Curriculum-Driven Edubot: A Framework for Developing Language Learning Chatbots Through Synthesizing Conversational Data

TL;DR

This paper introduces Curriculum-Driven EduBot, a chatbot framework that synthesizes textbook content and large language models to enhance language learning through curriculum-aligned, adaptive conversational practice.

Contribution

It presents a novel method for creating curriculum-based chatbots by extracting textbook topics, generating dialogues with language models, and fine-tuning open-source models for educational use.

Findings

EduBot outperforms ChatGPT in curriculum-based dialogues.

EduBot adapts to different English proficiency levels.

User studies show improved student engagement.

Abstract

Chatbots have become popular in educational settings, revolutionizing how students interact with material and how teachers teach. We present Curriculum-Driven EduBot, a framework for developing a chatbot that combines the interactive features of chatbots with the systematic material of English textbooks to assist students in enhancing their conversational skills. We begin by extracting pertinent topics from textbooks and using large language models to generate dialogues related to these topics. We then fine-tune an open-source model using our generated conversational data to create our curriculum-driven chatbot. User studies demonstrate that EduBot outperforms ChatGPT in leading curriculum-based dialogues and adapting its dialogue to match the user's English proficiency level. By combining traditional textbook methodologies with conversational AI, our approach offers learners an interactive tool that aligns with their curriculum and provides user-tailored conversation practice. This facilitates meaningful student-bot dialogues and enriches the overall learning experience within the curriculum's pedagogical framework.