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Showing 46 to 60 of 619 results Save | Export
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Li, Juan; Jiang, Hongquan; Shang, Aihua; Chen, Jingli – Computer Assisted Language Learning, 2021
Associative learning strategy (ALS) is an important means of acquiring vocabulary--especially in L2 learning. This study proposes a method to identify the associative learning mechanism based on complex network theory. First, a distributed association strategy (DAS) for the associative learning of L2 learners based on distributed language learning…
Descriptors: Associative Learning, Second Language Learning, Vocabulary, Learning Strategies
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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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Mandana Rohollahzadeh Ebadi – Computer Assisted Language Learning, 2025
Drawing on Mayer's Cognitive Theory of Multimedia Learning, the present study aims to examine the effectiveness of technology-mediated teaching vocabulary in the form of multimedia glosses on EFL learners' depth and breadth of lexical knowledge. The study was conducted with 91 male and female undergraduate students at a lower-intermediate level of…
Descriptors: Vocabulary Development, Undergraduate Students, Females, Comparative Analysis
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Soyoof, Ali; Reynolds, Barry Lee; Vazquez-Calvo, Boris; McLay, Katherine – Computer Assisted Language Learning, 2023
As technology has advanced, so have opportunities for language socialization and practice. This reciprocal relationship has resulted in the emergence of a subfield of Computer Assisted Language Learning (CALL): Informal Digital Learning of English (IDLE). IDLE has manifested in various forms, including the more notable extramural and…
Descriptors: Informal Education, Second Language Instruction, Second Language Learning, English (Second Language)
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Roohani, Ali; Heidari Vincheh, Maryam – Computer Assisted Language Learning, 2023
Mobile-assisted language learning (MALL), which provides access to learning without the constraints of place and time, is worthy of exploration for pedagogical purposes. Given the use of gaming applications and social media as potential instructional methods for MALL, this study investigated the effect of these two methods, along with traditional…
Descriptors: Educational Technology, Telecommunications, Handheld Devices, Game Based Learning
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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
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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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Raniya Abdullah Alsehibany; Safaa M. Abdelhalim – Computer Assisted Language Learning, 2025
In the past two decades, corpora have been proposed as valuable computer-assisted tools for teaching and learning academic writing in English at the university level. This article reports on an empirical study that sought to examine the effectiveness of direct corpus consultation in overcoming vocabulary errors in academic writing. This study is…
Descriptors: Undergraduate Students, Majors (Students), English (Second Language), Second Language Learning
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Kruk, Mariusz; Pawlak, Miroslaw – Computer Assisted Language Learning, 2023
The paper presents the results of a quasi-experimental study which was conducted with a view to determining the effect of an intervention in the form of the application of teacher-designed Internet-based resources (i.e., websites, podcasts, movie clips) that students could use autonomously on the development of pronunciation of the English regular…
Descriptors: Pronunciation Instruction, Second Language Learning, Second Language Instruction, English (Second Language)
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Barrett, Neil E.; Liu, Gi-Zen; Wang, Hei-Chia – Computer Assisted Language Learning, 2022
This paper investigates English language learners' oral presentation needs, alongside students' and instructors' perceptions towards mobile seamless language learning. The findings will be used to develop a mobile-based learning environment. Interviews with both instructors and students were used to help build a Likert questionnaire which was…
Descriptors: Public Speaking, Oral Language, Performance, Electronic Learning
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Sun, Peijian Paul; Mei, Bing – Computer Assisted Language Learning, 2022
This study focuses on preservice Chinese-as-a-second/foreign-language (L2 Chinese) teachers with a theoretical perspective based on prior technology acceptance research in the educational context, to investigate factors influencing preservice L2 Chinese teachers' intention to use educational technology in their future classrooms. Six relevant…
Descriptors: Chinese, Second Language Instruction, Preservice Teachers, Language Teachers
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Peichin Chang; Pin-Ju Chen; Li-Ling Lai – Computer Assisted Language Learning, 2024
Machine Translation (MT) tools have advanced to a level of reliability such that it is now opportune to consider their place in language teaching and learning. Given their potential, the current study sought to engage EFL university sophomores in recursive editing afforded by Google Translate (GT) for one semester, and investigated (1) whether the…
Descriptors: Editing, Computer Software, Artificial Intelligence, Translation
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Yu-Fen Yang; Wen-Min Hsieh; Wing-Kwong Wong; Yi-Chun Hong; Siao-Cing Lai – Computer Assisted Language Learning, 2024
Foreign Language Anxiety (FLA) is considered a central affective factor influencing English as a Foreign Language (EFL) learning. This study thus developed an online simulation game to create a virtually situated learning environment for reducing EFL primary school students' FLA levels and improving their English vocabulary learning. A total of…
Descriptors: Foreign Countries, English (Second Language), Second Language Learning, Second Language Instruction
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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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Huang, Tzu-Hua; Wang, Lun-Zhu – Computer Assisted Language Learning, 2023
TPR (Total Physical Response) is a methodology for teaching foreign languages. In traditional TPR, teachers need to spend a considerable amount of time confirming the accuracy of students' movements, which results in a low-efficiency teaching process and affects the fairness of student learning. A motion sensing system can assess the accuracy of…
Descriptors: Artificial Intelligence, Second Language Learning, Second Language Instruction, Motion
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