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Austin, Gavin; Pongpairoj, Nattama; Trenkic, Danijela – Language Learning, 2015
Second language (L2) learners often show inconsistent production of some aspects of L2 grammar. One view, primarily based on data from L2 article production, suggests that grammatical patterns licensed by learners' native language (L1) and those licensed by their L2 compete for selection, leading to variability in the production of L2 functional…
Descriptors: English (Second Language), Second Language Learning, Grammar, Bilingualism
Lin, Phoebe M. S. – Applied Linguistics, 2012
With the ever increasing number of studies on formulaic language, we are beginning to learn more about the processing of formulaic language (e.g. Ellis et al. 2008; Siyanova et al. 2011), its use in speech (e.g. Aijmer 1996; Wood 2012) and writing (e.g. Hyland 2008a, 2008b) and its application in natural language processing (e.g. Tschichold 2000).…
Descriptors: Evidence, Language Research, Applied Linguistics, Memory
Enright, Mary K.; Quinlan, Thomas – Language Testing, 2010
E-rater[R] is an automated essay scoring system that uses natural language processing techniques to extract features from essays and to model statistically human holistic ratings. Educational Testing Service has investigated the use of e-rater, in conjunction with human ratings, to score one of the two writing tasks on the TOEFL-iBT[R] writing…
Descriptors: Second Language Learning, Scoring, Essays, Language Processing
Chapelle, Carol A.; Chung, Yoo-Ree – Language Testing, 2010
Advances in natural language processing (NLP) and automatic speech recognition and processing technologies offer new opportunities for language testing. Despite their potential uses on a range of language test item types, relatively little work has been done in this area, and it is therefore not well understood by test developers, researchers or…
Descriptors: Test Items, Computational Linguistics, Testing, Language Tests
Wagner, Joachim; Foster, Jennifer; van Genabith, Josef – CALICO Journal, 2009
A classifier which is capable of distinguishing a syntactically well formed sentence from a syntactically ill formed one has the potential to be useful in an L2 language-learning context. In this article, we describe a classifier which classifies English sentences as either well formed or ill formed using information gleaned from three different…
Descriptors: Sentences, Language Processing, Natural Language Processing, Grammar
Ellis, Nick C.; Simpson-Vlach, Rita; Maynard, Carson – TESOL Quarterly: A Journal for Teachers of English to Speakers of Other Languages and of Standard English as a Second Dialect, 2008
Natural language makes considerable use of recurrent formulaic patterns of words. This article triangulates the construct of "formula" from corpus linguistic, psycholinguistic, and educational perspectives. It describes the corpus linguistic extraction of pedagogically useful formulaic sequences for academic speech and writing. It determines…
Descriptors: Psycholinguistics, Second Language Learning, Language Processing, Native Speakers
Liou, Hsien-Chin; Chang, Jason S; Chen, Hao-Jan; Lin, Chih-Cheng; Liaw, Meei-Ling; Gao, Zhao-Ming; Jang, Jyh-Shing Roger; Yeh, Yuli; Chuang, Thomas C.; You, Geeng-Neng – CALICO Journal, 2006
This paper describes the development of an innovative web-based environment for English language learning with advanced data-driven and statistical approaches. The project uses various corpora, including a Chinese-English parallel corpus ("Sinorama") and various natural language processing (NLP) tools to construct effective English…
Descriptors: Natural Language Processing, English (Second Language), Bilingualism, Web Based Instruction
Dodigovic, Marina – Language Awareness, 2003
Based on the statistical regularity of certain error types, an interlanguage grammar could be devised and applied to develop an intelligent computer tool, capable not only of identifying the typical errors in L2 student writing, but also of making adequate corrections. The purpose of the corrections is to make the student aware of the language…
Descriptors: Assignments, Sentences, Research and Development, Metalinguistics

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