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Showing 1 to 15 of 21 results Save | Export
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Wajeeh Daher; Faaiz Gierdien – African Journal of Research in Mathematics, Science and Technology Education, 2024
Texts generated by artificial intelligence agents have been suggested as tools supporting students' learning. The present research analyses the language of texts generated by ChatGPT when solving mathematical problems related to the quadratic equation. We use the functional grammar theoretical framework that includes three meta-functions: the…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Problem Solving
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Montri Tangpijaikul – LEARN Journal: Language Education and Acquisition Research Network, 2025
Despite the significant impact of the lexical approach for vocabulary learning, its classroom implementation has not been uniform. While related activities share the common Observe-Hypothesize-Experiment (OHE) elements, practitioners and researchers do not highlight how language input from the observing stage is turned into output and at what…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Teaching Methods
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Atthasith Chuanpipatpong – PASAA: Journal of Language Teaching and Learning in Thailand, 2025
Writing is often considered the most difficult language skill for EFL learners due to its persistent grammatical and lexical challenges. Although tools such as Google Translate and ChatGPT are increasingly used, concerns persist regarding overreliance and reduced learner autonomy. This study investigated the grammatical errors and writing…
Descriptors: Foreign Countries, Error Analysis (Language), English (Second Language), Second Language Learning
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Parlindungan Pardede; Ninuk Lustyantie; Ifan Iskandar – Journal of English Teaching, 2023
Over the last decades, applied linguistics and language teaching/learning have investigated language errors committed by learners for both diagnostic and prognostic purposes. Initially, error analysis was conducted manually and involved a limited number of corpus. However, computer software advancement has facilitated much larger amounts of data…
Descriptors: Error Analysis (Language), English (Second Language), Second Language Learning, Second Language Instruction
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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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Lei, Jiun-Iung – English Language Teaching, 2020
While Automated Writing Evaluation (AWE) can perform an error diagnosis (Chen & Cheng, 2008), previous studies used to exclude it from the process of error analysis. This study aimed to examine the reactions of Grammarly Premium towards a group of night school students' English writings at a Taiwanese technical university. The participants of…
Descriptors: Writing Evaluation, Computer Software, Error Analysis (Language), Second Language Learning
Ekaterina Tabenkina – ProQuest LLC, 2023
The present project is a research-based and practice-tested online synchronous curriculum for English language learners with the Russian language mother tongue. The curriculum's theoretical component is grounded in Vygotsky's, Leont'ev', and Engestrom's "Cultural Historical Activity Theory" as well as in scholarly papers on the influence…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Foreign Countries
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Pratiwi, Damar Isti; Puspitasari, Armyta; Fikria, Ainun – TESL-EJ, 2023
While writing has evolved away from the conventional method of using pens and paper in favor of digital tools (Li et al., 2019), English teachers continue to face difficulties in teaching writing. This study shows how mind-mapping and the program, Writeabout, can be merged for online writing classes in English for Specific Purposes (ESP)…
Descriptors: Writing Instruction, Teaching Methods, Cognitive Mapping, Computer Assisted Instruction
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Rahayu, Endang Yuliani; Soepriatmadji, Liliek; Purwanto, Sugeng – English Language Teaching, 2022
In EFL teaching, it has been theorized that intelligibility can be achieved by relative closeness of oral performance to the standard of EFL proficiency. The current study sought to investigate the position of interlanguage performance of EFL college students in terms of intelligibility of the language product (Speaking). Ten students' Mid…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Language Proficiency
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Olney, Andrew M. – Grantee Submission, 2021
This paper explores a general approach to paraphrase generation using a pre-trained seq2seq model fine-tuned using a back-translated anatomy and physiology textbook. Human ratings indicate that the paraphrase model generally preserved meaning and grammaticality/fluency: 70% of meaning ratings were above 75, and 40% of paraphrases were considered…
Descriptors: Translation, Language Processing, Error Analysis (Language), Grammar
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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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Behrens, Susan J.; Chirinos, Yoshivel; Spencer, Marisa; Spradley, Sonya – NADE Digest, 2016
Utilizing the framework of educational linguistics, we investigate ways to foster greater awareness of, and facility with, academic English for educators and students across disciplines by maximizing the popularity of language-related software packages, applications and websites, those already commonly found in and out of the classroom. Our work…
Descriptors: Academic Discourse, Computer Software, Metalinguistics, Web Sites
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Chukharev-Hudilainen, Evgeny; Saricaoglu, Aysel – Computer Assisted Language Learning, 2016
Expressing causal relations plays a central role in academic writing. While it is important that writing instructors assess and provide feedback on learners' causal discourse, it could be a very time-consuming task. In this respect, automated writing evaluation (AWE) tools may be helpful. However, to date, there have been no AWE tools capable of…
Descriptors: Discourse Analysis, Feedback (Response), Undergraduate Students, Accuracy
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Amaral, Luiz A.; Meurers, W. Detmar – CALICO Journal, 2009
Error diagnosis in ICALL typically analyzes learner input in an attempt to abstract and identify indicators of the learner's (mis)conceptions of linguistic properties. For written input, this process usually starts with the identification of tokens that will serve as the atomic building blocks of the analysis. In this paper, we discuss the…
Descriptors: Grammar, Computer Assisted Instruction, Identification, Error Analysis (Language)
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