The relevance of the research under consideration is due to the need to improve the efficiency of the analysis of the quality, and completeness of the knowledge obtained by students when solving computational problems, the example problems in mathematics. The theoretical argumentation is proposed and the practical implementation of an intelligent automated analytical system for analyzing the quality and forecasting the content of educational material and the trajectories of the student's learning direction is described. The relevance of the research is the creation of neural network algorithms that allow analyzing the dynamics of changes in the student's level of formation of skills to solve arithmetic problems. The methods of analyzing the assimilation of educational information and methods of personalized construction of the curriculum for each student are substantiated.

A model of distributed storage split data using algorithms, multidimensional parity, resistance to partial losses of the storage sites, is regarded as an alternative way of security that can replace the conventional multiple reservations and carrying costs of growth of the physical volume. In this model, the generated redundant data allows you to restore partial loss of the split parts. In this case, the recovery is performed at the expense of the parity files formed during the splitting procedure, in which the main action is the calculation of bitwise parity with summation modulo "two". With this additional operation between the source files, you can restore the corrupted file without distortion. A comparison with several models that use checksum codes for recovery shows that the estimated probability of losses due to storage failure in the case of multidimensional parity codes is significantly less than when using other split data storage options. Using the operation of adding the bits of undamaged files, you can completely restore corrupted files. According to the calculated data, even when theoretically non-recoverable losses are reached, it is always possible to find combinations of chain recovery. The complexity of alternative methods, including the iterative decoding method, makes a distributed split data storage system using multidimensional parity algorithms a more convenient error correction technology. Keywords— , , , , loss recovery, .