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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
Hsu, Hsiu-Chen; Lo, Yun-Fang – Language Learning & Technology, 2018
This study investigated the effect of wiki-mediated collaborative writing on the development of learners' individual writing in a second language (L2). Participants were 52 learners of English as a foreign language enrolled in two intact junior writing classes at a Taiwanese university. One class was assigned to be a wiki-collaborative writing…
Descriptors: Collaborative Writing, Second Language Learning, Second Language Instruction, Pretests Posttests
Chen, Zhenzhen; Chen, Weichao; Jia, Jiyou; Le, Huixiao – Language Learning & Technology, 2022
Despite the growing interest in investigating the pedagogical application of Automated Writing Evaluation (AWE) systems, studies on the process of AWE-supported writing are still scant. Adopting activity theory as the framework, this qualitative study aims to examine how students incorporated AWE feedback into their writing in an English as a…
Descriptors: Writing Instruction, Writing Processes, Teaching Methods, Learning Strategies
Shi, Zhan; Liu, Fengkai; Lai, Chun; Jin, Tan – Language Learning & Technology, 2022
Automated Writing Evaluation (AWE) systems have been found to enhance the accuracy, readability, and cohesion of writing responses (Stevenson & Phakiti, 2019). Previous research indicates that individual learners may have difficulty utilizing content-based AWE feedback and collaborative processing of feedback might help to cope with this…
Descriptors: Writing Instruction, Writing Evaluation, Feedback (Response), Accuracy
Matthews, Joshua; Wijeyewardene, Ingrid – Language Learning & Technology, 2018
Despite the current potential to use computers to automatically generate a large range of text-based indices, many issues remain unresolved about how to apply these data in established language teaching and assessment contexts. One way to resolve these issues is to explore the degree to which automatically generated indices, which are reflective…
Descriptors: Correlation, Robotics, Second Language Learning, Second Language Instruction
Liu, Sha; Yu, Guoxing – Language Learning & Technology, 2022
This study used eye-tracking, in combination with stimulated recalls and reflective journals, to investigate L2 learners' engagement with automated feedback and the impact of feedback explicitness and accuracy on their engagement. Twenty-four Chinese EFL learners revised their writing through Write & Improve with Cambridge, a new automated…
Descriptors: Eye Movements, Second Language Learning, Second Language Instruction, Feedback (Response)
Chen, Chi-Fen Emily; Cheng, Wei-Yuan Eugene – Language Learning & Technology, 2008
Automated writing evaluation (AWE) software is designed to provide instant computer-generated scores for a submitted essay along with diagnostic feedback. Most studies on AWE have been conducted on psychometric evaluations of its validity; however, studies on how effectively AWE is used in writing classes as a pedagogical tool are limited. This…
Descriptors: Feedback (Response), Writing Evaluation, Instructional Effectiveness, Foreign Countries
