FOKE: A Personalized and Explainable Education Framework Integrating Foundation Models, Knowledge Graphs, and Prompt Engineering

TL;DR

FOKE addresses personalization, interactivity, and explainability in intelligent education by integrating foundation models with knowledge graphs through a forest-based knowledge representation, and by leveraging prompt engineering and graph embeddings to tailor guidance. It introduces a hierarchical knowledge forest $KF={T_k}_{k=1}^K$, a multi-dimensional user profile $(A,B,T)$, and a structured prompt representation $(G,E,F)$, fused through a graph embedding framework to enable personalized, explainable guidance. The framework is demonstrated across interactive programming education, personalized learning path planning, and intelligent homework assessment, with Scholar Hero as a real-world instantiation. The authors discuss evaluation challenges and outline future work in expanding knowledge forests, improving prompts, and assessing impact in diverse educational settings.

Abstract

Integrating large language models (LLMs) and knowledge graphs (KGs) holds great promise for revolutionizing intelligent education, but challenges remain in achieving personalization, interactivity, and explainability. We propose FOKE, a Forest Of Knowledge and Education framework that synergizes foundation models, knowledge graphs, and prompt engineering to address these challenges. FOKE introduces three key innovations: (1) a hierarchical knowledge forest for structured domain knowledge representation; (2) a multi-dimensional user profiling mechanism for comprehensive learner modeling; and (3) an interactive prompt engineering scheme for generating precise and tailored learning guidance. We showcase FOKE's application in programming education, homework assessment, and learning path planning, demonstrating its effectiveness and practicality. Additionally, we implement Scholar Hero, a real-world instantiation of FOKE. Our research highlights the potential of integrating foundation models, knowledge graphs, and prompt engineering to revolutionize intelligent education practices, ultimately benefiting learners worldwide. FOKE provides a principled and unified approach to harnessing cutting-edge AI technologies for personalized, interactive, and explainable educational services, paving the way for further research and development in this critical direction.

Figures (2)

• Figure 1: Overview of the FOKE Framework
• Figure 2: Scholar Hero: The Application of the FOKE framework.