Digitalization and Innovation Transfer as a Leadership Trend in Education: Bibliometric Analysis and Social Analytics

Vitaliia Koibichuk (), Anastasiia Samoilikova () and Tetiana Vasylieva ()
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Vitaliia Koibichuk: Sumy State University
Anastasiia Samoilikova: Sumy State University
Tetiana Vasylieva: Sumy State University

Chapter Chapter 17 in Leadership, Entrepreneurship and Sustainable Development Post COVID-19, 2023, pp 233-247 from Springer

Abstract: Abstract Today, digitalization is both an important direction and a significant result of the transfer of innovation. It has covered all spheres of modern life, and education is no exception. Moreover, the COVID-19 pandemic has significantly affected the transformation of learning around the world. Thus, the main purpose of this chapter is to determine key trends in learning transformation in the context of digitalization and innovation transfer as a leadership trend in education based on bibliometric and cluster analysis and social analytics. To achieve this target, the bibliometric analysis of indexed scientific papers by the Scopus database, the comparative and quantitative analysis of statistical metrics were made using ScientoPy software and Python language. The number of publications devoted to research of development and features of the e-learning market has increased rapidly over the past 2 years (2020–2021), almost three times compared to 2016–2020. The growing use of artificial intelligence and machine learning in the e-learning system stimulates the mastery of digitalization tools in education. This chapter presents the dynamics of the market of electronic educational services in accordance with statistical data and the results of the forecast of the leading research and consulting company, the advantages of e-learning, and the most used of them, and disadvantages and problems of distance learning. Comparative characteristics of indicators of infrastructure, access, opportunities, and barriers are studied for Poland, Ukraine, Germany, and Cyprus. Also, there is the cluster analysis of the median values of countries’ web behavior in relation to online learning. It was performed using the Ward’s method and Agglomeration scheme in Statgraphics 19 software based on IEEE data set from 20 countries and Google Trends analytics for the 18 years period. Six clusters of countries that have similar web behavior related to online learning were determined. The received results can be used by state and local authorities and scientific and educational institutions for the further development and improvement of e-learning technologies to strengthen leadership in education.

Keywords: Artificial intelligence; Distance learning; e-learning; Leadership in education; Web behavior (search for similar items in EconPapers)
JEL-codes: D83 I21 O31 (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/978-3-031-28131-0_17

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