Innovation in Language Learning

Edition 17

Accepted Abstracts

An Immersive Language Learning Platform Leveraging Canon Literature and AI-driven Tools

Sasha Mile Rudan, University in Oslo; LitTerra Foundation, Belgrade, Serbia (Norway)

Sinisa Rudan, LitTerra Foundation, Belgrade; ChaOS, Belgrade (Serbia)

Lazar Kovacevic, LitTerra Foundation, Belgrade (Serbia); Inverudio, Chicago (United States) (Serbia)

Abstract

We present LitTerra [1], a cutting-edge literary platform that supports an engaging and interactive language learning model. LitTerra offers a hybrid and inter-textual reading experience, particularly focused on multi-lingual corpora, making it an ideal tool for language learners. At its core, the LitTerra platform is generic-by-design, and as such, it supports various uses, including creative translation work [2], socially engaged art [3], and digital scholarly editing (DSE),  thanks to its generic features such as dynamic workflows, multi-annotations, AI integration, advanced layouts, collaboration, and multi-media text augmentation. By selecting a multilingual corpus of renowned literary works, we provide learners with a rich language learning resource. Our platform utilizes machine alignment and manual refinement to generate bilingual parallel texts, which are then augmented with open-world references, images, and text simplifications to facilitate comprehension. Key values proposed are: (1) Simplification: simplifying sentences using synonyms that are etymologically, phonetically, or semantically easier for learners, (2) Augmentation: words are augmented with open-world references, and images, while sentences are augmented with AI-generative images, which facilitates contextual understanding and retention , (3) Adaptive Learning Quests and Gamification: the platform collecting learned words and utilizes generative AI to generate multi-modal personalized quests and games based on learners' progress, reinforcing learning outcomes and making learning enjoyable, (4) Interactive Learning: Engaging learners with AI-driven chats and dialogues in the target language, partially evaluated for correctness using multi-lingual LLMs and embeddings, (5) User-Generated and Localized Content: Users can incorporate external content; such as poems, songs, news or social media posts, while the corpus itself provides location-related texts that makes travelers more motivate. All this enriches experience, stimulate immenrsiona and finally increases the learning experience.

 

Keywords

Multi-lingual literary canon, ICT, generative AI, augmentation, gamification

 

REFERENCES

[1] Rudan, Sasha Mile, et al. "Twin Talk: Bukvik+ LitTerra+ Colabo. Space-An example of DH collaboration across disciplines, languages, and style." (2020): 15-29.

[2] Rudan, Sasha Mile, et al. "Augmenting and Informing the Translation Process through Workflow-Enabled CALT Tools." Computer-Assisted Literary Translation. Routledge, 2023. 258-281.

[3] O'Sullivan, James. "ELO2019: Electronic Literature Organization Conference & Media Arts." (2019).

 

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