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Lee, Sangmin-Michelle – Computer Assisted Language Learning, 2023
With a significant number of students using machine translation (MT) for academic purposes in recent years, language teachers can no longer ignore it in their classrooms. Although an increasing number of studies have reported its pedagogical benefits, studies have also revealed that language teachers are still sceptical about using MT for various…
Descriptors: Instructional Effectiveness, Teaching Methods, Translation, Second Language Learning
Qing Ma; Rui Yuan; Lok Ming Eric Cheung; Jing Yang – Computer Assisted Language Learning, 2024
The development of corpus-based language pedagogy (CBLP) is a complex and intriguing process that pertains to how corpus technology is directly applied to classroom teaching. Using a case study approach, this study investigated how two experienced university English teachers integrated corpus technology in authentic classroom teaching. Data…
Descriptors: Teaching Methods, Pedagogical Content Knowledge, Computational Linguistics, English (Second Language)
Pérez-Paredes, Pascual – Computer Assisted Language Learning, 2022
This research uses the theoretical framework of CALL normalisation developed by Bax (2003) and Chambers and Bax (2006) to offer a systematic review (Gough et al., 2012) of the uses and spread of data-driven learning (DDL) and corpora in language learning and teaching across five major CALL-related journals during the 2011-2015 period. DDL research…
Descriptors: Computational Linguistics, Teaching Methods, Computer Assisted Instruction, Second Language Learning
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
Poole, Robert – Computer Assisted Language Learning, 2022
The present study explores the attitudes of novice teachers towards corpus-aided language learning and teaching in an undergraduate writing course for multilingual students at a large US public university. The participating instructors facilitated approximately 75 minutes of corpus training for their students and implemented 4-6 corpus activities…
Descriptors: Undergraduate Students, Beginning Teachers, Computational Linguistics, Second Language Learning
Crosthwaite, Peter; Luciana; Wijaya, David – Computer Assisted Language Learning, 2023
The use of corpora for the purposes of language teaching and learning, commonly known as "data-driven learning" (DDL), is gaining popularity across a range of CALL contexts. However, how trainee teachers attempt to develop the technological, pedagogical and content knowledge (TPACK) to integrate corpus tools and DDL pedagogy into…
Descriptors: Computer Assisted Instruction, Teaching Methods, Online Courses, English (Second Language)
Zare, Javad; Karimpour, Sedigheh; Aqajani Delavar, Khadijeh – Computer Assisted Language Learning, 2023
The purpose of the present study was to investigate if following data-driven learning (DDL) to raise the learners' awareness of discourse organizers through concordancing improves their comprehension of English academic lectures. To address this issue, the current study adopted a quasi-experimental (comparison group, pretest-posttest) design. 96…
Descriptors: Classroom Communication, Discourse Analysis, Computational Linguistics, English for Academic Purposes
Loncar, Michael; Schams, Wayne; Liang, Jong-Shing – Computer Assisted Language Learning, 2023
The following review incorporates a systematic selection, coding, and analysis methodology in order to compile a corpus of empirical research studies that investigate the use of technology-mediated feedback in L2 writing contexts published from 2015-2019. Trends are identified by coding and quantitatively analyzing key parameters of the corpus,…
Descriptors: Research Reports, Writing Instruction, Feedback (Response), Technology Uses in Education
Chung, Eun Seon; Ahn, Soojin – Computer Assisted Language Learning, 2022
Many studies that have investigated the educational value of online machine translation (MT) in second language (L2) writing generally report significant improvements after MT use, but no study as of yet has comprehensively analyzed the effectiveness of MT use in terms of various measures in syntactic complexity, accuracy, lexical complexity, and…
Descriptors: Translation, Computational Linguistics, English (Second Language), Second Language Learning
Guo, Qian; Feng, Ruiling; Hua, Yuanfang – Computer Assisted Language Learning, 2022
AWCF can facilitate academic writing development, especially for novice writers of English as a foreign language (EFL). Existing AWCF studies mainly focus on teacher and learner perceptions; fewer have investigated the error-correction effect of AWCF and factors related to the effect. Especially lacking is research on how successfully students can…
Descriptors: Error Correction, Feedback (Response), English (Second Language), Second Language Learning
Vakili, Shokoufeh; Ebadi, Saman – Computer Assisted Language Learning, 2022
Theoretically grounded in Vygotsky's sociocultural theory of mind, Dynamic Assessment (DA) provides researchers with the opportunity to investigate different aspects of learners' developmental trajectory, including the ways they overcome their errors. As a qualitative inquiry into the nature of errors reflecting learners' development in academic…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Computer Assisted Testing
Tsai, Kuei-Ju – Computer Assisted Language Learning, 2019
Corpora are well-known for the affordance to make linguistic regularities salient. Since the coinage of the term 'data-driven learning' (DDL) in the 1990s, much has been done to investigate the effects of DDL on learning vocabulary, most notably lexico-grammatical patterns. However, less researched is how learners construct vocabulary knowledge…
Descriptors: Dictionaries, Computational Linguistics, Second Language Learning, Second Language Instruction
Kennedy, Claire; Miceli, Tiziana – Computer Assisted Language Learning, 2017
While there is widespread agreement on the expected benefits of hands-on access to corpora for language learners, reports abound of the difficulties involved in realising those benefits in practice. A particular focus of discussion is the challenge of transferring the skills of the corpus linguist to learners, so that they can explore this type of…
Descriptors: Computational Linguistics, Teaching Methods, 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
Harvey-Scholes, Calum – Computer Assisted Language Learning, 2018
Software can facilitate English as a Foreign Language (EFL) students' self-correction of their free-form writing by detecting errors; this article examines the proportion of errors which software can detect. A corpus of 13,644 words of written English was created, comprising 90 compositions written by Spanish-speaking students at levels A2-B2…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Error Correction