Abstract

The purpose of the study is to develop an algorithm for managing investments in preparation for entering a higher educational institution as an investment project.Materials and methods. The study includes a review of bibliographic sources on the existing methods and approaches to determining the economic efficiency of preparing for admission to a higher educational institution, as well as methods for assessing the effectiveness of investment projects. It also includes the collection and analysis of a statistical set of data and the development of a mechanism for choosing a training method with the available data about the applicant through neural network modeling.Results. A number of factors influencing the effectiveness of preparing an applicant for admission are considered. The effectiveness of the main trajectories of preparation for admission is evaluated by modeling the results of the collected statistical population, in particular: school preparation, tutoring, additional courses. Neural network models are created to determine the relationship between the factors influencing the result of preparation for admission and to make a choice to determine the significance of the applicant’s input parameters for various training trajectories. In accordance with the selected data, a neural network model is being developed to select the optimal trajectory for preparing for admission to a higher educational institution. As a result of creating a neural network model, a mathematical model is designed to determine the most optimal training method. Preparation for admission is considered as an investment project. By applying the method of evaluating the effectiveness of an investment project and the approach to managing it, based on the created model, an algorithm is described for choosing the best trajectory for preparing for admission to a higher educational institution, which allows applicants to independently evaluate investments in training as an investment project and choose the most cost-effective way of training. By adapting the method of assessing the economic efficiency of investments by discounting cash flows used in the business environment, a methodology was formulated for choosing the most optimal training trajectory.Conclusion. It can be argued that it makes sense to consider investments in additional preparation for a high school student to enter a higher educational institution as an investment project in which the parent acts as an investor, and the goal of the project is to enter a higher educational institution. To assess the effectiveness of investments in training and competent management of them, an algorithm has been developed for choosing the most cost-effective trajectory of preparation for entering a higher educational institution, using the example of admission to the Perm State National Research University. The algorithm is based on a neural network model that takes into account the input parameters of students: the duration of training, the frequency of additional classes, the level of motivation and average performance as factors influencing the probability of entering a higher educational institution. The algorithm is designed and can be used to manage investments in additional education of the child by determining the most cost-effective way to use financial resources. It is expedient to use the developed algorithm in those cases when the final goal involves the admission of a child to an educational institution. In this case, the use of the model will offer the best training path from an economic point of view for a particular applicant, taking into account the input parameters.

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