In personalized education platforms, explainable recommendation is often pursued by transferring knowledge-graph path reasoning methods from other domains, yet differences in educational data and evaluation practices can make these transfers misaligned and leave it unclear which methods remain reliable and why. Knowledge-graph reasoning can enable transparent, structure-aware personalization in this setting by producing recommendation paths …
Category: Education
EDGE: A Conversational Interface driven by Large Language Models for Educational Knowledge Graphs Exploration
Navigating educational data is a growing challenge. EDGE offers a fusion of large language models and knowledge graphs to enable intuitive, natural language-driven exploration, empowering educators, learners, and administrators with actionable insights for accessing and understanding educational ecosystems. In an era where digital education platforms generate vast amounts of data, navigating and making sense of …