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Wenting Chen; Jianwu Gao – Computer Assisted Language Learning, 2024
While the importance of the peer feedback in second or foreign language (L2 or FL) classrooms in higher education has been increasingly recognized, empirical research on discussing peer feedback literacy from the perspective of community-based academic writing is very much in its infancy. Informed by the Community of Inquiry (CoI) framework, this…
Descriptors: Inquiry, Community Education, Feedback (Response), Computer Mediated Communication
Turgay Han; Elif Sari – Computer Assisted Language Learning, 2024
Feedback is generally regarded as an integral part of EFL writing instruction. Giving individual feedback on students' written products can lead to a demanding, if not insurmountable, task for EFL writing teachers, especially in classes with a large number of students. Several Automated Writing Evaluation (AWE) systems which can provide automated…
Descriptors: Foreign Countries, Automation, Feedback (Response), English (Second Language)
W. A. Piyumi Udeshinee; Ola Knutsson; Sirkku Männikkö Barbutiu; Chitra Jayathilake – Computer Assisted Language Learning, 2024
The discussion on the dynamic assessment (DA) -- a combination of assessment and instruction -- and regulatory scales from implicit to explicit corrective feedback (CF) is relatively new in the CALL context. Applying the notions of Sociocultural Theory, Zone of Proximal Development (ZPD) and Mediation, the present study examines how a DA-based…
Descriptors: Synchronous Communication, Evaluation Methods, Feedback (Response), English (Second Language)
Mengtian Chen – Computer Assisted Language Learning, 2024
This article discusses whether digital visual and audio feedback in learners' own voices improves their perception and production of lexical tones in Chinese as a foreign language. Forty-four beginners participated in a four-week training focused on the pronunciation of Mandarin Chinese tones at the word level. Half received digital feedback…
Descriptors: Feedback (Response), Computer Assisted Instruction, Pronunciation Instruction, Mandarin Chinese
Link, Stephanie; Mehrzad, Mohaddeseh; Rahimi, Mohammad – Computer Assisted Language Learning, 2022
Recent years have witnessed an increasing interest in the use of automated writing evaluation (AWE) in second language writing classrooms. This increase is partially due to the belief that AWE can assist teachers by allowing them to devote more feedback to higher-level (HL) writing skills, such as content and organization, while the technology…
Descriptors: Automation, Writing Evaluation, Feedback (Response), Revision (Written Composition)
Zhe Zhang; Ken Hyland – Computer Assisted Language Learning, 2025
Research on second language (L2) writing suggests that student engagement with automated writing evaluation (AWE) feedback is influenced by various individual and contextual factors. Little attention, however, has been given to the role that students' digital literacy can play in this process. Increasingly, digital literacy is becoming…
Descriptors: Writing Evaluation, Feedback (Response), Second Language Learning, Second Language Instruction
Behice Ceyda Cengiz; Amine Hatun Atas – Computer Assisted Language Learning, 2025
This research investigates the correlation between online self-regulation (OSR) and in class co-regulation (CR) within a flipped EFL (English as a Foreign Language) writing classroom. Employing a mixed methods approach, the study amalgamates descriptive and correlational quantitative data with qualitative interview data. Participants consisted of…
Descriptors: English (Second Language), Second Language Instruction, Second Language Learning, Correlation
Bin Zou; Qinglang Lyu; Yining Han; Zijing Li; Weilei Zhang – Computer Assisted Language Learning, 2025
Adapted from the Technology Acceptance Model (TAM), the Integrated Model of Technology Acceptance (IMTA) has been used to examine the perceptions and acceptance of computer-assisted language learning (CALL), such as online learning, mobile learning, and learning management systems. However, whether IMTA can be applied to empirical research on…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Artificial Intelligence
Pham, Ha Thi Phuong – Computer Assisted Language Learning, 2022
This study investigates how two feedback forms and sequences influence peer feedback and revision. The two feedback forms included: written asynchronous computer-mediated communication (hereafter WACMC) in Google Docs and traditional oral face-to-face interaction (hereafter OF2F). These two forms were used in two sequences: WACMC followed by OF2F…
Descriptors: Feedback (Response), English (Second Language), Writing (Composition), Peer Evaluation
Yi-chen Chen – Computer Assisted Language Learning, 2024
Public speaking is considered the most anxiety-provoking speaking activity for English as a foreign language (EFL) learner. While traditional lecture-based classrooms hinder EFL learners' constant practice and frequent interaction due to large class sizes and limited time, recent developments in technology, including Artificial Intelligence (AI),…
Descriptors: Computer Assisted Instruction, Teaching Methods, Oral Language, Second Language Learning
Conijn, Rianne; Martinez-Maldonado, Roberto; Knight, Simon; Buckingham Shum, Simon; Van Waes, Luuk; van Zaanen, Menno – Computer Assisted Language Learning, 2022
Current writing support tools tend to focus on assessing final or intermediate products, rather than the writing process. However, sensing technologies, such as keystroke logging, can enable provision of automated feedback during, and on aspects of, the writing process. Despite this potential, little is known about the critical indicators that can…
Descriptors: Automation, Feedback (Response), Writing Evaluation, Learning Analytics
Guo, Qian; Feng, Ruiling; Hua, Yuanfang – Computer Assisted Language Learning, 2022
AWCF can facilitate academic writing development, especially for novice writers of English as a foreign language (EFL). Existing AWCF studies mainly focus on teacher and learner perceptions; fewer have investigated the error-correction effect of AWCF and factors related to the effect. Especially lacking is research on how successfully students can…
Descriptors: Error Correction, Feedback (Response), English (Second Language), Second Language Learning
Ko, Myong-Hee – Computer Assisted Language Learning, 2019
The present study examined students' perspectives on using smartphones and social media to fill a lacuna in mobile-assisted feedback in L2 vocabulary learning. As part of a vocabulary-building activity, 208 undergraduate students in Korea drafted sentences incorporating target vocabulary taught by their instructor and uploaded their sentences to a…
Descriptors: Handheld Devices, Telecommunications, Social Media, Vocabulary Development
Youngs, Bonnie L.; Prakash, Akhil; Nugent, Rebecca – Computer Assisted Language Learning, 2018
Logged tracking data for online courses are generally not available to instructors, students, and course designers and developers, and even if these data were available, most content-oriented instructors do not have the skill set to analyze them. Learning analytics, mined from logged course data and usually presented in the form of learning…
Descriptors: Online Courses, French, Second Language Learning, Second Language Instruction
Ma, Qing – Computer Assisted Language Learning, 2020
This study investigated how one type of learner-generated information and content, i.e. inter-group peer online feedback, provided on a wiki writing assignment for an English for Academic Purposes (EAP) course, could contribute to student L2 writing. Using a mixed method approach, more than 1000 entries of online peer comments were collected,…
Descriptors: English for Academic Purposes, Second Language Learning, Second Language Instruction, Collaborative Writing
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