Curriculum-Driven Edubot: A Framework for Developing Language Learning
  Chatbots Through Synthesizing Conversational Data
Yu Li Shang Qu Jili Shen Shangchao Min Zhou Yu
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 then using large language
models to generate dialogues related to these topics. We then fine-tune an
open-source LLM using our generated conversational data to create our
curriculum-driven chatbot. User studies demonstrate that our chatbot
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.