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Tanjun Liu; Dana Gablasova – Computer Assisted Language Learning, 2025
Collocations, a crucial component of language competence, remain a challenge for L2 learners across all proficiency levels. While the data-driven learning (DDL) approach has shown great potential for collocation learning from a shorter-term perspective, this study investigates its effectiveness in the long term, examining both linguistic gains and…
Descriptors: Phrase Structure, Learning Analytics, English (Second Language), Second Language Instruction
Cheng-Yueh Jao; Hui-Chin Yeh; Wan-Rou Huang; Nian-Shing Chen – Computer Assisted Language Learning, 2024
While previous studies have focused on the outcomes of using dubbing apps to foster learner's development of English-speaking ability, this study, grounded in cognitive apprenticeship (CA), is an investigation of the learning processes, which included modeling, coaching, scaffolding, articulation, reflection, and exploration, involved in the use…
Descriptors: Video Technology, Audiovisual Aids, Audio Equipment, Translation
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
Mark Feng Teng – Computer Assisted Language Learning, 2025
The present study aims to examine incidental vocabulary learning from different genres of captioned videos while considering frequency, vocabulary knowledge, comprehension, and working memory. A total of 210 learners who learn English as a foreign language (EFL) were assigned to 6 treatment conditions that differed in terms of video genres…
Descriptors: Incidental Learning, Vocabulary Development, Recall (Psychology), Second Language Learning
Jun Lei; Qian Zhang – Computer Assisted Language Learning, 2025
This article reports on the results of an investigation into what matters to learners of language Massive Open Online Courses (LMOOCs). The study conducted content and sentiment analyses of learner reviews of LMOOCs to investigate the key themes/subthemes in learner reviews and learners' emotional tendencies in the themes/subthemes as well as…
Descriptors: MOOCs, Second Language Instruction, Second Language Learning, College Students
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
Xin An; Ching Sing Chai; Yushun Li; Ying Zhou; Bingyu Yang – Computer Assisted Language Learning, 2025
To address the emerging trend of language learning with Artificial Intelligence (AI), this study explored junior and senior high school students' behavioral intentions to use AI in second language (L2) learning, and the roles of related technological, social, and motivational factors. An eight-factor survey was constructed using a 5-point Likert…
Descriptors: Educational Trends, Trend Analysis, Second Language Learning, Second Language Instruction
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
Zeng, Shuang; Zhang, Jingjing; Gao, Ming; Xu, Kate M.; Zhang, Jiang – Computer Assisted Language Learning, 2022
Learning analytics (LA) has the potential to generate new insights into the complexities of learning behaviours in language massive open online courses (LMOOCs). In LA, the collective attention model takes an ecological system view of the dynamic process of unequal participation patterns in online and flexible learning environments. In this study,…
Descriptors: Learning Analytics, MOOCs, Oral Language, English (Second Language)
Jaeho Jeon – Computer Assisted Language Learning, 2024
Professionals within the field of language learning have predicted that chatbots would provide new opportunities for the teaching and learning of language. Despite the assumed benefits of utilizing chatbots in language classrooms, such as providing interactional chances or helping to create an anxiety-free atmosphere, little is known about…
Descriptors: Computer Assisted Instruction, Artificial Intelligence, Learning Analytics, Computer Software
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
Cucchiarini, Catia; Hubers, Ferdy; Strik, Helmer – Computer Assisted Language Learning, 2022
Idiomatic expressions like "hit the road" or "turn the tables" are known to be problematic for L2 learners, but research indicates that learning L2 idiomatic language is important. Relatively few studies, most of them focusing on English idioms, have investigated how L2 idioms are actually acquired and how this process is…
Descriptors: Second Language Learning, Second Language Instruction, Computer Assisted Instruction, Teaching Methods
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; Xiao, Wei – Computer Assisted Language Learning, 2021
Although digital game-based vocabulary learning (DGBVL) has attracted considerable attention, factors attributing to the facilitative effects of DGBVL have not yet been satisfactorily understood. To this end, under the theoretical framework of flow theory, this study investigates the effects of flow experiences on Chinese…
Descriptors: Second Language Learning, Second Language Instruction, English (Second Language), Feedback (Response)

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