Adaptive Tutoring in Virtual Learning Worlds Kawa Nazemi kawa.nazemi@igd.fraunhofer.de Nadeem Bhatti Nadeem.bhatti@igd.fraunhofer.de Eicke Godehardt eicke.godehardt@igd.fraunhofer.de Christoph Hornung christoph.hornung@igd.fraunhofer.de Abstract: To enhance the learning success of the learners in the Virtual Learning Worlds (VLW) and effective of VLW, the aspects like precognition and learning aptitude of the learners play a key role. The constructivistic approach based VLW not only offers learning, but also great experience by exploring through reality based virtual worlds. VLWs can be extended with such a Learning Environment. They are Novices or Beginner and need more explanations and instructions to understand a topic and resolve a given problem. An Adaptive Tutoring System tries to find out the differences in precognitions and learning aptitudes and offers the learning task depending on these parameters. In the following paper a new system is designed for adapting a VLE to learners’ need and presenting the learning tasks based on the recommended pedagogical approach. 1 Introduction A Virtual Learning Environment (VLE) provides the opportunity to interact and learn in a virtual world, which is simulating the real environment, where the adopted knowledge can be used. The user of such a system learns as a result of experiencing and handling in and with different situations. The learning process in a VLE is based upon the constructivistic approach (see Bhatti, Hornung and Godehardt 2005). Beside the constructivistic approach there are two other famous approaches which try to convey knowledge or give the learner the ability to appropriate knowledge in their own way, namely cognitivistic and behaviouristic approaches. Based on the type of knowledge the different approaches should be used for conveying knowledge (see Baumgartner and Payr 1997). Knowledge itself can be classified in three categories: declarative knowledge, procedural knowledge and Know-how (see Ryle 2003, Baumgartner 1993). But not only the type of knowledge are decisive for the best pedagogical approach. More important than the type of knowledge is the state of knowledge of each learner (see Baumgartner and Payr 1997). To enhance the effectiveness of the learning process, a teaching system should consider the precognitions and learning aptitudes of each learner, who works with that system. Depending on these parameters the learner should be analyzed and the most effective pedagogical approach should be chosen. This paper will describe a solution for a teaching system, which was developed in a research project (see Bhatti, Hornung and Godehardt 2005), which analyzes the learner before and while he interacts with a system and chooses the most effective pedagogical approach for that learner. Further the transformation of the pedagogical approaches into the tutoring based teaching in a virtual environment will be described. An exemplary scenario should clarify the operation methods of the adaptive tutoring system.