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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
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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
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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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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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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
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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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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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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
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Harbusch, Karin; Itsova, Gergana; Koch, Ulrich; Kuhner, Christine – Computer Assisted Language Learning, 2008
We built an NLP system implementing a "virtual writing conference" for elementary-school children, with German as the target language. Currently, state-of-the-art computer support for writing tasks is restricted to multiple-choice questions or quizzes because automatic parsing of the often ambiguous and fragmentary texts produced by pupils…
Descriptors: Essays, Tests, Writing Instruction, Natural Language Processing
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Stewart, Iain A. D.; File, Portia – Computer Assisted Language Learning, 2007
Early and intermediate second language (L2) learners often encounter difficulties when engaging in introductory social conversations, typically having had little opportunity to practise such interactions. This article describes a project to design and prototype a computer dialogue system, Let's Chat, which would allow learners to rehearse social…
Descriptors: Second Language Learning, Speech Communication, Linguistic Input, Language Processing
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Vlugter, P.; Knott, A.; McDonald, J.; Hall, C. – Computer Assisted Language Learning, 2009
We describe a computer assisted language learning (CALL) system that uses human-machine dialogue as its medium of interaction. The system was developed to help students learn the basics of the Maori language and was designed to accompany the introductory course in Maori running at the University of Otago. The student engages in a task-based…
Descriptors: College Students, Introductory Courses, Malayo Polynesian Languages, Pretests Posttests
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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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Pasero, Robert; Sabatier, Paul – Computer Assisted Language Learning, 1998
Describes principles underlying ILLICO, a generic natural-language software tool for building larger applications for performing specific linguistic tasks such as analysis, synthesis, and guided composition. Shows to what extent this approach is relevant to the development of computer-assisted language-learning systems. (Author/VWL)
Descriptors: Computer Assisted Instruction, Computer Software, Natural Language Processing, Second Language Instruction