing conventions. When the other evaluation procedures such as productivity and syntactic complexity indicators were included, four dimensions emerged: substantive quality, productivity, syntactic complexity, and spelling and writing conventions. Language and literacy predictors were differentially related to each dimension in written composition.
Conclusion: These four dimensions may be a useful guideline for evaluating developing beginning writers' compositions.
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http://dx.doi.org/10.1044/1092-4388(2013/12-0152) | DOI Listing |
Neuroimage
December 2024
School of Psychology, Shenzhen University, Shenzhen, China. Electronic address:
Understanding how children acquire syntactic structures from a limited set of grammatical rules and use them creatively to convey meaning has been a longstanding interest for scientific communities. Previous studies on syntactic development have revealed its close correlation with the development of vocabulary and working memory. Our study sought to elucidate how the relations between syntactic processing, word processing, and working memory were instantiated in the brain, and how earlier neural patterns might predict language abilities one year later.
View Article and Find Full Text PDFPLoS One
December 2024
Department of Developmental of Applied Psychology and Human Development, Ontario Institute for Studies in Education, University of Toronto, Toronto, Canadá.
This longitudinal study explored the contribution of transcription skills, oral language abilities, and executive functions in kindergarten to written production in grade 1 among Spanish-speaking children (N = 191) through structural equation modeling (SEM). Three dimentions of written production were assessed, including productivity, quality, and syntactic complexity. Accordingly, three SEM models were tested to explore these relationships, and the estimated models for each endogenous variable demonstrated good fit.
View Article and Find Full Text PDFTop Cogn Sci
December 2024
Department of Linguistics, University of Massachusetts Amherst.
As they process complex linguistic input, language comprehenders must maintain a mapping between lexical items (e.g., morphemes) and their syntactic position in the sentence.
View Article and Find Full Text PDFCereb Cortex
December 2024
Institute for the Interdisciplinary Study of Language Evolution, University of Zurich, Affolternstrasse 56, 8050 Zürich, Switzerland.
Models of phonology posit a hierarchy of prosodic units that is relatively independent from syntactic structure, requiring its own parsing. It remains unexplored how this prosodic hierarchy is represented in the brain. We investigated this foundational question by means of an electroencephalography (EEG) study.
View Article and Find Full Text PDFPeerJ Comput Sci
February 2024
School of Information Engineering, Fuyang Normal University, Fuyang, Anhui, China.
With the continuous advancement of deep learning technologies, neural machine translation (NMT) has emerged as a powerful tool for enhancing communication efficiency among the members of cross-language collaborative teams. Among the various available approaches, leveraging syntactic dependency relations to achieve enhanced translation performance has become a pivotal research direction. However, current studies often lack in-depth considerations of non-Euclidean spaces when exploring interword correlations and fail to effectively address the model complexity arising from dependency relation encoding.
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