Abstract

The aim of this work is to move from the foreign dominated to the self-dominated by encouraging people to draw their own conclusions with the help of own rational consideration. Here a room as an environment that is encouraging innovation, which can be denoted as “Innovation Lab”, and making processes as can be regarded as “Smart Lab” is an essential base. The question related to this generalized self-organizational learning method investigated in our paper is how a UVC, which is a room that connects people from different physical places to one synchronous and virtual perceivable place, which is built on these preconditions, can be operated both resource and learning-efficient for both the course participants and the educational organization. A practical approach of implementing a virtual classroom concept, including informative tutorial-feedback, is developed conceptually that also accounts for and implements the results of reinforcement machine-learning methods in AI applications. The difference that makes the difference is gained by reimplementing the AI tools in an AI instrument, in a “Smart Lab” environment and that in the teaching environment. By means of this, a cascaded feedback-loop system is informally installed, which gains feedback at different levels of abstraction. By this learning on each stage, in a collaborative and together decentralized and sequential fashion takes place, as the selforganizational implementations lead implicitly, also by means of the in the course implemented tools, to increasingly self-control. As such in the course, a tool is implemented, as generalizations by means of reinforcement learnings are to be emergently foreseen by this method, which goes beyond the tools, that have already been implemented before. This AI-enhanced learning coevolution shall then, predictively, as well increase the potential of the course participants as the educational organization according to the Wittgensteinean parable: A ladder leading into a selfly-organized future.