LangLingual: A Personalised, Exercise-oriented English Language Learning Tool Leveraging Large Language Models

Sammriddh Gupta, Sonit Singh, Aditya Joshi, Mira Kim
10/27/2025
cs.CLcs.CY

No confident code implementation found for this paper. 2 possible matches can be shown below.

Abstract

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.

View on arXivView PDF

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. 2 weaker matches are hidden by default — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Similar Papers

Talking with Oompa Loompas: A novel framework for evaluating linguistic acquisition of LLM agents

81% match2025

DIALIGHT: Lightweight Multilingual Development and Evaluation of Task-Oriented Dialogue Systems with Large Language Models

80% match1 repo122024

Using Chatbots to Teach Languages

80% match2022

LLM Agents for Education: Advances and Applications

80% match2025

VQA support to Arabic Language Learning Educational Tool

80% match2025

Evaluating LLM-Generated Lessons from the Language Learning Students' Perspective: A Short Case Study on Duolingo

80% match2026

Cite this paper

@article{gupta2025langlingual,
  title  = {LangLingual: A Personalised, Exercise-oriented English Language Learning Tool Leveraging Large Language Models},
  author = {Sammriddh Gupta and Sonit Singh and Aditya Joshi and Mira Kim},
  year   = {2025},
  eprint = {2510.23011},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2510.23011v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2510.23011.svg)](https://codeofpaper.com/paper/2510.23011)

Discussion