Driving simulators need an Intelligent Tutoring System (ITS). Simulators provide ways to conduct objective measurements on students' driving behavior and opportunities for creating the best possible learning environment. The generated traffic situations can be influenced directly according to the needs of the student. We created an ITS -the Virtual Driving Instructor (VDI) -for guiding the learning process of driving. The VDI is a multiagent system that provides low cost and integrated controlling functionality to tutor students and create the best training situations.

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Augmented tabletops can be used to create multi-modal and collaborative environments in which natural interactions with tangible objects that represent virtual (digital) information can be performed. Such environments are considered potentially interesting for many different applications. In this paper, we address the question of whether or not it makes sense to use such environments to design learning experiences for young children. More specifically, we present the "Read-It" application that we have created to illustrate how augmented tabletops can support the development of reading skills. Children of fiveto-seven-years old were actively involved in designing and testing this application. A pilot experiment was conducted with a prototype of the Read-It application, in order to confirm that it does indeed meet the a priori expectations. We hope that the Read-It application will inspire the development of more tabletop applications that are targeted at specific user groups and activities.

Abstract. Multi-modal tabletop applications offer excellent opportunities for enriching the education of young children. Read-It is an example of an interactive game with a multi-modal tangible interface that was designed to combine the advantages of current physical games and computer exercises. It is a novel approach for supporting children who learn to read. The first experimental evaluation has demonstrated that the Read-It approach is indeed promising and meets a priori expectations.

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