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Showing 1 to 15 of 24 results Save | Export
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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Rajati Mariappan; Kim Hua Tan; Bromeley Philip – Journal of Education and Learning (EduLearn), 2025
Incorporating technology with linguistics has created opportunities to explore the effectiveness of grammar checkers in cultivating an autonomous learning culture among English as a second language (ESL) and English as a foreign language (EFL) learner. Even though there have been numerous studies on grammar checkers to cultivate autonomous…
Descriptors: Computational Linguistics, Computer Software, Grammar, Private Schools
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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
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Chutinan Noobutra – LEARN Journal: Language Education and Acquisition Research Network, 2024
The present study investigates whether or not Thai students' English writing skills can be improved by using an online grammar checker. First, typical syntactic errors made by undergraduate students majoring in English and English for Careers were examined. Secondly, possible reasons for syntactic errors in English writing in the light of Lado's…
Descriptors: Error Correction, Native Language, Second Language Learning, Second Language Instruction
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Ritonga, Mahyudin; Zulmuqim, Zulmuqim; Bambang, Bambang; Kurniawan, Rahadian; Pahri, Pahri – World Journal on Educational Technology: Current Issues, 2022
Information technology provides a lot of convenience for humans in completing their tasks and getting results according to targets. In line with that, language teachers have a duty to find out the level of language skills and forms of language errors in students. Machine Learning as part of technology can be maximized to detect forms of Arabic…
Descriptors: Arabic, Error Correction, Video Technology, Speech Communication
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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
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Gupton, Timothy; Sánchez Calderón, Silvia – Second Language Research, 2023
We examine the second language (L2) acquisition of variable Spanish word order by first language (L1) speakers of English via the acquisition of unaccusative and transitive predicates in various focus-related contexts. We employ two bimodal linguistic tasks: (1) acceptability judgment task (B-AJT) and (2) appropriateness preference task (B-APT).…
Descriptors: Spanish, Second Language Learning, Second Language Instruction, Language Proficiency
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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
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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
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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
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Mughaz, Dror; Cohen, Michael; Mejahez, Sagit; Ades, Tal; Bouhnik, Dan – Interdisciplinary Journal of e-Skills and Lifelong Learning, 2020
Aim/Purpose: Using Artificial Intelligence with Deep Learning (DL) techniques, which mimic the action of the brain, to improve a student's grammar learning process. Finding the subject of a sentence using DL, and learning, by way of this computer field, to analyze human learning processes and mistakes. In addition, showing Artificial Intelligence…
Descriptors: Artificial Intelligence, Teaching Methods, Brain Hemisphere Functions, Grammar
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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
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DeKeyser, Robert M., Ed.; Botana, Goretti Prieto, Ed. – Language Learning & Language Teaching, 2019
This book is unique in bringing together studies on instructed second language acquisition that focus on a common question: "What renders this research particularly relevant to classroom applications, and what are the advantages, challenges, and potential pitfalls of the methodology adopted?" The empirical studies feature experimental,…
Descriptors: Second Language Learning, Second Language Instruction, Computer Assisted Instruction, Decision Making
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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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Crosthwaite, Peter – Computer Assisted Language Learning, 2017
An increasing number of studies have looked at the value of corpus-based data-driven learning (DDL) for second language (L2) written error correction, with generally positive results. However, a potential conundrum for language teachers involved in the process is how to provide feedback on students' written production for DDL. The study looks at…
Descriptors: Feedback (Response), Error Correction, Morphology (Languages), Syntax
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