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Showing 1 to 15 of 31 results Save | Export
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Pu Pu; Daniel Yu-Sheng Chang – Computer Assisted Language Learning, 2025
While blended learning has received scholarly attention in EFL contexts, little empirical research has investigated the effects of online input modes on learning achievement and attitudes. This study thus examined the effects of bimodal and multimodal online input on blended speaking instruction in a Chinese university. A quasi-experimental,…
Descriptors: Speech Communication, Blended Learning, Student Attitudes, Learning Processes
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Huiwan Zhang; Wei Wei; Yiqian Cao – Computer Assisted Language Learning, 2024
The role of computer-assisted language learning (CALL) in developing vocabulary knowledge has been investigated extensively in the field of English for Academic Purposes with positive outcomes. However, its implications for medical education, and specifically foreign languages for medical purposes, have not received much attention. This study…
Descriptors: Computer Assisted Instruction, Educational Technology, Technology Uses in Education, Medical Education
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Guangxiang Liu; Chaojun Ma; Jie Bao; Zhixin Liu – Computer Assisted Language Learning, 2025
Utilizing a structural equation modeling approach, this article aims to examine the dynamics between Informal Digital Learning of English (IDLE) and Intercultural Competence (ICC). Altogether, 1490 Chinese college students from different types of universities in China answered the self-developed and validated IDLE-ICC questionnaire. The results…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Intercultural Communication
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Yue Zhang; Guangxiang Liu – Computer Assisted Language Learning, 2024
Informal digital learning of English (IDLE) is an increasingly important subfield of inquiry in Computer-Assisted Language Learning (CALL) for its concentration on the language learning practices of the digital native EFL students in out-of-class contexts. Attention in mainstream research of IDLE has been directed to (meta)cognition, learning…
Descriptors: Informal Education, English (Second Language), Second Language Learning, Second Language Instruction
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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
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Zheng, Chunping; Wang, Lili; Chai, Ching Sing – Computer Assisted Language Learning, 2023
Although formative assessment has been recognized as an effective way for improving learning, scant attention has been paid to the specific design on the sequence of applying formative assessment practice in computer-assisted language learning (CALL). Even less emphasis has been devoted to the cognitive and affective outcomes of different orders…
Descriptors: Self Evaluation (Individuals), Peer Evaluation, Video Technology, Formative Evaluation
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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
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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
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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
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Yue Zhang; Guangxiang Leon Liu – Computer Assisted Language Learning, 2025
In Computer-assisted language learning (CALL), the relationship between learner background and classroom-based digital language learning has been widely studied; however, little attention has been directed to informal digital learning of English (IDLE), a crucial subdomain of inquiry of CALL. Building on our prior IDLE study, this explanatory…
Descriptors: Language Proficiency, English (Second Language), Second Language Instruction, Second Language Learning
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Guoyuhui Huang; Khe Foon Hew – Computer Assisted Language Learning, 2024
Over the past two decades, the Involvement Load Hypothesis (ILH) has become a popular buzzword in the field of Second Language Acquisition (SLA). Although applications of the ILH can improve students' learning of productive vocabulary, this effect appears to be transitory. Students' learning of productive vocabulary often fades over time, as shown…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, Vocabulary Development
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Zhang, Ruofei; Zou, Di; Xie, Haoran – Computer Assisted Language Learning, 2022
Spaced repetition has been widely implemented and examined in mobile-assisted word learning as an important learning strategy. However, the nature of spaced repetition by commercial word-learning apps and the factors leading to the favoured mobile-assisted spaced repetition have yet to be investigated in authentic contexts. In this study, we coded…
Descriptors: Computer Assisted Instruction, Teaching Methods, English (Second Language), Second Language Learning
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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
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Sallam, Marwan H.; Martín-Monje, Elena; Li, Yan – Computer Assisted Language Learning, 2022
This study aims to explore the current published research on Language Massive Open Online Courses (LMOOCs), outlining the types of papers, countries where studies were performed and institutions devoted to this field. Also, it intends to classify the reviewed literature following a general categorisation of MOOCs, and to identify the main trends…
Descriptors: Educational Research, Educational Trends, Second Language Learning, MOOCs
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Shadiev, Rustam; Yang, Meng-ke; Reynolds, Barry Lee; Hwang, Wu-Yuin – Computer Assisted Language Learning, 2022
In this study, the participants learned English as a foreign language (EFL) in the classroom and then worked on five learning tasks to apply their newly learned knowledge to unfamiliar environments. The participants took photos of people, objects, situations or scenarios and described them in detail using a mobile learning system. Familiarization…
Descriptors: English (Second Language), Second Language Learning, Second Language Instruction, Vocabulary Development
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