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Hassanzadeh, Mohammad; Fotoohnejad, Samira – Journal of Computer Assisted Learning, 2021
Considering the prominence attached to written corrective feedback (WCF) within the domain of second/foreign language (L2) acquisition, automated writing evaluation (AWE) tools have steadily gained ground over the last two decades. The current study was an attempt to investigate the extent incorporating an AWE program, known as Criterion®, within…
Descriptors: Program Implementation, Automation, Writing Evaluation, Writing Instruction
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Elif Sari; Turgay Han – Journal of Computer Assisted Learning, 2024
Background: With the growing trend of integrating technology into teaching environments, using Automated Writing Evaluation (AWE) in writing instruction has been extensively studied over the last two decades. The studies on AWE mostly investigated its impact on students' writing proficiencies and revealed conflicting results. However, very few…
Descriptors: Writing Evaluation, Second Language Learning, Second Language Instruction, English (Second Language)
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Sahin Kizil, Aysel – Journal of Computer Assisted Learning, 2023
Background: Data-driven learning (DDL) has been regarded as one of the promising approaches that could effectively enhance writing performance of English as a foreign language (EFL) learners. Although extensive research has been conducted on the use of DDL in developing various aspects of writing skill, there exist only few studies to date that…
Descriptors: Learning Analytics, English (Second Language), Second Language Learning, Second Language Instruction
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Wang, Y.; Harrington, M.; White, P. – Journal of Computer Assisted Learning, 2012
This paper introduces "CTutor", an automated writing evaluation (AWE) tool for detecting breakdowns in local coherence and reports on a study that applies it to the writing of Chinese L2 English learners. The program is based on Centering theory (CT), a theory of local coherence and salience. The principles of CT are first introduced and…
Descriptors: Foreign Countries, Educational Technology, Expertise, Feedback (Response)