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Chunping Zheng; Xu Chen; Huayang Zhang; Ching Sing Chai – Language Learning & Technology, 2024
This quasi-experimental research investigates the employment of a formative assessment platform aided by artificial intelligence in an English public speaking course. The platform integrates deep learning, automatic speech recognition, and automatic writing evaluation. It provides automated assessment and immediate feedback on speakers' public…
Descriptors: Peer Evaluation, Comparative Analysis, Feedback (Response), Self Evaluation (Individuals)
Zhang, Hong; Torres-Hostench, Olga – Language Learning & Technology, 2022
The main purpose of this study is to evaluate the effectiveness of Machine Translation Post-Editing (MTPE) training for FL students. Our hypothesis was that with specific MTPE training, students will able to detect and correct machine translation mistakes in their FL. Training materials were developed to detect six typical mistakes from Machine…
Descriptors: Computational Linguistics, Translation, Second Language Learning, Second Language Instruction
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
Gao, Jianwu; Ma, Shuang – Language Learning & Technology, 2019
This study investigated whether the effect of two forms of computer-automated metalinguistic corrective feedback in drills transferred to subsequent writing tasks. The English simple past tense, a learned structure, was selected as the target structure. Participants included 117 intermediate learners of English as a foreign language assigned to…
Descriptors: Feedback (Response), Metalinguistics, Computer Assisted Instruction, Drills (Practice)
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)
Xu, Cuiqin; Ding, Yanren – Language Learning & Technology, 2014
The advance of computer input log and screen-recording programs over the last two decades has greatly facilitated research into the writing process in real time. Using Inputlog 4.0 and Camtasia 6.0 to record the writing process of 24 Chinese EFL writers in an argumentative task, this study explored L2 writers' pausing patterns in computer-assisted…
Descriptors: Writing Processes, Computer Assisted Instruction, Writing Assignments, Persuasive Discourse