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Tao, Yingxu; Zou, Bin – Computer Assisted Language Learning, 2023
Technological progress has enhanced classroom gamification in a number of learning contexts. Kahoot! as a digital game-based learning platform is being increasingly integrated into teaching environments to facilitate effective classroom learning. The research focused on Chinese students' perceptions of using Kahoot! in classroom teaching in order…
Descriptors: Student Attitudes, Educational Games, Audience Response Systems, English (Second Language)
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)
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
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)
Taichi Yamashita – Computer Assisted Language Learning, 2024
The present paper reports on the effectiveness and inclusiveness of human-delivered synchronous written corrective feedback (SWCF) in paired writing tasks. Replicating Yamashita, Study 2 and Study 3 each conducted a classroom-based quasi-experimental study in an English-as-a-Second-Language (ESL) writing program at an American university. In Study…
Descriptors: Synchronous Communication, Feedback (Response), Student Evaluation, Written Language
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)
Aloraini, Nouf; Cardoso, Walcir – Computer Assisted Language Learning, 2022
The literature on students' perceptions towards using Social Media (SM) for language learning reports mixed findings: while some studies indicate learners' positive perceptions of their use for academic purposes (e.g., Bani-Hani et al.), others suggest that learners' perceptions might vary due to their proficiency in the language (e.g., Gamble…
Descriptors: College Students, English Language Learners, Foreign Countries, Social Media
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
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
Zhai, Na; Ma, Xiaomei – Computer Assisted Language Learning, 2022
Automated writing evaluation (AWE) has been used increasingly to provide feedback on student writing. Previous research typically focused on its inter-rater reliability with human graders and validation frameworks. The limited body of research has only discussed students' attitudes or perceptions in general. A systematic investigation of the…
Descriptors: Automation, Writing Evaluation, Feedback (Response), College Students
Jingjing Zhu; Xi Zhang; Jian Li – Computer Assisted Language Learning, 2024
Traditional L2 pronunciation teaching puts too much emphasis on explicit phonological knowledge ('knowing that') rather than on procedural knowledge ('knowing how'). The advancement of mobile-assisted language learning (MALL) offers new opportunities for L2 learners to proceduralize their declarative articulatory knowledge into production skills…
Descriptors: Artificial Intelligence, Technology Uses in Education, Pronunciation Instruction, Second Language Instruction
Kiliçkaya, Ferit – Computer Assisted Language Learning, 2022
Although a plethora of research has been conducted on written corrective feedback and timing of feedback in various teaching and learning contexts, there is a paucity of research on learners' preferences regarding different online written corrective feedback. Such a lacuna becomes prominent in EFL contexts, especially in grammar classes, where…
Descriptors: Preservice Teachers, Language Teachers, Electronic Learning, Written Language
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)

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