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Yucel Yilmaz; Gisela Granena; Laia Canals; Aleksandra Malicka – Language Learning & Technology, 2024
The present study examines the impact of the explicitness of corrective feedback and explicit associative memory on the acquisition of -ing/-ed participial adjectives through delayed video-based corrective feedback. Fifty-two L1 Spanish learners were randomly assigned to one of three groups (implicit, explicit, or no-feedback) and performed an…
Descriptors: Foreign Countries, College Students, English (Second Language), Second Language Instruction
Alif Silpachai; Reza Neiriz; MacKenzie Novotny; Ricardo Gutierrez-Osuna; John M. Levis; Evgeny Chukharev – Language Learning & Technology, 2024
It is unclear whether corrective feedback (CF) provided by L2 computer-assisted pronunciation training (CAPT) tools must be 100% accurate to promote an acceptable level of improvement in pronunciation. Using a web-based interface, 30 native speakers of Chinese completed a pretest, a computer-based training session to produce nine sound contrasts…
Descriptors: College Students, Foreign Students, English (Second Language), Second Language Instruction
Rakhun Kim – Language Learning & Technology, 2024
This study investigated the instructional effects of learner uptake following automatic corrective recast from artificial intelligence (AI) chatbots on the learning of the English caused-motion construction. 69 novice-level EFL learners in a Korean high school were recruited to investigate the instructional effects of corrective recast from AI…
Descriptors: Artificial Intelligence, Error Correction, Second Language Learning, Second Language Instruction
Dongkawang Shin; Yuah V. Chon – Language Learning & Technology, 2023
Considering noticeable improvements in the accuracy of Google Translate recently, the aim of this study was to examine second language (L2) learners' ability to use post-editing (PE) strategies when applying AI tools such as the neural machine translator (MT) to solve their lexical and grammatical problems during L2 writing. This study examined 57…
Descriptors: Second Language Learning, Second Language Instruction, Translation, Computer Software
Ranalli, Jim; Yamashita, Taichi – Language Learning & Technology, 2022
To the extent automated written corrective feedback (AWCF) tools such as Grammarly are based on sophisticated error-correction technologies, such as machine-learning techniques, they have the potential to find and correct more common L2 error types than simpler spelling and grammar checkers such as the one included in Microsoft Word (technically…
Descriptors: Error Correction, Feedback (Response), Computer Software, Second Language Learning
Yiran Wen; Jian Li; Hongkang Xu; Hanwen Hu – Language Learning & Technology, 2023
The problem of cognitive overload is particularly pertinent in multimedia L2 classroom corrective feedback (CF), which involves rich communicative tools to help the class to notice the mismatch between the target input and learners' pronunciation. Based on multimedia design principles, this study developed a new multimodal CF model through…
Descriptors: Error Correction, Videoconferencing, Second Language Learning, Second Language Instruction
Bronson Hui; Björn Rudzewitz; Detmar Meurers – Language Learning & Technology, 2023
Interactive digital tools increasingly used for language learning can provide detailed system logs (e.g., number of attempts, responses submitted), and thereby a window into the user's learning processes. To date, SLA researchers have made little use of such data to understand the relationships between learning conditions, processes, and outcomes.…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Learning Processes
Kourtali, Nektaria-Efstathia – Language Learning & Technology, 2022
The role of recasts, a corrective feedback technique, has received much attention from instructed SLA researchers. While a variety of factors have been identified as influencing their effectiveness in facilitating uptake and L2 development (e.g., learners' age and level of proficiency), the role of mode of interaction has been the object of…
Descriptors: Teaching Methods, Computer Mediated Communication, Second Language Learning, Second Language Instruction
Yamashita, Taichi – Language Learning & Technology, 2021
This study investigated the effects of corrective feedback (CF) during in-class computer-mediated collaborative writing on grammatical accuracy in a new piece of individual writing. Forty-eight ESL students at an American university worked on two computer-mediated animation description tasks in pairs. The experimental group received indirect CF on…
Descriptors: Error Correction, Feedback (Response), Computer Mediated Communication, Synchronous Communication
Wu, Yi-ju – Language Learning & Technology, 2021
Adopting the approaches of "pattern hunting" and "pattern refining" (Kennedy & Miceli, 2001, 2010, 2017), this study investigates how seven freshman English students from Taiwan used the Corpus of Contemporary American English to discover collocation patterns for 30 near-synonymous change-of-state verbs and new ideas about…
Descriptors: Phrase Structure, Teaching Methods, Second Language Learning, Second Language Instruction
Chen, Zhenzhen; Chen, Weichao; Jia, Jiyou; Le, Huixiao – Language Learning & Technology, 2022
Despite the growing interest in investigating the pedagogical application of Automated Writing Evaluation (AWE) systems, studies on the process of AWE-supported writing are still scant. Adopting activity theory as the framework, this qualitative study aims to examine how students incorporated AWE feedback into their writing in an English as a…
Descriptors: Writing Instruction, Writing Processes, Teaching Methods, Learning Strategies
Gigue`re, Christine; Parks, Susan – Language Learning & Technology, 2018
This study examined the role of corrective feedback in the context of an English as a second language (ESL) and French as a second language (FSL) eTandem chat exchange involving Grade 6 students. The students were enrolled in intensive programs in the provinces of Quebec and Ontario and had an elementary to low intermediate level of language…
Descriptors: Feedback (Response), Computer Mediated Communication, Second Language Instruction, Second Language Learning
Gao, Jianwu; Ma, Shuang – Language Learning & Technology, 2019
This study investigated whether the effect of two forms of computer-automated metalinguistic corrective feedback in drills transferred to subsequent writing tasks. The English simple past tense, a learned structure, was selected as the target structure. Participants included 117 intermediate learners of English as a foreign language assigned to…
Descriptors: Feedback (Response), Metalinguistics, Computer Assisted Instruction, Drills (Practice)
Yoon, Hyunsook; Jo, Jung Won – Language Learning & Technology, 2014
Studies on students' use of corpora in L2 writing have demonstrated the benefits of corpora not only as a linguistic resource to improve their writing abilities but also as a cognitive tool to develop their learning skills and strategies. Most of the corpus studies, however, adopted either direct use or indirect use of corpora by students, without…
Descriptors: Error Correction, English (Second Language), Foreign Countries, Case Studies
Lawley, Jim – Language Learning & Technology, 2015
This paper describes the development of web-based software at a university in Spain to help students of EFL self-correct their free-form writing. The software makes use of an eighty-million-word corpus of English known to be correct as a normative corpus for error correction purposes. It was discovered that bigrams (two-word combinations of words)…
Descriptors: Computer Software, Second Language Learning, English (Second Language), Error Correction
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