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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
Joshua Kloppers – International Journal of Computer-Assisted Language Learning and Teaching, 2023
Automated writing evaluation (AWE) software is an increasingly popular tool for English second language learners. However, research on the accuracy of such software has been both scarce and largely limited in its scope. As such, this article broadens the field of research on AWE accuracy by using a mixed design to holistically evaluate the…
Descriptors: Grammar, Automation, Writing Evaluation, Computer Assisted Instruction
Waad Alsaweed; Saad Aljebreen – International Journal of Computer-Assisted Language Learning and Teaching, 2024
Artificial intelligence revolution becomes a trend in most aspects of life. ChatGPT, an AI chatbot, has impacted various domains, including education and language learning. Enhancing writing abilities of ESL learners requires frequent writing practice and feedback, which ChatGPT can easily provide. However, ChatGPT's accuracy in identifying and…
Descriptors: Error Correction, Writing Instruction, Grammar, Morphemes
Jiahui Wu; Jianwei Li; Zigang Ge; Mingrui Xu; Li Lin; Ru Zhang – Journal of Educational Computing Research, 2025
Automated written corrective feedback (AWCF) tools play a crucial role in supporting English writing instruction. However, issues such as insufficient accuracy and hallucination have undermined users' trust in these systems. To address these challenges, this study investigates the potential of Generative Artificial Intelligence (GAI) enhanced by…
Descriptors: Error Correction, Feedback (Response), Artificial Intelligence, Computer Software
Junifer Leal Bucol; Napattanissa Sangkawong – Innovations in Education and Teaching International, 2025
This research paper employs an exploratory framework to evaluate the potential of ChatGPT as an Automated Writing Evaluation (AWE) tool in teaching English as a Foreign Language (EFL) in Thailand. The main objective is to investigate how well ChatGPT can assess students' writing using prompts and pre-defined rubrics compared to human raters.…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, English (Second Language)
Mohsen, Mohammed Ali – Journal of Educational Computing Research, 2022
Written corrective feedback for improving L2 writing skills has been a debatable issue for more than two decades. The aims of this meta-analysis are to (1) provide a quantitative measure of the effect of computer-generated written feedback for improving L2 writing skills and (2) verify how moderators (i.e., adopted technology, task types, and…
Descriptors: Computer Assisted Instruction, Teaching Methods, Second Language Learning, Second Language Instruction
Mohammadi, Mojtaba; Zarrabi, Maryam; Kamali, Jaber – International Journal of Language Testing, 2023
With the incremental integration of technology in writing assessment, technology-generated feedback has found its way to take further steps toward replacing human corrective feedback and rating. Yet, further investigation is deemed necessary regarding its potential use either as a supplement to or replacement for human feedback. This study aims to…
Descriptors: Formative Evaluation, Writing Evaluation, Feedback (Response), Computer Assisted Testing
Saeed, Murad Abdu; Al Qunayeer, Huda Suleiman – Language Learning Journal, 2022
Teacher feedback has been reported to be challenging for learners to understand and use productively in revising their writing, especially when it is provided in a monologic manner. There have thus been calls for teachers to ensure feedback is more 'dialogic' or 'interactive', encouraging students to become active respondents to feedback rather…
Descriptors: Teacher Student Relationship, Feedback (Response), Computer Software, Writing Instruction
Ferman, Sara; Shmuel, Sapir Amira; Zaltz, Yael – Language Learning and Development, 2022
The acquisition of a new morphological rule can be influenced by numerous factors, including the type of feedback provided during learning. The present study aimed to test the effect of different feedback types on children's ability to learn and generalize an artificial morphological rule (AMR). Two groups of eight-year-olds learned to judge and…
Descriptors: Morphology (Languages), Feedback (Response), Error Correction, Learning Processes
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
Woodworth, Johanathan; Barkaoui, Khaled – TESL Canada Journal, 2020
While feedback is widely considered essential for second language (L2) writing development (Bitchener & Ferris, 2012), teachers may not always be able to provide their learners with immediate and frequent corrective feedback. Automated writing evaluation (AWE) systems can help respond to this challenge by providing L2 learners with written…
Descriptors: Writing Evaluation, Feedback (Response), Error Correction, Second Language Instruction
Xu, Yi – Interpreter and Translator Trainer, 2023
The research on interpreting aptitude has focused on the abilities, skills and personal traits of individuals in order to predict their future interpreting performance. However, an important variable between the personal characteristics and success of trainee interpreters in interpreter training, which is instructional practices, is overlooked.…
Descriptors: Prediction, Language Aptitude, Feedback (Response), Short Term Memory
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
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