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Gao, Zhao-Ming – Computer Assisted Language Learning, 2011
Previous studies on self-correction using corpora involve monolingual concordances and intervention from instructors such as marking of errors, the use of modified concordances, and other simplifications of the task. Can L2 learners independently refine their previous outputs by simply using a parallel concordancer without any hints about their…
Descriptors: Translation, Pretests Posttests, Guidelines, English (Second Language)
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
Amaral, Luiz; Meurers, Detmar; Ziai, Ramon – Computer Assisted Language Learning, 2011
Intelligent language tutoring systems (ILTS) typically analyze learner input to diagnose learner language properties and provide individualized feedback. Despite a long history of ILTS research, such systems are virtually absent from real-life foreign language teaching (FLT). Taking a step toward more closely linking ILTS research to real-life…
Descriptors: Feedback (Response), Second Language Learning, Intelligent Tutoring Systems, Information Management
Wu, Shaoqun; Franken, Margaret; Witten, Ian H. – Computer Assisted Language Learning, 2010
Extensive knowledge of collocations is a key factor that distinguishes learners from fluent native speakers. Such knowledge is difficult to acquire simply because there is so much of it. This paper describes a system that exploits the facilities offered by digital libraries to provide a rich collocation-learning environment. The design is based on…
Descriptors: Electronic Libraries, Language Processing, Internet, Native Speakers
Dickinson, Markus; Eom, Soojeong; Kang, Yunkyoung; Lee, Chong Min; Sachs, Rebecca – Computer Assisted Language Learning, 2008
Task-based synchronous computer-mediated communication (CMC) may represent an optimal psycholinguistic environment for form-meaning connections, but learners do not receive feedback from a trusted authority. Intelligent computer-assisted language learning (ICALL) provides feedback, but the encouragement of communicative interaction remains largely…
Descriptors: Feedback (Response), Computer Mediated Communication, Computer Assisted Instruction, Second Language Learning
Lee, Lina – Computer Assisted Language Learning, 2009
Blogs and podcasts open new ways for global communication and development of intercultural awareness. This article reports a Spanish-American telecollaborative project through which students created blogs and podcasts for intercultural exchanges in light of the sociocultural perspectives. The article outlines the methodology for the project…
Descriptors: Web Sites, Intercultural Communication, Electronic Publishing, Cultural Awareness
Loewen, Shawn; Reissner, Sophie – Computer Assisted Language Learning, 2009
Although many second language learners still study in a traditional, face-to-face classroom, an increasing number of students now participate in virtual classrooms and communicate online. Regardless of the mode of communication, interaction and focus on form can be considered important components of the learning environment. This paper reports on…
Descriptors: Second Language Instruction, Interaction, Foreign Countries, English (Second Language)
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
Dekhinet, Rayenne – Computer Assisted Language Learning, 2008
This study investigates the value of online enhanced corrective feedback for non-native speakers of English from (1) the quality of their interaction online, (2) their perceptions, and (3) the challenges encountered. Online enhanced feedback is an online peer tutoring technique that was developed from Negotiated Meaning and used by native speakers…
Descriptors: Peer Teaching, Native Speakers, English (Second Language), Tutoring
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
Edasawa, Yasuyo; Kabata, Kaori – Computer Assisted Language Learning, 2007
This study investigates the effect of a cross-cultural bilingual communication project on students' second language learning. A collaborative key-pal project was conducted between Japanese university students learning English and Canadian university students learning Japanese. Ethnographic data were collected from the students' exchanged messages…
Descriptors: Ethnography, Communication Skills, Bilingualism, English (Second Language)
Fischer, Robert – Computer Assisted Language Learning, 2007
This article presents a survey of computer-based tracking in CALL and the uses to which the analysis of tracking data can be put to address questions in CALL in particular and second language acquisition (SLA) in general. Adopting both quantitative and qualitative methods, researchers have found that students often use software in unexpected ways,…
Descriptors: Computer Mediated Communication, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
Peer reviewedYang, Jie Chi; Akahori, Kanji – Computer Assisted Language Learning, 1999
Compares two Web-based systems. The Japanese writing computer-assisted language-learning system, the T system, enables learners to key-in sentences freely, detects learners' errors and displays appropriate feedback messages to guide learners to correct errors themselves. The M system enables learners to input their answer from a multiple selection…
Descriptors: Comparative Analysis, Computer Assisted Instruction, Error Correction, Feedback
Heift, Trude – Computer Assisted Language Learning, 2006
This article discusses design and usability issues pertaining to context-sensitive "help" in computer-assisted language learning (CALL). As part of the discussion, we present a study in which we examined the effects of three independent factors on student usage of context-sensitive "help": feedback, exercise type, and language proficiency. Forty…
Descriptors: Computer Assisted Instruction, Second Language Instruction, Second Language Learning, Feedback
Loewen, Shawn; Erlam, Rosemary – Computer Assisted Language Learning, 2006
Zo eplicates in a synchronous learning environment a study that looked at the effectiveness of providing two types of corrective feedback to students in the classroom. Elementary learners of L2 English (N = 31) completed two communicative tasks, during which time they received either recasts (implicit feedback) or metalinguistic information…
Descriptors: English (Second Language), Second Language Learning, Feedback, Instructional Effectiveness

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