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Direct linkGodwin-Jones, Robert – Language Learning & Technology, 2022
In recent years, advances in artificial intelligence (AI) have led to significantly improved, or in some cases, completely new digital tools for writing. Systems for writing assessment and assistance based on automated writing evaluation (AWE) have been available for some time. That is the case for machine translation as well. More recent are…
Descriptors: Writing Instruction, Artificial Intelligence, Feedback (Response), Writing Evaluation
Clark, Eve V. – Discourse Processes: A Multidisciplinary Journal, 2020
In this article, I examine how repairs in adult-child conversations guide children's acquisition of language. Children make unprompted self-repairs to their utterances. They also respond to prompts for repair, whether open ("Hm?," "What?") or restricted ("You hid what?"), and to restricted offers (Child: "I…
Descriptors: French, Verbs, Semitic Languages, Native Language
Sepehrinia, Sajjad; Nemati, Majid; Khomijani Farahani, Ali Akbar – Language Learning Journal, 2019
Among focus-on-form studies, oral corrective feedback (CF) has probably received the greatest attention. The majority of studies in this area appear to support a positive role for oral CF in improving interlanguage development. However, theorists adopting a nativist view of second language acquisition continue to question its effectiveness. The…
Descriptors: Oral Language, Interlanguage, Syntax, Error Correction
Download full textAltamimi, Dheif Allah Hussain Falah; Ab Rashid, Radzuwan; Elhassan, Yasir Mohamed Mohamed – English Language Teaching, 2018
The purpose of this review paper is to identify the core spelling errors in Arabic and Non Arabic Contexts. The most common difficulty that Arab learners may face during their English writing is correct spelling, for many different reasons such as the interference between English and Arabic language and the irregularity of the English language…
Descriptors: College Students, Spelling, Error Patterns, Error Correction
Hauser, Eric – Modern Language Journal, 2017
Within the framework of Conversation Analysis for Second Language Acquisition (CA-SLA), this study uses learning behavior tracking (LBT) (Markee, 2008) with longitudinal data to investigate word learning by one adult second language (L2) user of English. The adult is a first language (L1) user of Japanese with limited proficiency in English. Data…
Descriptors: Discourse Analysis, English (Second Language), Japanese, Native Language
