MAKING DECISIONS IN EDUCATIONAL MANAGEMENT WITH PROBABILISTIC AND IMPRECISE INFORMATION

Decision making is a cornerstone in educational management and in many other disciplines. Usually, people need to make decisions in order to assess educational problems in the most efficient way. In this paper, we study decision methodologies in educational management when the available information can be assessed with probabilistic and imprecise information. We introduce the uncertain induced generalized probabilistic ordered weighted averaging (UIGPOWA) operator. It is an aggregation operator that unifies the probability and the OWA operator in the same formulation and considering the degree of importance that each concept has in the aggregation. It also uses order inducing variables that deals with complex reordering processes of the information. Moreover, it is able to deal with imprecise environments that cannot be assessed with precise information but it is possible to use imprecise information such as the use of interval numbers. Furthermore, it also uses generalized aggregation operators that include a wide range of particular cases including the probabilistic OWA (POWA) operator, the induced generalized OWA (IGOWA) and the generalized probabilistic aggregation (GPA). We see that the applicability of this new approach is very broad because it can be implemented in a wide range of fields including statistics, economics and engineering. We focus on educational management problems. Specifically, we develop a new decision making approach regarding the selection of the optimal studies plan. We use group decision making techniques to assess the problem in order to obtain a more robust approach. We use the theory of expertons in the analysis. Thus, we can represent the information of the different experts in a collective way.