Xu, Liang
ORCID: 0000-0002-2619-1883, Uí Dhonnchadha, Elaine
ORCID: 0000-0003-3448-4288 and Ward, Monica
ORCID: 0000-0001-7327-1395
(2023)
Harnessing the power of images in CALL: AI image generation for context specific visual aids in less commonly taught languages.
In: EUROCALL 2023: CALL for all Languages, 15-18 August 2023, Reykjavik, Iceland.
Abstract
This paper explores the application of AI image generation in Computer-Assisted Language Learning (CALL) for Less Commonly Taught Languages (LCTLs). It delves into the potential of text to image generation models in creating context specific visual aids to enhance comprehension and engagement among learners. The integration of AI generated images in a language learning game, Cipher, is discussed, showcasing the benefits and challenges encountered. Learner feedback indicates positive inclinations towards the AI generated images, but also highlights the need for meticulous selection to address biases and stereotypes. Overall, this approach shows promise in creating culturally relevant CALL resources and improving language learning experiences for learners of LCTLs.
Metadata
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| Event Type: | Conference |
| Refereed: | Yes |
| Uncontrolled Keywords: | CALL, less commonly taught languages, AI image generation, educational games |
| 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 > ADAPT Research Institutes and Centres > d-real |
| Published in: | CALL for all Languages - EUROCALL 2023, Short Papers. . Editorial Universitat Politècnica de València. |
| Publisher: | Editorial Universitat Politècnica de València |
| Official URL: | https://riunet.upv.es/server/api/core/bitstreams/0... |
| Funders: | Science Foundation Ireland |
| ID Code: | 31983 |
| Deposited On: | 11 Dec 2025 11:25 by Liang Xu . Last Modified 11 Dec 2025 11:25 |
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