20–22 Nov 2026
The WINC Aichi
Asia/Tokyo timezone

Teaching Beyond the Classroom: AI-Supported Digital Literacy

21 Nov 2026, 14:30
30m
The WINC Aichi

The WINC Aichi

Practice-oriented Presentation (30-minutes) ALL: Accessibility in Language Learning Room 1105

Speaker

Ms Tungalag Sharkhuu (ELTAM, Mongolian National University of Education)

Description

This presentation explores how generative AI transforms English language education in Mongolia. Grounded in Mobile-Assisted Language Learning (MALL), the study examines how AI tools foster learner autonomy and multimodal communication. Findings demonstrate that while AI provides linguistic support, students must develop critical "human-in-the-loop" skills to ensure cultural sensitivity. The session offers practical strategies for integrating AI-supported digital literacies to bridge local and global communication in higher education contexts.

Abstract section 5: References

Butarbutar, R. (2024). Artificial intelligence for language learning and teaching: A narrative literature study. Englisia: Journal of Language, Education, and Humanities, 12(1), 147–163. https://doi.org/10.22373/ej.v12i1.23211
Edmett, A., Ichaporia, N., Crompton, H., & Crichton, R. (2024). Artificial intelligence and English language teaching: Preparing for the future (2nd ed.). British Council. https://doi.org/10.57884/78EA-3C69
Kukulska-Hulme, A. (2020). Mobile-assisted language learning. In C. A. Chapelle (Ed.), The concise encyclopedia of applied linguistics. Wiley.
Naveen, R., & Dwivedi, A. (2025). A multidimensional comparison of ChatGPT, Google Translate, and DeepL in the translation of Chinese tourism texts: fidelity, fluency, cultural sensitivity, and persuasiveness. Frontiers in Artificial Intelligence, 8, Article 1619489. https://doi.org/10.3389/frai.2025.1619489

Abstract section 3: Content/method

This study employed a qualitative classroom-based methodology over one semester. Data collection included systematic classroom observations, student reflective journals, and artifact analysis of AI-generated digital projects.
Using thematic analysis, the research examined how students integrated AI for multimodal tasks. This approach captures the nuanced development of learner autonomy and the "human-in-the-loop" evaluative process required to ensure linguistic and cultural accuracy in a Mongolian context.

Abstract section 1: Relevance

This presentation aligns with Mobile-Assisted Language Learning (MALL) theory (Kukulska-Hulme, 2020), emphasizing how AI facilitates learning beyond traditional borders. It addresses the practical challenge English teachers face: integrating generative AI to foster learner autonomy and digital competence (Edmett et al., 2024).
By referencing current literature on AI’s narrative role in pedagogy (Butarbutar, 2024), the study bridges the gap between theoretical multimodal communication and classroom reality. It specifically highlights the necessity of "human-in-the-loop" verification, ensuring AI-generated content remains culturally sensitive and accurate (Naveen & Dwivedi, 2025).

Abstract section 2: Contribution/research questions

This research investigates how generative AI influences English acquisition and digital literacy in a Mongolian higher education context. The project is guided by follwoing research questions:
1. How does the integration of AI tools in undergraduate English courses impact learner autonomy and language production both inside and beyond the classroom?
2. To what extent does AI-supported feedback enhance students’ critical digital competence and their ability to evaluate machine-generated content for cultural and linguistic accuracy?

Abstract section 4: Outcomes/results

This research study demonstrates that AI integration significantly boosts learner autonomy and English usage outside the classroom. Analysis of student reflections and work reveals a marked improvement in multimodal communication and digital proficiency. Key results indicate that while AI provides instant linguistic feedback, students developed a critical "human-in-the-loop" approach, actively correcting machine-generated content for cultural sensitivity and accuracy. Ultimately, the findings suggest that AI tools serve as a vital bridge between local Mongolian contexts and global communication standards, enhancing both confidence and technical skill.

Title Teaching Beyond the Classroom: AI-Supported Digital Literacy
Teaching Context College and university education

Author

Ms Tungalag Sharkhuu (ELTAM, Mongolian National University of Education)

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