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Showing 1 to 15 of 32 results Save | Export
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Bolgün, M. Ali; McCaw, Tatiana – Computer Assisted Language Learning, 2019
With the ever-increasing number of available language technology products, there is also a need to evaluate them objectively. Unsubstantiated beliefs about what language technology can and cannot do inside or outside the language classroom often influence decisions about the choice of language technology to be used. The declarative/procedural…
Descriptors: Neurosciences, Second Language Learning, Second Language Instruction, Metalinguistics
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Choi, Sung-Kwon; Kwon, Oh-Woog; Kim, Young-Kil – Research-publishing.net, 2017
This paper aims to describe a computer-assisted English learning system using chatbots and dialogue systems, which allow free conversation outside the topic without limiting the learner's flow of conversation. The evaluation was conducted by 20 experimenters. The performance of the system based on a free conversation by topic was measured by the…
Descriptors: Foreign Countries, Second Language Learning, English (Second Language), Second Language Instruction
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Heift, Trude; Schulze, Mathias – Language Teaching, 2015
"Sometimes maligned for its allegedly behaviorist connotations but critical for success in many fields from music to sport to mathematics and language learning, 'practice' is undergoing something of a revival in the applied linguistics literature" (Long & Richards 2007, p. xi). This research timeline provides a systematic overview of…
Descriptors: Computer Assisted Instruction, Second Language Instruction, Second Language Learning, Learning Processes
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Kwon, Oh-Woog; Lee, Kiyoung; Kim, Young-Kil; Lee, Yunkeun – Research-publishing.net, 2015
This paper introduces a Dialog-Based Computer-Assisted second-Language Learning (DB-CALL) system using semantic and grammar correctness evaluations and the results of its experiment. While the system dialogues with English learners about a given topic, it automatically evaluates the grammar and content properness of their English utterances, then…
Descriptors: Computer Assisted Instruction, Semantics, Grammar, Teaching Methods
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Harbusch, Karin; Cameran, Christel-Joy; Härtel, Johannes – Research-publishing.net, 2014
We present a new feedback strategy implemented in a natural language generation-based e-learning system for German as a second language (L2). Although the system recognizes a large proportion of the grammar errors in learner-produced written sentences, its automatically generated feedback only addresses errors against rules that are relevant at…
Descriptors: German, Second Language Learning, Second Language Instruction, Feedback (Response)
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Engwall, Olov – Computer Assisted Language Learning, 2012
Pronunciation errors may be caused by several different deviations from the target, such as voicing, intonation, insertions or deletions of segments, or that the articulators are placed incorrectly. Computer-animated pronunciation teachers could potentially provide important assistance on correcting all these types of deviations, but they have an…
Descriptors: Feedback (Response), Phonetics, Pronunciation, Computer Assisted Instruction
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O'Brien, Myles – The EUROCALL Review, 2012
The Mango Suite is a set of three freely downloadable cross-platform authoring programs for flexible network-based CALL exercises. They are Adobe Air applications, so they can be used on Windows, Macintosh, or Linux computers, provided the freely-available Adobe Air has been installed on the computer. The exercises which the programs generate are…
Descriptors: Web Based Instruction, Computer Software, Error Correction, Feedback (Response)
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Heift, Trude – CALICO Journal, 2010
This article discusses the development and functionalities of an intelligent computer-assisted language learning (ICALL) system. By way of example, we describe "E-Tutor", an ICALL system for L2 learners of German that has been in use for a decade. Based on advancements in technology, user studies with L2 learners of German as well as feedback…
Descriptors: Feedback (Response), Use Studies, Computer Assisted Instruction, Educational Technology
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Blanchard, Alexia; Kraif, Olivier; Ponton, Claude – CALICO Journal, 2009
This paper presents a "didactic triangulation" strategy to cope with the problem of reliability of NLP applications for computer-assisted language learning (CALL) systems. It is based on the implementation of basic but well mastered NLP techniques and puts the emphasis on an adapted gearing between computable linguistic clues and didactic features…
Descriptors: Spelling, Educational Technology, Natural Language Processing, Computer Assisted Instruction
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Nagata, Noriko – CALICO Journal, 2009
This paper presents a new version of Robo-Sensei's NLP (Natural Language Processing) system which updates the version currently available as the software package "ROBO-SENSEI: Personal Japanese Tutor" (Nagata, 2004). Robo-Sensei's NLP system includes a lexicon, a morphological generator, a word segmentor, a morphological parser, a syntactic…
Descriptors: Textbooks, Computer Assisted Instruction, Computer Software, Natural Language Processing
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Gamon, Michael; Leacock, Claudia; Brockett, Chris; Dolan, William B.; Gao, Jianfeng; Belenko, Dmitriy; Klementiev, Alexandre – CALICO Journal, 2009
In this paper we present a system for automatic correction of errors made by learners of English. The system has two novel aspects. First, machine-learned classifiers trained on large amounts of native data and a very large language model are combined to optimize the precision of suggested corrections. Second, the user can access real-life web…
Descriptors: English (Second Language), Error Correction, Second Language Learning, Computer Assisted Instruction
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De Felice, Rachele; Pulman, Stephen – CALICO Journal, 2009
In this article, we present an approach to the automatic correction of preposition errors in L2 English. Our system, based on a maximum entropy classifier, achieves average precision of 42% and recall of 35% on this task. The discussion of results obtained on correct and incorrect data aims to establish what characteristics of L2 writing prove…
Descriptors: Language Patterns, Form Classes (Languages), Error Correction, Second Language Learning
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Futagi, Yoko; Deane, Paul; Chodorow, Martin; Tetreault, Joel – Computer Assisted Language Learning, 2008
This paper describes the first prototype of an automated tool for detecting collocation errors in texts written by non-native speakers of English. Candidate strings are extracted by pattern matching over POS-tagged text. Since learner texts often contain spelling and morphological errors, the tool attempts to automatically correct them in order to…
Descriptors: Native Speakers, English (Second Language), Limited English Speaking, Computational Linguistics
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Granger, Sylviane; Kraif, Olivier; Ponton, Claude; Antoniadis, Georges; Zampa, Virginie – ReCALL, 2007
Learner corpora, electronic collections of spoken or written data from foreign language learners, offer unparalleled access to many hitherto uncovered aspects of learner language, particularly in their error-tagged format. This article aims to demonstrate the role that the learner corpus can play in CALL, particularly when used in conjunction with…
Descriptors: Metalinguistics, Natural Language Processing, English (Second Language), Second Language Learning
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Chang, Yu-Chia; Chang, Jason S.; Chen, Hao-Jan; Liou, Hsien-Chin – Computer Assisted Language Learning, 2008
Previous work in the literature reveals that EFL learners were deficient in collocations that are a hallmark of near native fluency in learner's writing. Among different types of collocations, the verb-noun (V-N) one was found to be particularly difficult to master, and learners' first language was also found to heavily influence their collocation…
Descriptors: Sentence Structure, Verbs, Nouns, Foreign Countries
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