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2023-08-29

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Vol. 8 No. 2 (2023)

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Research Articles

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How to Cite

Rožman, M., Tominc, P., & Vrečko, I. (2023). Building skills for the future of work: Students’ perspectives on emerging jobs in the Data and AI Cluster through artificial intelligence in education. Environment and Social Psychology, 8(2). https://doi.org/10.54517/esp.v8i2.1670

Building skills for the future of work: Students’ perspectives on emerging jobs in the Data and AI Cluster through artificial intelligence in education

Maja Rožman

Faculty of Economics and Business, University of Maribor

Polona Tominc

Faculty of Economics and Business, University of Maribor

Igor Vrečko

Faculty of Economics and Business, University of Maribor


DOI: https://doi.org/10.54517/esp.v8i2.1670


Keywords: education, students, artificial intelligence, statistics, quantitative methods

Abstract

The main goal of this paper is to supplement the existing literature with new knowledge in the field of artificial intelligence and education, which relates to the importance of courses in statistics, quantitative methods, and students’ perspectives about emerging jobs in the Data and AI Cluster. A multidimensional model of the perceived usefulness of artificial intelligence in students’ perspective about emerging jobs in the Data and AI Cluster was formed; it includes constructs students’ knowledge of the meaning of “artificial intelligence”, their perception of its usefulness in their studies, the perceived ease of use of AI, the perceived usefulness of statistics and quantitative methods, students’ perspective on work skills for the future, and their perspective on emerging jobs in the Data and AI Cluster. The empirical research included 197 undergraduate and postgraduate students from the University of Maribor, Faculty of Economics and Business in Slovenia, who had prior knowledge of statistics obtained during their studies. The data were analyzed using structural equation modeling. The main findings of our research are important for curricula development and stress these implications: emphasis on teaching the meaning and importance of AI, integration of AI in coursework, strengthening quantitative skills and developing future work skills that are aligned with emerging trends in the Data and AI Cluster.

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