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Adnane Ez-zizi; Dagmar Divjak; Petar Milin – Language Learning, 2024
Since its first adoption as a computational model for language learning, evidence has accumulated that Rescorla-Wagner error-correction learning (Rescorla & Wagner, 1972) captures several aspects of language processing. Whereas previous studies have provided general support for the Rescorla-Wagner rule by using it to explain the behavior of…
Descriptors: Error Correction, Second Language Learning, Second Language Instruction, Gender Differences
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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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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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Ranalli, Jim – Computer Assisted Language Learning, 2018
Automated written corrective feedback (AWCF) has qualities that distinguish it from teacher-provided WCF and potentially undermine claims about its value for L2 student writers, including disparities in the amounts of useful information it provides across error types and the fact that inaccuracies in error-flagging must be anticipated. It remains…
Descriptors: Error Correction, Feedback (Response), Computer Assisted Instruction, Second Language Learning
Tokdemir Demirel, Elif; Kazazoglu, Semin – Online Submission, 2015
This study reports on the results of classroom research investigating the effects of using data-driven learning methods by students in revising their writing errors. The main purpose of the study is to examine to what extent is consulting a corpus effective in correcting lexical errors in their writing. It has been found in previous research that…
Descriptors: Computational Linguistics, Second Language Learning, Second Language Instruction, Teaching Methods
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Gao, Zhao-Ming – Computer Assisted Language Learning, 2011
Previous studies on self-correction using corpora involve monolingual concordances and intervention from instructors such as marking of errors, the use of modified concordances, and other simplifications of the task. Can L2 learners independently refine their previous outputs by simply using a parallel concordancer without any hints about their…
Descriptors: Translation, Pretests Posttests, Guidelines, English (Second Language)
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Bradley, Linda, Ed.; Thouësny, Sylvie, Ed. – Research-publishing.net, 2012
For the first time, the annual conference of the European Association for Computer-Assisted Language Learning (EUROCALL) took place in Sweden. The conference took place at the Faculty of Education on historic ground on the old fortification walls of Carolus Dux from the 17th century right in the centre of the city. This year's host comprised the…
Descriptors: Second Language Instruction, Second Language Learning, Computer Assisted Instruction, Teaching Methods