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Exploring the Synergies between Technology and Socio-Cultural Approaches in Computer-Assisted Language Learning for Less Commonly Taught languages

Xu, Liang orcid logoORCID: 0000-0002-2619-1883, Uí Dhonnchadha, Elaine and Ward, Monica orcid logoORCID: 0000-0001-7327-1395 (2023) Exploring the Synergies between Technology and Socio-Cultural Approaches in Computer-Assisted Language Learning for Less Commonly Taught languages. In: 10th Language & Technology Conference, April 21-23, 2023, Poznań, Poland.

Abstract
Language learning is a complex task and to be successful, it involves a range of cognitive processes. Intelligent Computer Assisted Language Learning systems can be useful for enhancing the effectiveness and efficiency of both teacher-led instruction and student learning. Digital technologies are routinely employed for commonly taught languages but are less frequently used in the Less Commonly Taught Language (LCTL) context. In this study, we investigate methods for encouraging the learning and teaching of LCTLs, particularly indigenous and endangered languages. Our research blends language learning pedagogy, socio-cultural theory, and Digital Game-Based Language learning (DGBLL) in the form of games and Virtual Reality. Language learning materials are enhanced with the aid of Natural Language Processing techniques. We present a DGBLL system designed to promote language learning and student engagement. The system has been tested successfully in primary school classrooms, with positive feedback from both students and teachers.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Subjects:Computer Science > Interactive computer systems
Computer Science > Multimedia systems
Humanities > Irish language
Humanities > Language
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Published in: Proceedings of the 10th Language & Technology Conference, pages 337-342. .
Official URL:https://ltc.amu.edu.pl/
Funders:SFI
ID Code:31371
Deposited On:11 Aug 2025 10:29 by Liang Xu . Last Modified 11 Aug 2025 10:29
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