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Tzu-Yu Tai; Howard Hao-Jan Chen – Computer Assisted Language Learning, 2024
English speaking is considered the most difficult and anxiety-provoking language skill for EFL learners due to lack of access to authentic language use, fear of making mistakes, and peers' negative comments. With automatic speech recognition and natural language processing, intelligent personal assistants (IPAs) have potential in foreign language…
Descriptors: English (Second Language), Speech Communication, English Language Learners, Anxiety
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
Huang, Ping-Yu; Tsao, Nai-Lung – Computer Assisted Language Learning, 2021
In this article, we describe an online English collocation explorer developed to help English L2 learners produce correct and appropriate collocations. Our tool, which is able to visually represent relevant correct/incorrect collocations on a single webpage, was designed based on the notions of collocation clusters and intercollocability proposed…
Descriptors: Second Language Learning, Second Language Instruction, English (Second Language), Error Correction
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
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
Aryadoust, Vahid; Ang, Bee Hoon – Computer Assisted Language Learning, 2021
Eye tracking technology has become an increasingly popular methodology in language studies. Using data from 27 journals in language sciences indexed in the Social Science Citation Index and/or Scopus, we conducted an in-depth scientometric analysis of 341 research publications together with their 14,866 references between 1994 and 2018. We…
Descriptors: Eye Movements, Sex Stereotypes, Research Reports, Trend Analysis
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)
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
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
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
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
Pérez-Paredes, Pascual; Ordoñana Guillamón, Carlos; Aguado Jiménez, Pilar – Computer Assisted Language Learning, 2018
Combined with the ubiquity and constant connectivity of mobile devices, and with innovative approaches such as Data-Driven Learning (DDL), Natural Language Processing Technologies (NLPTs) as Open Educational Resources (OERs) could become a powerful tool for language learning as they promote individual and personalized learning. Using a…
Descriptors: Language Teachers, Educational Resources, Telecommunications, Handheld Devices
Chen, Julian ChengChiang – Computer Assisted Language Learning, 2018
Driven by interactionist theory and operationalized by task-based interaction, this study aims to investigate EFL learners' task-based negotiation in Second Life (SL), a 3D multi-user virtual environment (MUVE). A group of adult EFL learners with diverse cultural/linguistic backgrounds in L1 participated in this task-based virtual class. Learners…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computer Assisted Instruction
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
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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