Methods for assessment of the quality of leaning are discussed, including possibilities to predict the results of the learning based on the calculation of negentropy. Negentropy is used as an integral informational index, demonstrating objective assessment of the learning model used. We suggest to use the emergent learning model, as a generalized projection of the learning process with substantiated merging of e-learning and traditional learning. For setting up a multi-criterial system for assessment of the quality of learning, we suggest to evaluate all components of pedagogical system in interplay with each other, on the first and all following hierarchical levels. We also suggest to define students as a special category of objects in the said pedagogical system, which interacts with other elements of the system, and thus the system is organized as “student-oriented”. Suggested methodology of prediction and assessment of the learning progress relies on building an hierarchical structure of criterial system of quality. In phase one, we have chosen basic criteria influencing the quality of the learning, which are organized into the first level of Ishikawa diagram. Basing on expert’s knowledge, we then assigned each criterium a corresponding coefficient of importance for the quality of learning. In the second phase, the same was done for criteria of the second and third levels of importance. In cases when it was not possible to unequivocally assess the coefficient of importance, we present the system of equations for calculating the membership function of a fuzzy set. In the third phase, integral values of negentropy were calculated for three study courses and for a model situation.

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This article is a logical continuation of the material published in the journal “Informatics and Education” № 6-2018. The authors consider the issues of predicting learning outcomes based on the calculation of negentropy, which is proposed to be considered as an integral information indicator characterizing the quality of student learning.The work can be divided into three stages and is based on the construction of the hierarchical structure of the criteria-based quality system. At the first stage, a questionnaire was developed for the survey of expert teachers, in which it was necessary to note, from the point of view of importance, the criteria of the first and second levels those influence the process of emergent learning. At the second stage, using an expert rationing method, an array of expert estimates was processed, representing an example of a fuzzy set. As a result, weighting coefficients were obtained according to the criteria of the first and second levels. At the third stage, a dichotomous assessment of the third level criteria was carried out and the integrated values of negentropy were calculated for the three directions of training and for the model situation.The algorithms proposed in the article can be used both to assess the quality of already developed online courses, products or educational processes with their use, and to predict learning outcomes based on expert assessment.