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Showing 1 to 15 of 26 results Save | Export
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Dan Zhao – Education and Information Technologies, 2025
Artificial intelligence is revolutionizing the education landscape and has been widely applied to language teaching and learning. This study investigates the transformative potential of AI-driven Natural Language Processing (NLP) tools in enhancing writing proficiency, focusing on language precision, content summarization, and creative writing…
Descriptors: Artificial Intelligence, Writing Skills, English (Second Language), Second Language Instruction
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Kai Guo; Deliang Wang – Education and Information Technologies, 2024
ChatGPT, the newest pre-trained large language model, has recently attracted unprecedented worldwide attention. Its exceptional performance in understanding human language and completing a variety of tasks in a conversational way has led to heated discussions about its implications for and use in education. This exploratory study represents one of…
Descriptors: Feedback (Response), English (Second Language), Artificial Intelligence, Natural Language Processing
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Osama Koraishi – Language Teaching Research Quarterly, 2024
This study conducts a comprehensive quantitative evaluation of OpenAI's language model, ChatGPT 4, for grading Task 2 writing of the IELTS exam. The objective is to assess the alignment between ChatGPT's grading and that of official human raters. The analysis encompassed a multifaceted approach, including a comparison of means and reliability…
Descriptors: Second Language Learning, English (Second Language), Language Tests, Artificial Intelligence
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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
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Uzun, Kutay; Ulum, Ömer Gökhan – Acuity: Journal of English Language Pedagogy, Literature and Culture, 2022
This study aimed to utilize sentiment and sentence similarity analyses, two Natural Language Processing techniques, to see if and how well they could predict L2 Writing Performance in integrated and independent task conditions. The data sources were an integrated L2 writing corpus of 185 literary analysis essays and an independent L2 writing…
Descriptors: Natural Language Processing, Second Language Learning, Second Language Instruction, Writing (Composition)
Shabnam Behzad – ProQuest LLC, 2024
Second language learners constitute a significant and expanding portion of the global population and there is a growing demand for tools that facilitate language learning and instruction across various levels and in different countries. The development of large language models (LLMs) has brought about a significant impact on the domains of natural…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Second Language Learning
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Hwang, Haerim; Kim, Hyunwoo – Applied Linguistics, 2023
One of the important components in second language (L2) development is to produce clause-level units of form-meaning pairings or argument structure constructions. Based on the usage-based constructionist approach that language development entails an ability to use more diverse, more complex, and less frequent constructions, this study tested…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Predictor Variables
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Xiaoling Bai; Nur Rasyidah Mohd Nordin – Eurasian Journal of Applied Linguistics, 2025
A perfect writing skill has been deemed instrumental to achieving competence in EFL, yet it is considered one of the most impressive learning domains. This study investigates the impact of human-AI collaborative feedback on the writing proficiency of EFL students. It examines key teaching domains, including the teaching environment, teacher…
Descriptors: Artificial Intelligence, Feedback (Response), Evaluators, Writing Skills
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Giang Thi Linh Hoang; Neomy Storch – Iranian Journal of Language Teaching Research, 2024
Research has suggested that the type of feedback learners receive can impact on whether learners understand the feedback, the extent to which they engage with it, and whether they incorporate it in their revised drafts. However, to date, only a small number of studies have investigated learner engagement with corrective feedback provided by…
Descriptors: Case Studies, Language Processing, English (Second Language), Second Language Learning
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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
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Miranty, Delsa; Widiati, Utami – Pegem Journal of Education and Instruction, 2021
Automated Writing Evaluation (AWE) has been considered a potential pedagogical technique that exploits technology to assist the students' writing. However, little attention has been devoted to examining students' perceptions of Grammarly use in higher education context. This paper aims to obtain information regarding the writing process and the…
Descriptors: Foreign Countries, Technology Uses in Education, Writing (Composition), Student Attitudes
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Sari, Elif; Han, Turgay – Reading Matrix: An International Online Journal, 2021
Providing both effective feedback applications and reliable assessment practices are two central issues in ESL/EFL writing instruction contexts. Giving individual feedback is very difficult in crowded classes as it requires a great amount of time and effort for instructors. Moreover, instructors likely employ inconsistent assessment procedures,…
Descriptors: Automation, Writing Evaluation, Artificial Intelligence, Natural Language Processing
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Liang, Yaqing; Li, Yanzhi; Sang, Zhonggang – Language Assessment Quarterly, 2023
This study investigated how peer-mediated Dynamic Assessment (DA) unfolded in translation revision competence (TRC) of students of Master's degree of Translation and Interpreting (MTI) in China. Thirty subjects first completed three revision tasks and were then rated as high- or low-level performers according to their average scores across the…
Descriptors: Translation, Student Evaluation, Peer Evaluation, Revision (Written Composition)
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González, Ruth Carolina Betancourt; Martínez, Elizabeth Alvarado – MEXTESOL Journal, 2020
In order to investigate the internal factors present in the interlanguage of learners of English as a foreign language, a qualitative research study was implemented to analyze the written productions of college students. The main objective of this case study was to identify the type of errors the students made and suggest the cognitive reasons…
Descriptors: Interlanguage, English (Second Language), Second Language Learning, Second Language Instruction
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Kim, Young-Suk Grace; Wolters, Alissa; Mercado, Janet; Quinn, Jamie – Journal of Educational Psychology, 2022
We investigated the dimensionality and relations between L1 (a speaker's first language) and L2 (a speaker's second language) writing skills in narrative and informational genres and higher order cognitive skills--inference, perspective taking, and comprehension monitoring--for Spanish-English dual language learners in primary grades. Dimensions…
Descriptors: Transfer of Training, Second Language Learning, Native Language, Bilingualism
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