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Hauptverfasser: Gupta, Sammriddh, Singh, Sonit, Joshi, Aditya, Kim, Mira
Format: Preprint
Veröffentlicht: 2025
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Online-Zugang:https://arxiv.org/abs/2510.23011
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author Gupta, Sammriddh
Singh, Sonit
Joshi, Aditya
Kim, Mira
author_facet Gupta, Sammriddh
Singh, Sonit
Joshi, Aditya
Kim, Mira
contents Language educators strive to create a rich experience for learners, while they may be restricted in the extend of feedback and practice they can provide. We present the design and development of LangLingual, a conversational agent built using the LangChain framework and powered by Large Language Models. The system is specifically designed to provide real-time, grammar-focused feedback, generate context-aware language exercises and track learner proficiency over time. The paper discusses the architecture, implementation and evaluation of LangLingual in detail. The results indicate strong usability, positive learning outcomes and encouraging learner engagement.
format Preprint
id arxiv_https___arxiv_org_abs_2510_23011
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle LangLingual: A Personalised, Exercise-oriented English Language Learning Tool Leveraging Large Language Models
Gupta, Sammriddh
Singh, Sonit
Joshi, Aditya
Kim, Mira
Computation and Language
Computers and Society
Language educators strive to create a rich experience for learners, while they may be restricted in the extend of feedback and practice they can provide. We present the design and development of LangLingual, a conversational agent built using the LangChain framework and powered by Large Language Models. The system is specifically designed to provide real-time, grammar-focused feedback, generate context-aware language exercises and track learner proficiency over time. The paper discusses the architecture, implementation and evaluation of LangLingual in detail. The results indicate strong usability, positive learning outcomes and encouraging learner engagement.
title LangLingual: A Personalised, Exercise-oriented English Language Learning Tool Leveraging Large Language Models
topic Computation and Language
Computers and Society
url https://arxiv.org/abs/2510.23011