Journal Article

Neuro-symbolic synergy in education: a survey of LLM-knowledge graph integration for explainable reasoning and emotion-aware student support

Ben Chaabene, Nour El Houda, Hammami, Hamza

2026

Overview

This article presents a structured survey of recent approaches integrating Large Language Models (LLMs) and Knowledge Graphs (KGs) in education, with a dual focus on explainable reasoning and emotion-aware student support. The objective is to assess how neuro-symbolic architectures and affective computing enhance both transparency and learner well-being in AI-driven tutoring systems. A multimodal literature review was conducted, combining keyword-based searches across Scopus, IEEE Xplore, and SpringerLink from 2020 to 2024, with inclusion criteria focusing on studies addressing LLM explainability, KG integration, and affective adaptation in education. The selected papers were analyzed using a three-axis framework: (1) technological synergy (LLM–KG–Affective AI), (2) evaluation metrics (Pedagogical Alignment Score, Anxiety Reduction Index, Scaffolding Perplexity Divergence), and (3) equity and explainability gaps. Results reveal that hybrid systems improve interpretability, engagement, and personalization, but remain limited by the absence of metacognitive modeling and standardized affective benchmarks. Practical implications include actionable strategies for developing transparent, stress-aware, and ethically grounded tutoring systems, such as emotion-adaptive scaffolding, blockchain-based validation of explanations, and federated learning for privacy-preserving personalization.

• Publisher: Springer Nature Singapore,Springer Nature B.V,SpringerOpen
• Subject: Academic Achievement / Accuracy / Affective computing / Affective learning systems / Affective Objectives / Artificial intelligence / Calculus / Computers and Education / Cultural Differences / Curricula / Database Management Systems / Distance Education / Distance learning / Education / Educational Environment / Educational Needs / Educational Technology / Emotional Intelligence / Emotional intelligence in pedagogy / Emotions / Equations (Mathematics) / Error Correction / Explainable AI in education / Federated learning / Graphs / Hybrid systems / Influence of Technology / Instructional Materials / Interdisciplinary subjects / Knowledge graph integration / Knowledge representation / Language / Language Processing / Large language models / Learner Engagement / Learning Experience / Literature reviews / Machine learning / Mathematical Formulas / Mathematical problems / National Curriculum / Natural language processing / Oral Language / Pedagogy / Psychological Needs / Real time / Reasoning / Scaffolding / Students / Well being