Applying demand analysis of a set of test problems for developing adaptive courses

Knowledge space theory was already applied for building adaptive testing and training systems which contain test and training problems including their prerequisite structure, and which offer explanations and help for solving these problems. Normally, however, lessons prepare students for solving problems. In this paper, the authors present a method for systematically structuring an adaptive eLearning course containing test problems as well as lessons. This method is based on knowledge space theory extended by component-wise representation of problems and on applying demand analysis. A course developed with such a method can be fed into an adaptive tutoring system, realized, e.g., within the adaptive tutoring system RATH.