Assessing the results of training in digital enterpreneurship in the age of high and deep tech

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Kyiv National Economic University named after Vadym Hetman

National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”

Technical University of Munich

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

Oleg Kaminsky ScD, Associate Professor, Associate Professor

Julia Yereshko ScD, Associate Professor, Professor

Sergii Kyrychenko PhD, Associate Professor

Maryna Duchenko PhD in Economics, Associate Professor

Kyiv, Munich

Abstract

competence learning digital entrepreneurship

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.

Keywords: digital economy; online courses; innovations in education; online education; online learning; digitalization; entrepreneurship; informatization of education; soft computing.

Анотація

ОЦІНЮВАННЯ РЕЗУЛЬТАТІВ НАВЧАННЯ ЦИФРОВОГО ПІДПРИЄМНИЦТВА В ЕПОХУ ВИСОКИХ ТА ГЛИБОКИХ ТЕХНОЛОГІЙ

Олег Камінський доктор економічних наук, доцент, доцент кафедри системного аналізу та кібербезпеки Київський національний економічний університет імені Вадима Г етьмана, м. Київ, Україна

Юлія Єрешко доктор економічних наук, доцент, професор кафедри економічної кібернетики Національний технічний університет України “Київський політехнічний інститут імені Ігоря Сікорського”, м. Київ, Україна Технічний університет Мюнхена, м. Мюнхен, Німеччина

Сергій Кириченко кандидат економічних наук, доцент, доцент кафедри економіки і підприємництва Національний технічний університет України “Київський політехнічний інститут імені Ігоря Сікорського”, м. Київ, Україна

Марина Дученко кандидат економічних наук, доцент, доцент кафедри економічної кібернетики Національний технічний університет України “Київський політехнічний інститут імені Ігоря Сікорського”, м. Київ, Україна

Цифрова трансформація та поступ Індустрії 4.0 у часи турбулентності змінюють функціонування організацій і їх взаємодію з людьми, яким вони надають послуги. Масове використання мережевих програмних додатків, хмарних сервісів змушує бізнес діджиталізувати свої процеси та надавати інноваційні продукти та послуги. Таке масове проникнення змінює виробничі та бізнес-процеси, ринок праці, а також базовий портрет робочої сили, незалежно від галузі чи її ролі. Крім того, ми спостерігаємо зміну базових навичок, необхідних у науці, дослідженнях і розробках, інженерії, ІТ, управлінні, підприємництві тощо. Ці навички трансформуються відповідно до технологічної реструктуризації продуктивних сил, водночас освітня діяльність характеризується певним відставанням у своєму розвитку. Важливо усвідомлювати, що характер і швидкість прогресу диктують потребу в сучасній робочій силі з багатопрофільною освітою (особливо з огляду на кількість прогнозів, що обіцяють повну автоматизацію в найближчі кілька десятиліть), незалежно від галузі або функції, особливо коли мова йде про глибокотехнологічні стартапи та високотехнологічні підприємства. Було зроблено висновок, що в межах сучасної технічної еволюції, в умовах високотехнологічних, а особливо deep tech структур, компетентності з цифрового підприємництва є якщо не ключовими, то дуже важливими. Ринок освіти також зазнає змін, але університетська освіта дуже повільно реагує на цифрові процеси. У статті запропоновано метод оцінювання рівня сформованості компетентностей студентів економічних спеціальностей у сфері навчання цифрового підприємництва на основі м'яких обчислень, а також сформульовано ключові базові компетентності, що виникають під час проходження онлайн-курсу з цифрового підприємництва, які ґрунтуються на останніх тенденціях розвитку у сфері ІТ. Обговорюються можливості щодо використання моделі для закладів вищої освіти. Запропонована математична модель має властивість універсальності та може бути застосована для отримання базових статистичних вибірок рівня набуття компетентностей на основі онлайн-курсів у різних галузях реального сектору економіки.

Ключові слова: цифрова економіка; онлайн-курси; інновації в освіті; онлайн-освіта; онлайннавчання; агрегатор; цифровізація; підприємництво; інформатизація освіти.

INTRODUCTION

Today, in the digital era, in the age of high and deep we can clearly distinguish the main directions and, hence, main challenges, when it comes to socio-economic development as it is based on the technological progress. As the latter advances rapidly, society and a number of industries struggle to catch up. And the main problem is that some of those mentioned above industries are crucial in assuring said technological advance, namely: public scientific institutions and universities as sources of knowledge and “nurseries” of intellectual and human capital. Unfortunately, they appear to be stuck in the age of low-to-middle tech when humankind is actually advancing from high to deep tech [1]. Moreover, we observe significant changes in labour market, as well as required skills in science, R&D, engineering, IT, management, entrepreneurship etc. Those skills are transforming in accordance to a technological transformation of productive forces, at the same time, professional education lags behind. And, if the hard skills are more or less up to date, those are namely the soft skills, that remain fairly unevolved as they were way back in the industrial age. It is important to understand, that given progress demands interdisciplinary trained and advanced workforce (especially looking back on the number of prognoses, that promise total automation in the future several decades), no matter the industry or a role, especially when it comes to deep tech startups. Meaning, an economist with no engineering background and data-analysis skills is not in demand already today. And vice-versa, an engineer with no entrepreneurial skills is potentially set to be left behind the labour market in the near future.

Problem statement. The ever-growing use of digital technologies in education today is one of the most important and sustainable trends when it comes to development of the global and globalised educational process, no matter, whether to satisfy high or deep tech conditions. Digital technologies make it possible to intensify the educational process, make it mobile and inclusive, differentiated and adapted to modern realities. And above all, digital technologies are the ones responsible of ensuring the continuity of education in the conditions of pandemics, military armed conflicts and other crises [2].

Key technological trends in the digital economy include:

- widespread adoption of intelligent sensors in machinery and production lines (technologies associated with the Industrial Internet of Things);

- shift towards unmanned manufacturing and the widespread implementation of robotics;

- transition from in-house data storage and computing to the utilization of distributed resources (referred to as 'cloud' technologies);

- complete automation and integration of production and management processes into a unified information system (from equipment to administrative levels);

- leveraging the collected data (both structured and unstructured) for analytical purposes (commonly known as 'big data' technologies);

- move towards digitized technical documentation and electronic document management (embracing 'paperless' technologies);

- digital design and modelling of the technological processes, objects, and products throughout their entire lifecycle, spanning from conception to operation (accomplished through engineering software);

- employing technologies that build materials up instead of cutting them away (referred to as 'additive' technologies or 3D printing);

- utilizing services for automated ordering of consumables and raw materials for product manufacturing, along with the automatic delivery of finished products directly to consumers, bypassing intermediaries;

- integrating unmanned technologies into the transportation systems, including the distribution of industrial goods;

- applying mobile technologies for the monitoring, control, and management of production processes.

Over a decade ago, started the Industry 4.0 movement in Ukraine and it remains strong and growing ever since. Said movement promotes the digitization when it comes to the processes that cover the entire chain of products creation, transition to smart production and the business models transformation. As of recent, the so-called platform of industrial and hi-tech sectors Industry4Ukraine operates in the country, consisting of more than 30 industrial and business associations. The concept of Industry 4.0 Centres (hereinafter - Centres 4.0) was initiated in 2018 by the Association of Industrial Automation Enterprises of Ukraine. It was supported by the Ministry of Education and Science of Ukraine. Such centres are considered to be one of the main tools in the progression of the fourth industrial revolution in the country. In 2018 first two Centres 4.0 were founded in two major Ukrainian business-industrial regional capitals: Kharkiv and Odesa. The national Centre 4.0 opened in 2019 on the base of the largest university of Ukraine - Igor Sikorsky Kyiv Polytechnic Institute. It provides the coverage of a wide spectrum of Industry 4.0 development. Later that year, Industry4Ukraine platform was launched.

Overall DeepTech and AI Ecosystem in Ukraine comprises of 26 hubs and 450 companies in marketing, fintech, transportation & drones, computer vision, 3D services, education, healthcare, blockchain, agriculture, etc. The dominant share among all belongs to software development with almost 34% of operational markets, located in Ukraine (just over 70%), US (16,2%), Europe (8,8%) and UK (3,2%). And even if Ukrainian DeepTech market grew considerably and with quite a stable rate for the past decade, especially in the last five years, there is still a number of problems to be resolved, namely [3]:

- The need for solid educational ground in AI & ML field

- Ukrainian AI market requires managers with fundraising experience

- The need of network-based industry events

- Absence of defined specialization of Ukrainian AI market

- Absence of market-focused analytical and investment platforms

It is also important to point out the lack of governmental incentive and week infrastructure, when it comes to dealing not only between start-ups and potential investors, but what is more important, between the whole education-entrepreneurship-government ecosystem. Thus, companies as well as government often experience a lack of the appropriate workforce, entrepreneurs are often not equipped enough with the need knowledge to start and properly grow their business, and educational institutions often lag in catching up with the labour market and the development of the needed skills, that come in handy in present-day economy.

Thus, as an important part of policymaking within Industry 4.0 development and especially within the framework of DeepTech progress, it is crucial to understand the rate with which the specific digital competencies are forming by the future workforce within the educational system. Especially important nowadays is forming the competencies in the field of information technologies and digital entrepreneurship. It is in this regard, the theoretical and methodological issues of diagnosing competence parameters of human resources in the aspect of society's readiness for a digital transformation become relevant.

Analysis of recent research and publications. The issue of developing the models for evaluating digital entrepreneurship competencies was once considered by various researchers. Thus, in studies [4], entrepreneurial experience of students was analysed. Conducted theoretical research suggests that researchers argue in favour of not treating the students as a homogeneous group. But rather, one should adapt the teaching strategies, as well as, educational content in order to satisfy the variety of educational needs.

The study [5] proposes a training model for the development of entrepreneurial potential. Given model combines the stages of the start-up process along with e-education methodologies that emerged from surveys of higher education students and young entrepreneurs.

The paper [6] analyses the European models that offer areas and indicators within entrepreneurial and digital competencies. Here authors propose the "EmDigital" model, which covers 4 areas, 15 sub-competencies and 45 indicators for the development of descriptive and attestation tests.

J. Nabi and R. Holden [7] argue that graduate education in the field of entrepreneurship is a complex process and remains insufficiently researched. However, they were able to confirm that the relationship between education, training, intention, and the actual choice of career actually exists. Although there is no one-size-fits-all approach to study the entrepreneurship practices that work for all majors and satisfy the different contexts that require individual approaches and, hence, suit the individual needs of students the best.

In [8] it is emphasized on the expediency of implementing the uniform basic requirements that cover all employees, regardless their role in the company. This was justified by the fact that world practice shows the benefit of targeting the efforts of each employee on the company's strategy. [9, 10] depicts the actual adjustments that were introduced to an undergraduate digital innovation course project, called Innovation Farm (IF), in response to the pandemic. Designed as an in-person course project, IF requires students to create AI-powered Android apps to address the important social issues.

V. Kovalenko, M. Marienko, and A. Sukhikh [10] study the Ukrainian experience in implementing the distance and blended teaching in general educational institutions, schools and universities alike. Moreover, they analyse the criteria, used to select the digital technologies alongside said process. Particular attention is paid to the issue of digitization in education during the pandemic and martial law, that required quite urgent transition of secondary education institutions to blended and distance teaching. Thus, M. Marienko and A. Sukhikh [11] describe the planning and organization of educational process by means of digital technologies during the state of martial law.

Given paper is aimed at developing a model for assessing the level of competences in digital entrepreneurship aquired by students majoring in economics and related fields. Presented model is based on soft computing and formulates the basic competencies that are formed during an online course in digital entrepreneurship. It also suggests several methods for obtaining the necessary competencies within the higher education system.

METHODOLOGY

Research is conducted, applying the general scientific and theoretical methods. Those among others include: analysis and synthesis of scientific, technical, and pedagogical literature on introducing the digital technologies in education, as well as development of digital economy and entrepreneurship; systemic, inductive, deductive approaches; interpretation of research results; as well as a practical approach, which includes research in the form of survey.

In order to satisfy the aim of the research, we construct a model, based on soft computing. All the competencies that were acquired by the students are sorted into four mastery levels: advanced, threshold, critical, below critical. Test results are formed into matrix, that is assessed with the introduction of a fuzzy variable. Next, the correspondence between the proposed levels of competence mastery and the variable n are established. The algorithm includes the following stages: 1) downloading test results; 2) connection of the "mastery_levels" dictionary, which displays the levels of the linguistic variable in the corresponding ranges of the values of belonging; 3) connecting the "balanced_values" dictionary to store balanced values (P_j) for each competency; 4) the "calculate_mastery" function, which calculates the level of mastery and competence of each student based on the test results; 5) converting "mastery_data" into a new DataFrame "mastery_df" and printing the results.

RESULTS AND DISCUSSION

Digital transformation affects every industry and fundamentally alters the economy, social security, defence, healthcare, education, science, logistics, and more. Society and individuals also do not remain simple bystanders within the digital transformation processes. The digital economy is becoming a major driver for improving the social and economic life of society and comprehensive use of Internet technologies to improve various processes related to human life.

Rapid technological progress opens a wide range of opportunities for the digital transformation of economic relations and as the result we observe the emergence and proliferation of HighTech and DeepTech. Digital tech allows to automate the business operations, which in turn increases their efficiency and productivity, opens up new opportunities, affects the development of entrepreneurship, and contributes to the formation of new products and management models. That is, within the Industry 4.0 framework, we experience the development of smart production, which uses cyber-physical systems (CyberPhysical Systems CPS) and the Internet of Things (Internet of Things, IoT) to increase the efficiency of industry and service sector.

In 2025, 50% of the world economy is expected to accelerate (or to be in the process of actively implementing) the digital transformation in order to increase the efficiency for the long-term growth. The developed countries of the world are rapidly developing innovative digital technologies dominated by digital platforms, artificial intelligence, and robotics. That is, digital solutions to power decarbonisation; use of the digitization and data harnessing to solve the global problems; the paradigm shift in connectivity to increase the global resilience; etc. According to the World Economic Forum, 87% of businesses will feel the disrupt in appropriate industry caused by digital tech; additional $ 100 trillion in value added is expected from digital transformation in 2025; 20% fewer emissions are expected [12].

Digital skills today are no longer the exclusive domain of a select few. Nowadays it has become the basic competence of every person out there; a must-have knowledge, without which it is more and more difficult to socialize, study or advance up the career ladder, even, as of latest, receive governmental services and various state-issued documents and certificates. It is hard to imagine how many millions of jobs are there in the world, that require advanced digital competencies and skills - big data, cyber security, programming, IoT; as well as how many jobs are there, that require obtaining the basic digital competencies - and the latter are several times more in number. Thus, in the context of ever-growing need in evolving the digital skills, current investigation of digital learning methodologies for the development of entrepreneurial capacity among university students occupies a position of strategic importance.

Proposed model is developed with the purpose to fill in some blanks when it comes to understanding existing methodologies for evaluating the results of online courses that promote digital knowledge development, as well as resolve the lack of unified methodology in evaluating obtained skills, that are expected to benefit potential entrepreneurs. Moreover, our attention was paid to students of higher education institutions and young entrepreneurs. Universities are to play a significant role in technological and economic development, as they are basically the cornerstones of deep tech ecosystems.

Hence, entrepreneurial skills, developed while within the university training have to meet the conditions of current techno-economic order, and must coincide with the following features:

- High-tech companies are based on a cutting-edge technology and disruptive innovations;

- Deep tech innovations are of radical nature [13]:

- Deep tech companies are based on innovations, that require substantial scientific and engineering input, ground-breaking research, and high entrepreneurial risks;

- Deep tech start-ups usually have longer introduction and development periods, compared to other new IT-businesses, that use wide-known technology [14];

- R&D requires usually considerably heavier financing and well-developed entrepreneurial skills;

- Competencies in digital entrepreneurship are a must-have in a digital age, and within deep tech start-ups in particular.

In Table 1, we have identified the basic competencies for developing the strategic knowledge and skills in digital entrepreneurship at each corresponding stage of start-up creation and evolution, based on an in-depth literature review on the most widespread methodologies used in e-education, which was complimented with the results of a survey of entrepreneurs and students.

Table 1