Volume 14, Number 1

Enhancing Educational QA Systems: Integrating Knowledge Graphs and Large Language Models for Context-Aware Learning

  Authors

Ayse Arslan, USA

  Abstract

This study explores the integration of Knowledge Graphs (KGs) and Large Language Models (LLMs) to develop an advanced question-answering (QA) system for educational purposes. The proposed method involves constructing a KG using LLMs, retrieving contextual prompts from high-quality learning resources, and enhancing these prompts to generate accurate answers to complex educational queries. The technical framework presented in this paper, along with the analysis of results, contributes significantly to the advancement of LLM applications in educational technology. The findings provide a robust foundation for developing intelligent, context-aware educational systems that leverage structured knowledge to support personalized learning and improve educational outcomes.