The landscape of education is rapidly evolving with the advent of Large Language Models (LLMs). The paper presents a personalized conversation-based tutoring system that harnesses LLMs to address learner-specific needs. Core components and insights from the study include:

• The integration of student modeling for diagnostic purposes.
• Utilization of prompt engineering within conversation-based tutoring to adjust teaching dynamically.
• A proof-of-concept system demonstrating effective personalization for learners.
• Available web demo to showcase the system’s functionality in real-time.

The combination of advanced LLMs and nuanced prompt engineering creates a personalized learning experience that can significantly impact education by customizing instruction and assessments to fit individual learning trajectories. Visit here