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Tzu-Yu Tai; Howard Hao-Jan Chen – Computer Assisted Language Learning, 2024
English speaking is considered the most difficult and anxiety-provoking language skill for EFL learners due to lack of access to authentic language use, fear of making mistakes, and peers' negative comments. With automatic speech recognition and natural language processing, intelligent personal assistants (IPAs) have potential in foreign language…
Descriptors: English (Second Language), Speech Communication, English Language Learners, Anxiety
Xue, Sijia; Churchill, Daniel – Computer Assisted Language Learning, 2022
The educational potential of mobile and social media technologies in combination is becoming increasingly salient with the advance of modern technology. However, there is a dearth in the research on educational use of mobile social media for language learning. This study adopted a qualitative single case study approach to investigate a language…
Descriptors: Second Language Learning, Second Language Instruction, Teaching Methods, Student Centered Learning
Awada, Ghada M.; Diab, Nuwar Mawlawi – Computer Assisted Language Learning, 2023
This study set out to examine which peer review, face-to-face given orally or online given in writing, is more effective in improving the overall argumentative writing achievement of English as a foreign language (EFL) university learners. The study utilized an experimental design and reported on one experiment including online peer review (OLPR)…
Descriptors: Peer Evaluation, Feedback (Response), English (Second Language), College Students
Nektaria-Efstathia Kourtali; Lais Borges – Computer Assisted Language Learning, 2024
Numerous studies have delved into the effects of interactional corrective feedback provided in the oral or written mode in the CALL environment (e.g.video-conferencing or text-based chat). Although previous research shows that several factors influence its effectiveness, a research area that merits more attention is the role of feedback timing…
Descriptors: Foreign Countries, Early Adolescents, English (Second Language), Second Language Learning
Outi Veivo; Maarit Mutta – Computer Assisted Language Learning, 2025
This study focuses on dialogue breakdowns that can occur in robot-assisted language learning (RALL). Our aim is to analyse how children use gaze to resolve these breakdowns, that is, interruptions in the interaction caused by the robot's inability to understand the children and react appropriately. Our corpus consists of 18 video filmed L2…
Descriptors: Robotics, Technology Uses in Education, Second Language Learning, Interaction
Yen-Jung Chen; Liwei Hsu; Shao-wei Lu – Computer Assisted Language Learning, 2024
It is well known that teachers' feedback plays an important role in students' learning, as it enhances learners' cognitive development; yet there has been little research on how positive feedback given in the form of emojis works in computer-assisted language learning (CALL) courses. In this study, an experiment was designed to clarify how English…
Descriptors: Visual Aids, English (Second Language), Second Language Learning, Feedback (Response)
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
Barrot, Jessie S. – Computer Assisted Language Learning, 2023
Despite the building up of research on the adoption of automated writing evaluation (AWE) systems, the differential effects of automated written corrective feedback (AWCF) on errors with different severity levels and gains across writing tasks remain unclear. Thus, this study fills in the vacuum by examining how AWCF through Grammarly affects…
Descriptors: Automation, Written Language, Error Correction, Feedback (Response)
Lee, Cynthia – Computer Assisted Language Learning, 2020
The aim of this article is to reveal the ways in which six 14- to 15-year-old second language (L2) learners, two each of high, mid, and low English proficiency levels were cognitively engaged in writing while using an automated content feedback program known as the Essay Critiquing System 2.0 in three out of five workshops in a Hong Kong secondary…
Descriptors: Adolescents, Automation, Feedback (Response), Computer Assisted Instruction
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)
Chen, Sherry Y.; Tseng, Yu-Fen – Computer Assisted Language Learning, 2021
We developed the Scaffolding English E-assessment Learning (SEEL), where instant feedback and scaffolding hints were provided, to facilitate students to acquire the knowledge of English grammar. On the other hand, an empirical study was conducted to investigate how cognitive styles (i.e. Holists vs. Serialists) affected learners' reactions to the…
Descriptors: Scaffolding (Teaching Technique), Computer Assisted Testing, English (Second Language), Second Language Learning
Muzakki Bashori; Roeland van Hout; Helmer Strik; Catia Cucchiarini – Computer Assisted Language Learning, 2024
Speaking skills generally receive little attention in traditional English as a Foreign Language (EFL) classrooms, and this is especially the case in secondary education in Indonesia. A vocabulary deficit and poor pronunciation skills hinder learners in their efforts to improve speaking proficiency. In the present study, we investigated the effects…
Descriptors: Computer Assisted Instruction, Teaching Methods, Audio Equipment, Video Technology
Dai, Yuanjun; Wu, Zhiwei – Computer Assisted Language Learning, 2023
Although social networking apps and dictation-based automatic speech recognition (ASR) are now widely available in mobile phones, relatively little is known about whether and how these technological affordances can contribute to EFL pronunciation learning. The purpose of this study is to investigate the effectiveness of feedback from peers and/or…
Descriptors: Educational Technology, Technology Uses in Education, Telecommunications, Handheld Devices
Ge, Zi-Gang – Computer Assisted Language Learning, 2022
This study aims to investigate the effectiveness of peer video feedback on adult e-learners' language learning. The participants were 60 first-year e-learning students majoring in telecommunications at an e-learning college in Beijing and participating in a 19-week English course. They were divided evenly into two groups with two peer feedback…
Descriptors: Video Technology, Feedback (Response), Peer Evaluation, Electronic Learning