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Enhancing human-centric CALL through AI innovations

Ward, Monica orcid logoORCID: 0000-0001-7327-1395, Xu, Liang orcid logoORCID: 0000-0002-2619-1883 and Uí Dhonnchadha, Elaine orcid logoORCID: 0000-0003-3448-4288 (2024) Enhancing human-centric CALL through AI innovations. In: EuroCALL 2024, 26-29 August 2024, Trnava, Slovakia.

Abstract
This paper explores the integration of Artificial Intelligence (AI) into Computer-Assisted Language Learning (CALL) to create a more engaging and supportive educational experience. This study delves into the utilisation of Natural Language Processing (NLP), AI image generation and text-to-speech (TTS) technologies to enhance the game-like elements of CALL resources. Drawing from recent experiments, the paper discusses the iterative improvements made to the Cipher game (Xu et al., 2024), shedding light on the positive impact of AI on both user experience and learning outcomes.The integration of NLP, AI image generation and TTS AI in CALL resources, as exemplified by the Cipher game, demonstrates their effectiveness in creating engaging and inclusive language learning experiences. These technologies not only improve productivity but also cater to the needs of learners with diverse requirements. This paper advocates for further exploration and implementation of AI in CALL to promote humanity, interactivity, and accessibility in language education.
Metadata
Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Refereed:Yes
Uncontrolled Keywords:CALL, Artificial Intelligence, digital game-based language learning
Subjects:Computer Science > Artificial intelligence
Computer Science > Interactive computer systems
Computer Science > Multimedia systems
Humanities > Irish language
Humanities > Language
Social Sciences > Educational technology
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
Research Institutes and Centres
Research Institutes and Centres > ADAPT
Research Institutes and Centres > d-real
Published in: Proceedings of the 2024 EUROCALL Conference. . Editorial Universitat Politècnica de València.
Publisher:Editorial Universitat Politècnica de València
Official URL:https://riunet.upv.es/server/api/core/bitstreams/e...
Copyright Information:Authors
Funders:Science Foundation Ireland
ID Code:32006
Deposited On:15 Dec 2025 11:32 by Liang Xu . Last Modified 15 Dec 2025 11:32
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