Structural relations of language and cognitive skills, and topic knowledge to written composition: A test of the direct and indirect effects model of writing

Kim, Young‐Suk Grace

doi:10.1111/bjep.12330

Cited by 45 publications

(67 citation statements)

References 41 publications

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“…). Perspective taking as measured by theory of mind was related to writing quality for students in grade 4 (Kim, 2020a).…”

mentioning

confidence: 99%

Expanding the Direct and Indirect Effects Model of Writing (DIEW): Reading–writing relations, and dynamic relations as a function of measurement/dimensions of written composition.

Kim¹,

Graham²

2022

Journal of Educational Psychology

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Within the context of the Direct and Indirect Effects Model of Writing (Kim & Park, 2019), we examined a dynamic relations hypothesis, which contends that the relations of component skills, including reading comprehension, to written composition vary as a function of dimensions of written composition. Specifically, we investigated (a) whether higher-order cognitive skills (i.e., inference, perspective taking, and monitoring) are differentially related to three dimensions of written composition-writing quality, writing productivity, and correctness in writing; (b) whether reading comprehension is differentially related to the three dimensions of written composition after accounting for oral language, cognition, and transcription skills, and whether reading comprehension mediates the relations of discourse oral language and lexical literacy to the three dimensions of written composition; and (c) whether total effects of oral language, cognition, transcription, and reading comprehension vary for the three dimensions of written composition. Structural equation model results from 350 English-speaking second graders showed that higher-order cognitive skills were differentially related to the three dimensions of written composition. Reading comprehension was related only to writing quality, but not to writing productivity or correctness in writing, and reading comprehension differentially mediated the relations of discourse oral language and lexical literacy to writing quality. Total effects of language, cognition, transcription, and reading comprehension varied largely for the three dimensions of written composition. These results support the dynamic relation hypothesis, role of reading in writing, and the importance of accounting for dimensions of written composition in a theoretical model of writing. Educational Impact and Implications StatementWritten composition is a multidimensional construct, and various dimensions of written composition draw on different language and cognitive skills. Higher-order cognitive skills such as inference, perspective taking, and monitoring as well as reading comprehension are important to the quality dimension of written composition. In contrast, lexical literacy and handwriting fluency were important contributors of writing productivity (or composition length) and correctness in writing, whereas vocabulary and grammatical knowledge made additional contributions to correctness in writing. These findings imply that dimensions of written composition should be carefully considered and calibrated in assessment and instruction and that systematic integration of reading and writing supports writing development.

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“…). Perspective taking as measured by theory of mind was related to writing quality for students in grade 4 (Kim, 2020a).…”

mentioning

confidence: 99%

Expanding the Direct and Indirect Effects Model of Writing (DIEW): Reading–writing relations, and dynamic relations as a function of measurement/dimensions of written composition.

Kim¹,

Graham²

2022

Journal of Educational Psychology

Self Cite

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“…In contrast to the not-so-simple view of writing, the DIEW model of writing (Kim & Schatschneider, 2017) considers oral language skills to be a direct influence on written composition from the beginning of formal writing instruction, proposing that not only transcription skills but also oral discourse-level skills (a component of text generation) have a strong and direct effect on written production beginning in Grade 1. Similarly to the not-so-simple view of writing, the DIEW model of writing has been validated by empirical evidence of early effects of oral discourse-level language skills on writing (Kim, 2019;Kim & Schatschneider, 2017), which has been observed in older writers as well (fourth graders; Kim, 2019).…”

Section: The Role Of Oral Language and Text Generation Skills In Writmentioning

confidence: 96%

Oral sentence generation training to improve fifth and 10th graders’ writing

Arfé

Festa²,

Ronconi

et al. 2020

Read Writ

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Text generation—the mental translation of ideas into language at word, sentence, and discourse levels—involves oral language abilities. However, oral language skills are rarely a target of writing interventions. We ran an intervention to improve fifth and 10th graders’ written production through the development of oral sentence generation (grammatical and syntactic) skills. One hundred and fifteen students—68 fifth graders (four classrooms) and 47 tenth graders (four classrooms)—participated in a stepped-wedge cluster-randomized controlled trial. Two fifth-grade classrooms (n = 35) and two 10th-grade classrooms (n = 20) received nine 90-min sessions (3 weeks, three sessions a week) of oral language intervention immediately after the pretest (experimental groups); the two other fifth- (n = 33) and 10th-grade classrooms (n = 27) received business-as-usual writing instruction and received a delayed oral language intervention after the posttest (waiting list group). The intervention consisted of team-based games to improve oral sentence generation and sentence reformulation skills. We assessed written sentence generation, written sentence reformulation, written text quality (macrostructure and language), and text writing fluency before (pretest) and after (posttest) the intervention and 5 weeks after the intervention (follow-up). The results showed that training on oral sentence generation skills can lead to significant gains in both sentence generation and sentence reformulation skills and text macrostructural quality. Improvement at the sentence level was, however, significant only for the younger writers (fifth graders).

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“…Combined with the overlay mechanism, this method can improve the coverage of the translation results to the source language and the fluency of the sentence, but the target context does not fully utilize the generated translation information. Literature [24] has modeled the structural relations of all words, so that the neural machine translation model can make better use of the context features of source language and target language. In addition, literature [25] studies the features of omitted words in source languages, finds that words with higher translation entropy are more likely to be omitted, and proposes to use coarse-tofine framework to improve the translation quality of sentences and words and reduce the number of missed translation of words with high entropy.…”

Section: Related Workmentioning

confidence: 99%

Generative Adversarial Network-Based Short Sequence Machine Translation from Chinese to English

Yan

Sun³

2022

Scientific Programming

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With the acceleration of economic globalization, the economic contact, information exchange, and financial integration between countries become more and more frequent. In this context, the communication between different languages is also closer, so accurate translation between languages is of great significance. However, existing methods give little thought to short sequence machine translation from Chinese to English. This paper designs a generative adversarial network to solve the above problem. First, a conditional sequence generating adversarial net is constructed, which includes two adversarial submodels: a generator and a discriminator. The generator is designed to generate sentences that are difficult to distinguish from human-translated sentences, and the discriminator is designed to distinguish the sentences generated by the generator from human-translated sentences. In addition, static sentence-level BLEU values will be used as reinforcement targets for the generator. During training, both dynamic discriminators and static BLEU targets are used to evaluate the generated sentences, and the evaluation results are fed back to the generator to guide the generator's learning. Finally, experimental results on English-Chinese translation dataset show that the translation effect is improved by more than 8% compared with the traditional neural machine translation model based on recurrent neural network (RNN) after the introduction of generative adversative network.

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Structural relations of language and cognitive skills, and topic knowledge to written composition: A test of the direct and indirect effects model of writing

Cited by 45 publications

References 41 publications

Expanding the Direct and Indirect Effects Model of Writing (DIEW): Reading–writing relations, and dynamic relations as a function of measurement/dimensions of written composition.

Expanding the Direct and Indirect Effects Model of Writing (DIEW): Reading–writing relations, and dynamic relations as a function of measurement/dimensions of written composition.

Oral sentence generation training to improve fifth and 10th graders’ writing

Generative Adversarial Network-Based Short Sequence Machine Translation from Chinese to English

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