Using cluster analysis for revealing gender equality patterns in EU ICT education and employment

Using cluster analysis for revealing gender equality patterns in EU ICT education and employment

V. Tokar; D. Tyshchenko; T. Franchuk; V. Makoiedova; A. Lotariev

Women are underrepresented in all aspects of ICT, including education and employment. This issue can be attributed to a lack of encouragement and opportunities for women to pursue ICT careers, as well as implicit biases and stereotypes leading to women being overlooked for roles in the industry. Cluster analysis is a useful tool for analyzing and grouping data to identify patterns and trends. This article aims to investigate the state of gender equality in information and communication technology education and employment across the European Union member-states using cluster analysis. The study uses data from the Eurostat to determine the female to male ratios of new bachelor entrants studying information and communication technologies, as well as employees working in the ICT in EU member-states. The article distinguishes gender equity leaders, adopters and laggards among EU member-states. The data was organized into six clusters of EU memberstates with a focus on gender equality among those who enter into bachelor-level ICT programs and are employed in the field. Moreover, the article examines the ratio of female to male enrolled in information technology in Ukraine analyzing the case of the State University of Trade and Economics. It was found that the ratio of female to male does not have a stable upward trend. The article proposes some initiatives aimed at increasing the number of girls and women in ICT. This study provides valuable insights into the current state of gender equality in the ICT sector across EU member-states. The findings of this study can inform policymakers and stakeholders in developing targeted interventions to address gender inequality in the ICT sector. This will promote a more inclusive and diverse ICT workforce, which is essential for economic growth and social development.

Keywords: Cluster Analysis, EU member-states, Female Empowerment, Gender Equality, Information Communication Technology, Gender Diversity Management

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