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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
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
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
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
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
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
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
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
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
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
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
Yang, Juan; Thomas, Michael S. C.; Qi, Xiaofei; Liu, Xuan – Computer Assisted Language Learning, 2019
From a psycholinguistic perspective of view, there are many cognitive differences that matter to individuals' second-language acquisition (SLA). Although many computer-assisted tools have been developed to capture and narrow the differences among learners, the use of these strategies may be highly risky because changing the environments or the…
Descriptors: Foreign Countries, Cognitive Ability, Phonological Awareness, English Teachers
Goh, Tiong-Thye; Sun, Hui; Yang, Bing – Computer Assisted Language Learning, 2020
This study investigates the extent to which microfeatures -- such as basic text features, readability, cohesion, and lexical diversity based on specific word lists -- affect Chinese EFL writing quality. Data analysis was conducted using natural language processing, correlation analysis and stepwise multiple regression analysis on a corpus of 268…
Descriptors: Essays, Writing Tests, English (Second Language), Second Language Learning
Zou, Bin; Li, Hui; Li, Jiaying – Computer Assisted Language Learning, 2018
Mobile apps are broadly used by students in and after class to improve their language skills. This study aimed to investigate how a curriculum app and a social communication app can be integrated into English language teaching and learning and what sorts of tasks can be employed to enhance learners' EFL learning. A curriculum app was created by…
Descriptors: Computer Assisted Instruction, English (Second Language), Second Language Learning, Second Language Instruction
Jiang, Wei; Eslami, Zohreh R. – Computer Assisted Language Learning, 2022
Although the effectiveness of computer-mediated collaborative writing (CMCW) is confirmed by many recent studies, only a few have investigated whether linguistic knowledge and writing skills learned through collaboration can be internalized and transferred to individual writing. This study uses a pre-and post-test design to investigate the impact…
Descriptors: Collaborative Writing, English (Second Language), Second Language Learning, Second Language Instruction
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