NEURODIDACTIC MODEL AS A TOOL FOR IMPROVING THE QUALITY OF TRAINING SPECIALISTS IN AN ENGINEERING UNIVERSITY

Abstract

The relevance of this study is due to the ever-growing shortage of engineering personnel in megacities, which are complex socio-economic systems, where engineering work is becoming one of the key factors of sustainable development. The most important task for the effective functioning of social and labor relations in megacities is the creation of new tools for assessing, forecasting and adapting human resources, including using modern digital technologies such as neural networks and blockchain. In this context, the authors of the article consider the possibility of using blockchain technologies and smart contracts in the field of social and labor relations of engineers in a megalopolis. The authors proposed a method for supporting management decisions as a set of digital tools including neural network algorithms, big data analysis and dynamic matching of applicant profiles and employer requirements. The authors developed the system for forming a digital “portrait of skills” of a graduate in the context of a dynamic, updated profile, reflecting his professional and personal competencies confirmed by digital “traces”. The proposed system for forming a digital “portrait of skills” of an engineer and a neural network method for comparing the formed skills with the requirements of employers in a metropolis were tested in metropolises universities and partner companies with a shortage of highly qualified engineering personnel.