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W. A. Piyumi Udeshinee; Ola Knutsson; Sirkku Männikkö Barbutiu; Chitra Jayathilake – Computer Assisted Language Learning, 2024
The discussion on the dynamic assessment (DA) -- a combination of assessment and instruction -- and regulatory scales from implicit to explicit corrective feedback (CF) is relatively new in the CALL context. Applying the notions of Sociocultural Theory, Zone of Proximal Development (ZPD) and Mediation, the present study examines how a DA-based…
Descriptors: Synchronous Communication, Evaluation Methods, Feedback (Response), English (Second Language)
Peichin Chang; Pin-Ju Chen; Li-Ling Lai – Computer Assisted Language Learning, 2024
Machine Translation (MT) tools have advanced to a level of reliability such that it is now opportune to consider their place in language teaching and learning. Given their potential, the current study sought to engage EFL university sophomores in recursive editing afforded by Google Translate (GT) for one semester, and investigated (1) whether the…
Descriptors: Editing, Computer Software, Artificial Intelligence, Translation
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
Reynolds, Barry Lee; Kao, Chian-Wen – Computer Assisted Language Learning, 2021
Feedback researchers have given little attention to how administration of language-focused instruction before writing in a second language combined with subsequent error correction after writing can affect the grammatical accuracy of learners' future writing. Moreover, the mode of the instruction (i.e., teacher instruction or game-based…
Descriptors: Instructional Effectiveness, Direct Instruction, Second Language Instruction, Second Language Learning
Rassaei, Ehsan – Computer Assisted Language Learning, 2023
The main purpose of the present study is to propose a framework for implementing group dynamic assessment (DA) using students' smartphones for improving and assessing EFL learners' ability to produce well-formed and appropriate requests. This study focuses on five learner reciprocity moves during DA interactions to get deeper insights into the…
Descriptors: Computer Assisted Testing, Second Language Learning, Second Language Instruction, English (Second Language)
Sarré, Cédric; Grosbois, Muriel; Brudermann, Cédric – Computer Assisted Language Learning, 2021
Corrective feedback (CF) can be provided to learners in different ways (explicit or implicit, focused or unfocused) and is the subject of major controversies in second language acquisition research. As no clear consensus has been reached so far about the most effective approach to CF with a view to fostering accuracy in second language (L2)…
Descriptors: Blended Learning, Comparative Analysis, Second Language Learning, Second Language Instruction
Bibauw, Serge; François, Thomas; Desmet, Piet – Computer Assisted Language Learning, 2019
This article presents the results of a systematic review of the literature on dialogue-based CALL, resulting in a conceptual framework for research on the matter. Applications allowing a learner to have a conversation in a foreign language with a computer have been studied from various perspectives and under different names (dialogue systems,…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Teaching Methods
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
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
Rassaei, Ehsan – Computer Assisted Language Learning, 2022
The study reported here investigated the effects of recasts on L2 development in terms of promoting EFL learners' accuracy in using English articles during mobile-mediated audio and video interactions. Fifty-two Iranian EFL learners were randomly assigned into two audio and video recasts conditions as well as two audio and video control groups.…
Descriptors: Comparative Analysis, Video Technology, Second Language Learning, Second Language Instruction
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
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
Lee, Sangmin-Michelle – Computer Assisted Language Learning, 2020
Although it remains controversial, machine translation (MT) has gained popularity both inside and outside of the classroom. Despite the growing number of students using MT, little is known about its use as a pedagogical tool in the EFL classroom. The present study investigated the role of MT as a CALL tool in EFL writing. Most studies on MT as a…
Descriptors: Translation, Computational Linguistics, English (Second Language), Second Language Learning
Paul, Jing Z.; Friginal, Eric – Computer Assisted Language Learning, 2019
This study investigated the effects of Facebook and Twitter on foreign language (Chinese) learners' written production in both short- (10 days) and long-term (50 days) pseudo-experimental settings. Adopting two concepts (i.e. symmetric vs. asymmetric) from matrix theory in social network analysis, we categorized Facebook as a symmetric social…
Descriptors: Social Networks, Second Language Learning, Network Analysis, Sentences
Ranalli, Jim – Computer Assisted Language Learning, 2018
Automated written corrective feedback (AWCF) has qualities that distinguish it from teacher-provided WCF and potentially undermine claims about its value for L2 student writers, including disparities in the amounts of useful information it provides across error types and the fact that inaccuracies in error-flagging must be anticipated. It remains…
Descriptors: Error Correction, Feedback (Response), Computer Assisted Instruction, Second Language Learning