PERO2 Machine Teaching based on a Normalized Ontological Knowledge Base

Abstract

In order to extend the deployment of Machines Teaching in educational institutions, by facilitating their appropriation by human learners (teachers and students) and to explore the motivation of interactive Machines Teaching to solve problems by making a human as an indispensable pillar of the teaching process. This research framework is part of PERO2 project (intelligent system for learning of reasoning and problem-solving dedicated to the physical science domain specifically the teaching subdomain "Electricity") which is about the integration of a semantic layer within the architecture of PERO2 this by means of representing the system's knowledge base via a normalized domain ontology and then integrating the exploitable ontological knowledge base instead of a relational database. To design this ontological knowledge base, we proposed in the current research work a hybrid construction method taking into account two main phases: (*) Conception phase of our domain ontology called "OntoPhyScEx". (**) Normalization also called Semantic validation phase of this domain ontology. As for the integration and exploitation of this domain ontology, it's been discussed in another paper.