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Hanne Roothooft; Amparo Lázaro-Ibarrola; Bram Bulté – Language Teaching Research, 2025
Second language (L2) writing research has demonstrated that young learners discuss linguistic issues, make use of feedback, and show a generally positive disposition toward writing tasks. However, many issues deserve further investigation. Regarding task implementation, few studies have been conducted with young learners writing individually, and…
Descriptors: Error Correction, Feedback (Response), Accuracy, Writing Instruction
Wen Liu – Language Teaching Research Quarterly, 2024
Automated writing evaluation feedback (AWE) has become popular in writing classrooms. However, few studies have conducted a comprehensive review of the employment of AWE in learning areas. This study aimed to provide a systematic review of the current research on AWE feedback, including its validity, effects, and students' engagement with AWE…
Descriptors: Writing Instruction, Learner Engagement, Feedback (Response), Teaching Methods
Godwin-Jones, Robert – Language Learning & Technology, 2022
In recent years, advances in artificial intelligence (AI) have led to significantly improved, or in some cases, completely new digital tools for writing. Systems for writing assessment and assistance based on automated writing evaluation (AWE) have been available for some time. That is the case for machine translation as well. More recent are…
Descriptors: Writing Instruction, Artificial Intelligence, Feedback (Response), Writing Evaluation
Lee, Sangmin-Michelle; Briggs, Neil – ReCALL, 2021
In recent years, marked gains in the accuracy of machine translation (MT) outputs have greatly increased its viability as a tool to support the efforts of English as a foreign language (EFL) students to write in English. This study examines error corrections made by 58 Korean university students by comparing their original L2 texts to that of MT…
Descriptors: Translation, Computational Linguistics, Second Language Learning, Second Language Instruction
Lee, Yo-An – English Teaching, 2023
Interactional modification is important in SLA research because it involves correcting problematic L2 use. However, not all modifications will lead to pedagogical changes. Participants in conversational interactions are not always oriented to linguistic forms or functions. One way to address this dilemma is to examine the process by which…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Discourse Analysis
Gamze Emir; Gonca Yangin-Eksi – TEFLIN Journal: A publication on the teaching and learning of English, 2023
This study investigated the effectiveness of using corpus as a data-driven learning (DDL) tool to enhance the academic writing skills of Turkish EFL learners. The study also explored learners' views of the potential use of corpus in L2 academic writing. To achieve these objectives, a mixed-method sequential explanatory design was employed,…
Descriptors: Computational Linguistics, English for Academic Purposes, Second Language Learning, Second Language Instruction
Waer, Hanan – Innovation in Language Learning and Teaching, 2023
Recent years have witnessed an increased interest in automated writing evaluation (hereafter AWE). However, few studies have examined the use of AWE with apprehensive writers. Hence, this study extends research in this area, investigating the effect of using AWE on reducing writing apprehension and enhancing grammatical knowledge. The participants…
Descriptors: Writing Evaluation, Writing Apprehension, English (Second Language), Second Language Learning
Mirzaeian, Vahid R. – The EUROCALL Review, 2021
Although the field of machine translation has witnessed huge improvements in recent years, its potentials have not been fully exploited in other interdisciplinary areas such as foreign language teaching. The aim of this paper, therefore, is to report an experiment in which this technology was employed to teach a foreign language to a group of…
Descriptors: Translation, Computational Linguistics, Error Correction, Phrase Structure
Xu, Wenwen; Kim, Ji-Hyun – English Teaching, 2023
This study explored the role of written languaging (WL) in response to automated written corrective feedback (AWCF) in L2 accuracy improvement in English classrooms at a university in China. A total of 254 freshmen enrolled in intermediate composition classes participated, and they wrote 4 essays and received AWCF. A half of them engaged in WL…
Descriptors: Grammar, Accuracy, Writing Instruction, Writing Evaluation
Valizadeh, Mohammadreza; Soltanpour, Fatemeh – Eurasian Journal of Applied Linguistics, 2021
This experimental study, using a pretest-treatment-posttest design, compared the effects of focused direct written corrective feedback and additional writing practice on L2 learners' written syntactic complexity. The participants were 60 Iranian elementary EFL learners, whose L2 proficiency as well as L2 writing syntactic complexity and accuracy…
Descriptors: Error Correction, Feedback (Response), Teaching Methods, 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
Bonner, Euan; Lege, Ryan; Frazier, Erin – Teaching English with Technology, 2023
Large Language Models (LLMs) are a powerful type of Artificial Intelligence (AI) that simulates how humans organize language and are able to interpret, predict, and generate text. This allows for contextual understanding of natural human language which enables the LLM to understand conversational human input and respond in a natural manner. Recent…
Descriptors: Teaching Methods, Artificial Intelligence, Second Language Learning, Second Language Instruction
Crosthwaite, Peter – Australian Review of Applied Linguistics, 2020
This paper describes the rationale, design and implementation of a short private online course (SPOC) on data-driven learning (DDL) (Johns, 1991), focusing on L2 error correction in postgraduate academic writing and involving over 300 registered users. I discuss the affordances of using a SPOC platform (namely "EdX") for online DDL…
Descriptors: Higher Education, Online Courses, Second Language Learning, Error Correction
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
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
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