Creation and testing of the educational and scientific activity model for educational institution: technology, quality assessment, socio-economic impact

Abstract

An attempt to algorithmize the process of creating and evaluating the quality of educational institutions' educational and scientific activities using an analogy with software products testing in the IT field is made in this paper. In the scope of this paper for describing the algorithm of creating the educational and scientific activities model for educational institutions, abstract-logical, analogue, and induction-deduction methods are used. The content of each of the given algorithm blocks, particularly from the point of view of its influence on the social and economic development of the state is considered. The multi-stage mechanism for checking the model performance according to the algorithm «testing – quality control – internal quality assurance – external quality assurance» is proposed. Indicators such as the economic model; implementation risk assessment; market research of services and competitors; creation of the network of sub-accounts of educational and scientific services providers; formation of the estimation for each element of the system operation; calculation of the estimated financing for the implementation of activities; search for donors and/or own funds to finance the main components of the system; the place of the educational institution in national and/or international rankings, rankings by specialty, et.; employer feedback; the average salary of the graduate of educational program; graduate carrier growth rate are proposed as socio-economic indicators of educational and scientific activity model (system) for educational institution. The presented algorithm of creating and testing an effective educational and scientific activity model for educational institution makes it possible to determine the conditions of multi-stage verification of the quality assurance mechanisms effectiveness, particularly at the stages of testing, quality control, internal and external quality assurance according to the relevant stakeholders' feedback (testers). At each stage of the algorithm, socio-economic impact factors, which are the tools for further adjustment (if necessary) and optimization of the model are identified.