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Aljohani, Nouf Jazaa – Asian-Pacific Journal of Second and Foreign Language Education, 2022
In this research study, unlike previous studies that have examined the advantages of peer review for low proficiency students, uses a longitudinal action mixed methods design is used to explore the impact of peer review on the academic writing of students with low English proficiency. The format was a longitudinal action study, which analyzed the…
Descriptors: Longitudinal Studies, Peer Evaluation, Writing Evaluation, Action Research
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
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
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
Yoon, Chae Won; Chon, Yuah V. – English Teaching, 2022
To investigate L2 adolescent learners' use of machine translation (MT), an MT error correction (EC) test was developed, based on the analysis of MT errors arising from translating the learners' L1 of middle school EFL textbooks. Learners were also asked to report on their use of MT EC strategies on the EC task. Results indicated that…
Descriptors: Translation, Error Analysis (Language), Error Patterns, Language Proficiency
Can, Seçkin; Daloglu, Aysegül – Journal on English Language Teaching, 2022
This study aims to investigate which types of errors lead to which types of corrective feedback and their distribution in university preparatory school speaking classes. Discourse analytic principles were used to analyze the learners' errors and types of oral corrective feedback in communicatively oriented speaking classes. The frequency and…
Descriptors: Oral Language, Error Correction, College Preparation, Video Technology
Inpanich, Pipittaporn; Somphong, Monnipha – English Language Teaching, 2022
This study aimed to investigate the effects of the integration of indirect feedback and concordances on improving grammatical accuracy in Thai EFL undergraduate students' writing and to explore the students' perceptions toward the intervention. Thirty third-year undergraduate students who studied at a government university in Bangkok were the…
Descriptors: Writing Instruction, English (Second Language), Second Language Learning, Second Language Instruction
Gholami, Leila – Foreign Language Annals, 2021
Research on incidental focus on form (FonF) has established associations among the nature of learner error, corrective feedback (CF), and effectiveness of CF measured through uptake. In this line of research, the analysis of learner error has been limited to errors with grammar, pronunciation, vocabulary, and spelling (nonformulaic). Consequently,…
Descriptors: Grammar, Phrase Structure, Second Language Learning, Second Language Instruction
Virlan, Ayse Yilmaz – Journal of English Teaching, 2022
In second language teaching and learning, making errors is inevitable as language learning requires a lot of cognitive effort and concentration on the part of learners. Understanding the types and frequencies of student errors is, therefore, an important issue for ESL and EFL teachers to determine how students can be helped to improve their skills…
Descriptors: Teaching Methods, Error Correction, Cognitive Ability, Second Language Instruction
González-Cruz, Belén; Cerezo, Lourdes; Nicolás-Conesa, Florentina – Studies in Second Language Learning and Teaching, 2022
This study compared the effects of computer-mediated (CM) versus pen-and-paper (P&P) writing on written accuracy and feedback processing in tasks written and rewritten collaboratively following a pedagogical treatment in two intact authentic classrooms. The study involved 32 secondary education low-proficiency English-as-a-foreign-language…
Descriptors: Second Language Learning, Second Language Instruction, Accuracy, Feedback (Response)
Pangaribuan, Tagor; Haddina, Elisa; Manik, Sondang – English Language Teaching, 2018
This research deals with the students' error in using conjunction (because, since, as, in case) in the sentences. Conjunction is very important for the learners to develop a skill in grammar. And grammar is the most important part of language for anyone. Should be first understood before being able to construct sentences, rules based on the…
Descriptors: Error Analysis (Language), Sentences, Sentence Structure, Form Classes (Languages)
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
Demirel, Elif Tokdemir – English Language Teaching, 2017
The present study aims to explore Turkish EFL students' major writing difficulties by analyzing the frequent writing errors in academic essays. Accordingly, the study examined errors in a corpus of 150 academic essays written by Turkish EFL students studying at the Department of English Language and Literature at a public university in Turkey. The…
Descriptors: Foreign Countries, Error Correction, Error Analysis (Language), English (Second Language)
Kodura, Malgorzata – Research-publishing.net, 2019
The aim of this paper is to make a point in a discussion whether and to what extent it is advisable to incorporate language instruction activities into the translation course. Although translation competence is often perceived as a set of sub-competencies that always includes language skills, regardless of the theoretical framework adopted, it is…
Descriptors: Modern Languages, Second Language Learning, Second Language Instruction, Teaching Methods
Kut, Begüm – International Online Journal of Education and Teaching, 2018
The objective of this study is to investigate the common errors of L2 learners in a Turkish university setting where they have to learn L2 and pass a B1 level exam in order to be faculty students. The study aims at identifying what types of errors the learners do, what the possible determining factors at the background are and how they can…
Descriptors: Second Language Learning, Second Language Instruction, English (Second Language), Foreign Countries