Technequality - Education systems and requirements - Analysing the relationship between initial education and skills acquisition across countries: Schools, Educations Systems and the Acquisition of Skills Relevant to the Future of Work

Technological innovations such as AI and robotization change task composition in occupations in many sectors of the economy. Machines are increasingly able to autonomously perform tasks that were long thought to be exclusively reserved for humans, including reading, writing, recognizing patterns, strategizing, and complex decision-making. Consequently, the task content of many jobs will change and technological innovations will lead to a shift in skills demands on the labor market. It is not completely
clear yet which skills today’s youth need to acquire to be productive on the labor market of tomorrow, but proficiency in skills that allow future workers to work with, build, or complement machines, are generally assumed to contribute to their productivity and employability. The question remains how such skills are best taught, and what roles schools and education systems play. In this paper we analyze the relationship between education systems and the acquisition of skills that are relevant for one’s employability during the Fourth Industrial Revolution. We assess the extent to which education systems and schools in European countries effectively support the acquisition of relevant skills, including (a) information processing skills, (b) creative problem-solving skills, and (c) computer skills. Analyses of these different aspects of skill acquisition, enhancement and utilization in times of accelerated technological change will also address inequality by gender, family context, and ethnic groups. We examine cross-national inequalities in the acquisition of computing and problem-solving skills by
parents’ socioeconomic status, ethnicity, and gender. We analyze data from PISA and the International Computer and Information Literacy Study (ICILS), and PIAAC using random slope multilevel analyses with cross-level interactions.