Large Language Models for Education: Understanding the Needs of Stakeholders, Current Capabilities and the Path Forward

Sankalan Pal Chowdhury, Nico Daheim, Ekaterina Kochmar, Jakub Macina, Donya Rooein, Mrinmaya Sachan, Shashank Sonkar


Abstract
This tutorial will aim to bridge the gap between NLP researchers and Artificial Intelligence in Education (AIED) practitioners to help participants understand the requirements and challenges of education, enabling them to develop LLMs that align with educational needs, and to enable educators to gain a deeper understanding of the capabilities and limitations of current NLP technologies, fostering effective integration of LLMs in educational contexts.
Anthology ID:
2025.bea-1.1
Volume:
Proceedings of the 20th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2025)
Month:
July
Year:
2025
Address:
Vienna, Austria
Editors:
Ekaterina Kochmar, Bashar Alhafni, Marie Bexte, Jill Burstein, Andrea Horbach, Ronja Laarmann-Quante, Anaïs Tack, Victoria Yaneva, Zheng Yuan
Venues:
BEA | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1–10
Language:
URL:
https://preview.aclanthology.org/display_plenaries/2025.bea-1.1/
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Bibkey:
Cite (ACL):
Sankalan Pal Chowdhury, Nico Daheim, Ekaterina Kochmar, Jakub Macina, Donya Rooein, Mrinmaya Sachan, and Shashank Sonkar. 2025. Large Language Models for Education: Understanding the Needs of Stakeholders, Current Capabilities and the Path Forward. In Proceedings of the 20th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2025), pages 1–10, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):
Large Language Models for Education: Understanding the Needs of Stakeholders, Current Capabilities and the Path Forward (Pal Chowdhury et al., BEA 2025)
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PDF:
https://preview.aclanthology.org/display_plenaries/2025.bea-1.1.pdf