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Showing 1 to 15 of 27 results Save | Export
Ekaterina Tabenkina – ProQuest LLC, 2023
The present project is a research-based and practice-tested online synchronous curriculum for English language learners with the Russian language mother tongue. The curriculum's theoretical component is grounded in Vygotsky's, Leont'ev', and Engestrom's "Cultural Historical Activity Theory" as well as in scholarly papers on the influence…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Foreign Countries
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Pratiwi, Damar Isti; Puspitasari, Armyta; Fikria, Ainun – TESL-EJ, 2023
While writing has evolved away from the conventional method of using pens and paper in favor of digital tools (Li et al., 2019), English teachers continue to face difficulties in teaching writing. This study shows how mind-mapping and the program, Writeabout, can be merged for online writing classes in English for Specific Purposes (ESP)…
Descriptors: Writing Instruction, Teaching Methods, Cognitive Mapping, Computer Assisted Instruction
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Qin, Ying – International Journal of Computer-Assisted Language Learning and Teaching, 2019
This study extracts the comments from a large scale of Chinese EFL learners' translation corpus to study the taxonomy of translation errors. Two unsupervised machine learning approaches are used to obtain the computational evidences of translation error taxonomy. After manually revision, ten types of English to Chinese (E2C) and eight types…
Descriptors: Taxonomy, Translation, Computer Assisted Instruction, Second Language Learning
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Lee, Kiyoung; Kwon, Oh-Woog; Kim, Young-Kil; Lee, Yunkeun – Research-publishing.net, 2015
This paper presents a hybrid approach for correcting grammatical errors in the sentences uttered by Korean learners of English. The error correction system plays an important role in GenieTutor, which is a dialogue-based English learning system designed to teach English to Korean students. During the talk with GenieTutor, grammatical error…
Descriptors: Grammar, Error Correction, Error Analysis (Language), Educational Strategies
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Choi, Inn-Chull – Computer Assisted Language Learning, 2016
A Web-based form-focused intelligent computer-assisted language learning (ICALL) tutoring system equipped with a process-oriented corrective feedback function was developed to investigate the extent to which such a program may serve as a viable method of teaching grammar to Korean secondary and elementary students. The present study was also…
Descriptors: Instructional Effectiveness, Computer Assisted Instruction, Intelligent Tutoring Systems, English (Second Language)
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Chukharev-Hudilainen, Evgeny; Saricaoglu, Aysel – Computer Assisted Language Learning, 2016
Expressing causal relations plays a central role in academic writing. While it is important that writing instructors assess and provide feedback on learners' causal discourse, it could be a very time-consuming task. In this respect, automated writing evaluation (AWE) tools may be helpful. However, to date, there have been no AWE tools capable of…
Descriptors: Discourse Analysis, Feedback (Response), Undergraduate Students, Accuracy
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Beuls, Katrien – Computer Assisted Language Learning, 2014
Construction grammar (CG) has been proposed as an adequate grammatical formalism for building intelligent language tutoring systems because it is highly compatible with the learning strategies observed in second language learning. Unfortunately, the lack of computational CG implementations has made it impossible in the past to corroborate these…
Descriptors: Error Analysis (Language), Grammar, Second Language Learning, Spanish
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Cowan, Ron; Choo, Jinhee; Lee, Gabseon Sunny – Language Learning & Technology, 2014
This study illustrates how a synergy of two technologies--Intelligent Computer-Assisted Language Learning (ICALL) and corpus linguistic analysis--can produce a lasting improvement in L2 learners' ability to edit persistent grammatical errors from their writing. A large written English corpus produced by Korean undergraduate and graduate students…
Descriptors: Computational Linguistics, Computer Assisted Instruction, Second Language Instruction, Second Language Learning
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MacDonald, Penny; Garcia-Carbonell, Amparo; Carot, Sierra, Jose Miguel – Language Learning & Technology, 2013
This study focuses on the computer-aided analysis of interlanguage errors made by the participants in the telematic simulation IDEELS (Intercultural Dynamics in European Education through on-Line Simulation). The synchronous and asynchronous communication analysed was part of the MiLC Corpus, a multilingual learner corpus of texts written by…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Interlanguage
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Amaral, Luiz A.; Meurers, W. Detmar – CALICO Journal, 2009
Error diagnosis in ICALL typically analyzes learner input in an attempt to abstract and identify indicators of the learner's (mis)conceptions of linguistic properties. For written input, this process usually starts with the identification of tokens that will serve as the atomic building blocks of the analysis. In this paper, we discuss the…
Descriptors: Grammar, Computer Assisted Instruction, Identification, Error Analysis (Language)
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Burston, Jack – CALICO Journal, 1996
Four grammar checkers, all of French Canadian origin, were evaluated: "Le Correcteur 101,""GramR,""Hugo Plus," and "French Proofing Tools." Results indicate that "Le Correcteur 101" is the best French grammar checker on the market and worth its premium cost. (two references) (CK)
Descriptors: Computer Assisted Instruction, Computer Software, Error Analysis (Language), Error Correction
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Sanders, Ruth – CALICO Journal, 1991
A typology for analyzing grammatical errors in student-written German compositions is presented and approaches to providing helpful error messages to student users of a parser-based writing aid are discussed. (19 references) (Author/LB)
Descriptors: Computer Assisted Instruction, Error Analysis (Language), German, Grammar
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Allen, John Robin – CALICO Journal, 1996
Discusses how computer-assisted language learning programs can generate error messages to help students in different ways. The article points out that an easier solution is to program a computer to recognize several different kinds of generic errors not related to any particular question but applicable to many situations, in order to generate…
Descriptors: College Students, Computer Assisted Instruction, Error Analysis (Language), Error Correction
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Rieber, Lloyd – College Teaching, 1992
One college writing teacher engaged his class in the revision of a computer program to check grammar, focusing on improvement of the algorithms for identifying inappropriate uses of the passive voice. Process and problems of constructing new algorithms, effects on student writing, and other algorithm applications are discussed. (MSE)
Descriptors: Algorithms, College Instruction, Computer Assisted Instruction, Computer Software
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Imlah, W. G.; du Boulay, J. B. H. – System, 1985
Describes an attempt to build a computer-assisted language instruction program which can trap and comment on grammatical errors such as subject/verb agreement by a purely syntactic analysis, that is, without recourse to word meanings. The program aims to increase educational effectiveness and to reduce the number of separate stored answers.…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Courseware, Error Analysis (Language)
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