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Direct linkShortt, Mitchell; Tilak, Shantanu; Kuznetcova, Irina; Martens, Bethany; Akinkuolie, Babatunde – Computer Assisted Language Learning, 2023
More than 300 million people use the gamified mobile-assisted language learning (MALL) application (app) Duolingo. The challenging tasks, reward incentives, systematic levels, and the ranking of users according to their achievements are just some of the elements that demonstrate strong gamification elements within this popular language learning…
Descriptors: Gamification, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
Zhi Quan; Lynn Grant; Darryl Hocking – Computer Assisted Language Learning, 2024
As a corpus-assisted method for language pedagogy, DDL (data-driven learning) may have the potential to enhance language exposure and promote active learner engagement. Concordancing, or KWIC (Key Words in Context), has been the traditional method used in DDL to retrieve numerous language examples, while the method has limitations with…
Descriptors: Language Patterns, Language Usage, Second Language Learning, English (Second Language)
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
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
Tai, Tzu-Yu; Chen, Howard Hao-Jan; Todd, Graeme – Computer Assisted Language Learning, 2022
VR technology allows learners to access simulated, immersive and interactive virtual environments to perform authentic learning activities. In particular, VR has emerged as a valuable tool for L2 learning. However, VR research has tended to pay more attention to desktop-based VR than to VR via mobile-rendered HMDs, leaving the potentials of VR…
Descriptors: Computer Simulation, Educational Technology, English (Second Language), Second Language Learning
Wu, Junjie Gavin; Miller, Lindsay – Computer Assisted Language Learning, 2021
This article reports the study of a novel way of raising tertiary-level students' native cultural awareness (NCA) via an informal mobile learning community. Through two cycles of action research at a teacher-education university in East China, the study drew upon the Community of Practice (CoP) theory to form a synchronous English chat group.…
Descriptors: Foreign Countries, Cultural Awareness, English (Second Language), Second Language Learning
