ASSESSING THE RESULTS OF TRAINING IN DIGITAL ENTREPRENEURSHIP IN THE AGE OF HIGH AND DEEP TECH

Abstract

Digital transformation and the rise of Industry 4.0 in times of turbulence are changing the way organizations operate and interact with the people they serve. The massive penetration of network software applications and cloud services forces businesses to digitize their processes and provide innovative products and services. Such mass penetration is changing production and business processes, the labour market, and the basic portrait of the workforce, regardless of industry or role. In addition, we are seeing a shift in the basic skills needed in science, research and development, engineering, IT, management, entrepreneurship, and more. These skills are transformed in accordance with the technological restructuring of productive forces, at the same time, educational activity is characterized by some lag in its development. It is important to realize that the nature and speed of progress dictates the need for an advanced workforce with a multidisciplinary educational background (especially given the number of predictions promising full automation in the next few decades), regardless of industry or function, especially when it comes to deep tech start-ups and high-tech enterprises. It was concluded that in the framework of modern technical evolution, in the conditions of high-tech, and especially deep tech structures, competencies in digital entrepreneurship are, if not key, then very important. The education market is also undergoing changes, but university education is very slow to respond to digital processes. The article proposes a method of assessing the level of competences of students of economic specialties in the field of learning digital entrepreneurship based on soft computing, and also formulates the key basic competencies that arise during the online course of digital entrepreneurship, which are based on the latest development trends in the field of IT. Special considerations for using the model for higher education institutions are discussed. The proposed mathematical model has the property of universality and can be applied to obtain basic statistical samples of the level of competence acquisition based on online courses in various areas of the real sector of the economy.