Cohesive Devices in English Writing Textbooks and Korean Learners’ English Writings

Cho, Hee Youn; Shin, Jeong-Ah

doi:10.15858/engtea.69.1.201403.41

Cited by 5 publications

(1 citation statement)

References 19 publications

(19 reference statements)

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“…Although ESL contexts contain a rich environment for the acquisition of formulaic language, EFL contexts often contain input that is scant or highly different from that found in native English contexts. Furthermore, the commercial book market produces resources of low quality that do not properly prepare EFL learners to write effectively (Chen, 2007;Cho & Shin, 2014).…”

Section: Formulaic Language In An Efl Contextmentioning

confidence: 99%

Improving EFL Writing Through Study of Semantic Concepts in Formulaic Language

Schenck¹,

Choi²

2014

ELT

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Within Asian EFL contexts such as South Korea, large class sizes, poor sources of input and an overreliance on the Grammar-Translation Method may negatively impact semantic and pragmatic development of writing content. Since formulaic language is imbued with syntactic, semantic and pragmatic linguistic features, it represents an ideal means to evaluate the influence of Asian EFL contexts on writing. Thus, formulaic language within academic texts from Korean university students was compared to that found in essays written by American university students. Results revealed that Korean EFL learners overused transitions to define the organization of academic texts at the expense of developing content. Moreover, they used repetition, general lists, and all-purpose formulaic language to "pad" content, neglecting to consider semantic or pragmatic purposes of the text. In contrast to their Korean EFL counterparts, American university students used formulaic language for a variety of pragmatic purposes such as involving the reader, putting examples into a larger perspective, adding connotation, and addressing the perspective of the reader. It appears that EFL contexts such as South Korea require pedagogical and curricular reforms which foster the development of writing composition for semantic and pragmatic purposes.

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Section: Formulaic Language In An Efl Contextmentioning

confidence: 99%

Improving EFL Writing Through Study of Semantic Concepts in Formulaic Language

Schenck¹,

Choi²

2014

ELT

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Machine Learning-Based Grammar Error Detection Method in English Composition

Zhu

Shi

Zhang

2021

Scientific Programming

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The detection of grammatical errors in English composition is an important task in the field of NLP. The main purpose of this task is to check out grammatical errors in English sentences and correct them. Grammatical error detection and correction are important applications in the automatic proofreading of English texts and in the field of English learning aids. With the increasing influence of English on a global scale, a huge breakthrough has been made in the task of detecting English grammatical errors. Based on machine learning, this paper designs a new method for detecting grammatical errors in English composition. First, this paper implements a grammatical error detection model based on Seq2Seq. Second, this paper implements a grammatical error detection and correction scheme based on the Transformer model. The Transformer model performs better than most grammar models. Third, this paper realizes the application of the BERT model in grammar error detection and error correction tasks, and the generalization ability of the model has been significantly enhanced. This solves the problem that the forward and backward cannot be merged when the Transformer trains the language model. Fourth, this paper proposes a method of grammatical error detection and correction in English composition based on a hybrid model. According to specific application scenarios, the corresponding neural network model is used for grammatical error correction. Combine the Seq2Seq structure to encode the input sequence and automate feature engineering. Through the combination of traditional model and deep model, the advantages are complemented to realize grammatical error detection and automatic correction.

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The potential of automated corrective feedback to remediate cohesion problems in advanced students’ writing

Strobl¹

2017

CALL in a Climate of Change: Adapting to Turbulent Global Conditions – Short Papers From EUROCALL 2017

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Abstract. This study explores the potential of a feedback environment using simple string-based pattern matching technology for the provision of automated corrective feedback on cohesion problems. Thirty-eight high-frequent problems, including non-target like use of connectives and co-references were addressed providing both direct and indirect feedback. Advanced students of German as a foreign language (L2) (n=36) received this feedback on summary writing in three subsequent sessions. Their revision activities were analysed for a ratio per 100 words and success rate, and their attitudes towards the feedback were investigated using questionnaires. The results show that automated feedback based on pattern matching has the potential to remedy over-and under-use of connectives and co-reference devices. Furthermore, although participants preferred direct feedback, the revision rate was higher with indirect metacognitive feedback providing grammar explanations.

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Cohesive Devices in English Writing Textbooks and Korean Learners’ English Writings

Cited by 5 publications

References 19 publications

Improving EFL Writing Through Study of Semantic Concepts in Formulaic Language

Improving EFL Writing Through Study of Semantic Concepts in Formulaic Language

Machine Learning-Based Grammar Error Detection Method in English Composition

The potential of automated corrective feedback to remediate cohesion problems in advanced students’ writing

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