An Efficient Approach to Decision-making in the Education Process: Markov Chain for Fuzzy States

This paper reports on an efficient approach within the control of the school education process. Namely, we use the discrete Markov chain for a system with fuzzy states that based on processing data from time series (a set of student’s grades within some time period). In this case, the transition matrix has stochastic nature. Such an approach makes it possible to obtain stationary states of the system that characterize its status at a certain given time interval. This result can be used in a decision support system for targeted status changes. A feature of the resulting Markov chain for fuzzy states of a system is the ability to take into account the dynamics of changes in system states when calculating average status values, in contrast to the widely used averaging based on calculating arithmetic averages.