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Qing-Ke Fu; Di Zou; Haoran Xie; Gary Cheng – Computer Assisted Language Learning, 2024
Automated writing evaluation (AWE) plays an important role in writing pedagogy and has received considerable research attention recently; however, few reviews have been conducted to systematically analyze the recent publications arising from the many studies in this area. The present review aims to provide a comprehensive analysis of the…
Descriptors: Journal Articles, Automation, Writing Evaluation, 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
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
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)
Jianhua Zhang; Lawrence Jun Zhang – Computer Assisted Language Learning, 2024
This study mainly explored the effects of teacher feedback, peer feedback and automated feedback on the use of metacognitive strategies in EFL writing. Ninety-seven participants were recruited and divided into three groups, who received two months of feedback from teachers, peers and an automatic writing evaluation system, respectively, and then…
Descriptors: Feedback (Response), Metacognition, English (Second Language), Second Language Learning
Azizullah Mirzaei; Hanieh Shafiee Rad; Ebrahim Rahimi – Computer Assisted Language Learning, 2024
The Attention, Relevance, Confidence, and Satisfaction (ARCS) model provides a basis for integrating motivational dynamics and technological affordances into the design and implementation of instructions to maintain learner motivation and interest. Little attention has been paid to this potential in teaching the complex and often demotivating…
Descriptors: Flipped Classroom, English (Second Language), Second Language Learning, Second Language Instruction
Wang, Weiwei; Jiang, Lianjiang – Computer Assisted Language Learning, 2023
While social networking sites (SNSs) have attracted growing scholarly interest in uncovering L2 learners' participation within these sites, the impact of writing on SNSs upon students' writing performance and learner autonomy remains underexplored. This study reported on a college EFL writing course participated by two groups of Chinese first-year…
Descriptors: Personal Autonomy, Social Networks, Social Media, Computer Mediated Communication
Boning Lyu; Chun Lai – Computer Assisted Language Learning, 2024
Studies have explored how second language (L2) learners engage with peer feedback in instructional contexts. However, how learners engage in self-initiated and self-directed feedback practices beyond the classroom in online spaces is largely unknown. Informed by an ecological perspective, an in-depth exploration of the dynamics and underpinning…
Descriptors: Learner Engagement, Social Networks, Second Language Learning, Second Language Instruction
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
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
Loncar, Michael; Schams, Wayne; Liang, Jong-Shing – Computer Assisted Language Learning, 2023
The following review incorporates a systematic selection, coding, and analysis methodology in order to compile a corpus of empirical research studies that investigate the use of technology-mediated feedback in L2 writing contexts published from 2015-2019. Trends are identified by coding and quantitatively analyzing key parameters of the corpus,…
Descriptors: Research Reports, Writing Instruction, Feedback (Response), Technology Uses in Education
Tsai, Shu-Chiao – Computer Assisted Language Learning, 2022
This study investigates the effectiveness of using Google Translate as a translingual CALL tool in English as a Foreign Language (EFL) writing, keyed to the perceptions of both more highly proficient Chinese English major university students and less-proficient non-English majors. After watching a 5-minute passage from a movie, each cohort of…
Descriptors: Computer Assisted Instruction, Translation, Second Language Learning, Second Language Instruction
Li, Rui; Meng, Zhaokun; Tian, Mi; Zhang, Zhiyi; Ni, Chuanbin; Xiao, Wei – Computer Assisted Language Learning, 2019
Automated Writing Evaluation (AWE) has been widely applied in computer-assisted language learning (CALL) in China. However, little is known about factors that influence learners' intention to use AWE. To this end, by adding two external factors (i.e. computer self-efficacy and computer anxiety) to the technology acceptance model (TAM), we surveyed…
Descriptors: Foreign Countries, English (Second Language), Second Language Learning, Automation
Sarré, Cédric; Grosbois, Muriel; Brudermann, Cédric – Computer Assisted Language Learning, 2021
Corrective feedback (CF) can be provided to learners in different ways (explicit or implicit, focused or unfocused) and is the subject of major controversies in second language acquisition research. As no clear consensus has been reached so far about the most effective approach to CF with a view to fostering accuracy in second language (L2)…
Descriptors: Blended Learning, Comparative Analysis, Second Language Learning, Second Language Instruction
Chung, Eun Seon; Ahn, Soojin – Computer Assisted Language Learning, 2022
Many studies that have investigated the educational value of online machine translation (MT) in second language (L2) writing generally report significant improvements after MT use, but no study as of yet has comprehensively analyzed the effectiveness of MT use in terms of various measures in syntactic complexity, accuracy, lexical complexity, and…
Descriptors: Translation, Computational Linguistics, English (Second Language), Second Language Learning
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