9 papers
From Prompts to Context: An Ontology-Driven Framework for Human-Generative AI Collaboration
Ngoc Luyen Le, Marie-Hélène Abel, Bertrand Laforge
Collaborations with Generative AI often begin with a short prompt and end with an opaque output, leaving implicit who was involved, what task was being pursued, which resources wer…
When Can We Trust Early Warnings? Leakage-Excluded Early Outcome Prediction from LMS Interaction Logs
Ngoc Luyen Le, Marie-Hélène Abel, Bertrand Laforge
Early-warning models built from Learning Management System (LMS) logs aim to predict end-of-course outcomes early enough to enable timely learner support. However, reported "early"…
KG-First, LLM-Fallback: A Hybrid Microservice for Grounded Skill Search and Explanation
Ngoc Luyen Le, Marie-Hélène Abel, Bertrand Laforge
Authoritative competency frameworks such as ESCO, ROME, and O*NET are essential for aligning education with labor market needs, yet their technical complexity and structural hetero…
Development of Ontological Knowledge Bases by Leveraging Large Language Models
Le Ngoc Luyen, Marie-Hélène Abel, Philippe Gouspillou
Ontological Knowledge Bases (OKBs) play a vital role in structuring domain-specific knowledge and serve as a foundation for effective knowledge management systems. However, their t…
Automated Skill Decomposition Meets Expert Ontologies: Bridging the Granularity Gap with LLMs
Le Ngoc Luyen, Marie-Hélène Abel
This paper investigates automated skill decomposition using Large Language Models (LLMs) and proposes a rigorous, ontology-grounded evaluation framework. Our framework standardizes…
How Well Do LLMs Predict Prerequisite Skills? Zero-Shot Comparison to Expert-Defined Concepts
Ngoc Luyen Le, Marie-Hélène Abel
Prerequisite skills - foundational competencies required before mastering more advanced concepts - are important for supporting effective learning, assessment, and skill-gap analys…