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Tzu-Yu Tai – Computer Assisted Language Learning, 2024
Intelligent personal assistants (IPAs) are a valuable tool in language learning because they provide opportunities for authentic interaction. However, their effectiveness, compared with that of human interlocutors, in facilitating second and foreign language interaction has not been explored. Therefore, this study investigated the effect of IPAs…
Descriptors: Artificial Intelligence, Natural Language Processing, English (Second Language), Second Language Learning
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Chengyuan Jia; Khe Foon Hew; Mingting Li – Computer Assisted Language Learning, 2025
Listening is a major challenge for many English-as-a-foreign language (EFL) learners. Decoding training, which helps learners develop the ability to recognize words from speech, is frequently used to assist EFL learners. Although recent empirical studies on decoding training have provided positive evidence on its effectiveness in improving EFL…
Descriptors: Flipped Classroom, Second Language Learning, Second Language Instruction, Teaching Methods
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Guoyuhui Huang; Khe Foon Hew – Computer Assisted Language Learning, 2024
Over the past two decades, the Involvement Load Hypothesis (ILH) has become a popular buzzword in the field of Second Language Acquisition (SLA). Although applications of the ILH can improve students' learning of productive vocabulary, this effect appears to be transitory. Students' learning of productive vocabulary often fades over time, as shown…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Vocabulary Development
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Han, Chao; Lu, Xiaolei – Computer Assisted Language Learning, 2023
The use of translation and interpreting (T&I) in the language learning classroom is commonplace, serving various pedagogical and assessment purposes. Previous utilization of T&I exercises is driven largely by their potential to enhance language learning, whereas the latest trend has begun to underscore T&I as a crucial skill to be…
Descriptors: Translation, Computational Linguistics, Correlation, Language Processing
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Timpe-Laughlin, Veronika; Sydorenko, Tetyana; Daurio, Phoebe – Computer Assisted Language Learning, 2022
Often, second/foreign (L2) language learners receive little opportunity to interact orally in the target language. Interactive, conversation-based spoken dialog systems (SDSs) that use automated speech recognition and natural language processing have the potential to address this need by engaging learners in meaningful, goal-oriented speaking…
Descriptors: Second Language Learning, Second Language Instruction, Oral Language, Dialogs (Language)
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Moussalli, Souheila; Cardoso, Walcir – Computer Assisted Language Learning, 2020
Second/foreign language (L2) classrooms do not always provide opportunities for input and output practice [Lightbown, P. M. (2000). Classroom SLA research and second language teaching. Applied Linguistics, 21(4), 431-462]. The use of smart speakers such as Amazon Echo and its associated voice-controlled intelligent personal assistant (IPA) Alexa…
Descriptors: Artificial Intelligence, Pronunciation, Native Language, Listening Comprehension
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Tham, Irwan; Chau, Meng Huat; Thang, Siew Ming – Computer Assisted Language Learning, 2020
This study seeks to understand how bilinguals process texts with lexical cues in their first language (L1) and second language (L2) using an eye-tracking methodology. Quantitative data were obtained from an eye-tracker and a post-test, while qualitative data were gathered through interviews with the participants. The findings from the eye-tracking…
Descriptors: Language Processing, Bilingualism, Second Language Learning, Second Language Instruction
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Goh, Tiong-Thye; Sun, Hui; Yang, Bing – Computer Assisted Language Learning, 2020
This study investigates the extent to which microfeatures -- such as basic text features, readability, cohesion, and lexical diversity based on specific word lists -- affect Chinese EFL writing quality. Data analysis was conducted using natural language processing, correlation analysis and stepwise multiple regression analysis on a corpus of 268…
Descriptors: Essays, Writing Tests, English (Second Language), Second Language Learning
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Stengers, Hélène; Deconinck, Julie; Boers, Frank; Eyckmans, June – Computer Assisted Language Learning, 2016
This paper reports an experiment designed to evaluate an attempt to improve the effectiveness of an existing L2 idiom-learning tool. In this tool, learners are helped to associate the abstract, idiomatic meaning of expressions such as "jump the gun" (act too soon) with their original, concrete meaning (e.g. associating "jump the…
Descriptors: Figurative Language, Recall (Psychology), Second Language Learning, Second Language Instruction
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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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Huang, Hsin-chou – Computer Assisted Language Learning, 2015
With the advancement of such Web 2.0 applications as weblogs, language learners have more opportunities to use a target language for communication purposes and to experience peer collaboration and interaction. In the search for ways to augment an EFL curriculum in which speaking practice is limited but the demand for improving oral proficiencies…
Descriptors: Web 2.0 Technologies, Semi Structured Interviews, Electronic Publishing, English (Second Language)
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Karlström, Petter; Lundin, Eva – Computer Assisted Language Learning, 2013
Digital tools are not always used in the manner their designers had in mind. Therefore, it is not enough to assume that learning through CALL tools occurs in intended ways, if at all. We have studied the use of an enhanced word processor for writing essays in Swedish as a second language. The word processor contained natural language processing…
Descriptors: Computer Assisted Instruction, Second Language Instruction, Novelty (Stimulus Dimension), Natural Language Processing
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McBride, Kara – Computer Assisted Language Learning, 2011
This study investigated the effects of training learners of English as a foreign language with different rates of speech and controls over speech rate. Subjects were put into one of four treatment groups: (A) trained on listening comprehension materials recorded at a fast speed, (B) trained on slow recordings, (C) given some choice about the…
Descriptors: Listening Comprehension, Listening Skills, English (Second Language), Speech Communication
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Romeo, Kenneth – Computer Assisted Language Learning, 2008
This paper addresses the comprehension of relative clauses in audio prompts using online listening exercises implemented in a classroom. Reaction time to short and long sentences containing subject and object relative clauses was assessed in subjects attending an intensive ESL course for graduate students. The results indicate the possibility that…
Descriptors: Graduate Students, Sentences, Reaction Time, English (Second Language)
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