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  4. Study-Buddy: A Knowledge Graph-Powered Learning Companion for School Students
 
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October 21, 2023
Conference Paper
Title

Study-Buddy: A Knowledge Graph-Powered Learning Companion for School Students

Abstract
Large Language Models (LLMs) have the potential to substantially improve educational tools for students. However, they face limitations, including factual accuracy, personalization, and the lack of control over the sources of information. This paper presents Study-Buddy, a prototype of a conversational AI assistant for school students to address the above-mentioned limitations. Study-Buddy embodies an AI assistant based on a knowledge graph, LLMs models, and computational persuasion. It is designed to support educational campaigns as a hybrid AI solution. The demonstrator showcases interactions with Study-Buddy and the crucial role of the Knowledge Graph for the bot to present the appropriate activities to the students. A video demonstrating the main features of Study-Buddy is available at: https://youtu.be/DHPTsN1RI9o.
Author(s)
Martinez, Fernanda
Universidad Privada Boliviana
Collarana Vargas, Diego  
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Calvaresi, Davide
University of Applied Sciences Western Switzerland
Arispe, Martin
Universidad Privada Boliviana
Florida, Carla
Universidad Privada Boliviana
Calbimonte, Jean-Paul
University of Applied Sciences Western Switzerland
Mainwork
The Semantic Web: ESWC 2023 Satellite Events. Proceedings  
Conference
Extended Semantic Web Conference 2023  
DOI
10.1007/978-3-031-43458-7_25
Language
English
Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS  
Keyword(s)
  • Knowledge Graphs

  • NLP

  • Personalized Education

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