Intelligent Tutoring Systems (ITS) are computer programs that use leamers" knowledge level to providing indívidualized education. ITS research has successfully delivered systems efficiently supporting one-to-one tutoring. Most of these systems are actively used in real-worid settings and have even contributed to changing traditional education curricula. Instructional activities, learning examples, exploring interactive simulations and playing educational games can benefit from individualized computer-based assistance. To enhance ongoing research related to the improvement of tutoring, we present an extended knowledge mode! including besides the standard modules a common shared database and knowledge-based background, too. The external databases can improve the guality of the behavior models both in tutor and student models. The Python programming language and OWL are efficient tools to combine the ontology management and machine leaming functions to develop ITS systems. In this Paper, we survey ITS technologies andpresent a novel extended architecture model for Intelligent e-Tutoring Systems
