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Data Science and Machine Learning Teaching Practices with Focus on Vocational Education and Training
Volume 22, Issue 4 (2023), pp. 671–690
Gorjan Nadzinski   Branislav Gerazov   Stefan Zlatinov   Tomislav Kartalov   Marija Markovska Dimitrovska   Hristijan Gjoreski   Risto Chavdarov   Zivko Kokolanski   Igor Atanasov   Jelena Horstmann     All authors (12)

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https://doi.org/10.15388/infedu.2023.28
Pub. online: 15 December 2023      Type: Article     

Published
15 December 2023

Abstract

With the development of technology allowing for a rapid expansion of data science and machine learning in our everyday lives, a significant gap is forming in the global job market where the demand for qualified workers in these fields cannot be properly satisfied. This worrying trend calls for an immediate action in education, where these skills must be taught to students at all levels in an efficient and up-to-date manner. This paper gives an overview of the current state of data science and machine learning education globally and both at the high school and university levels, while outlining some illustrative and positive examples. Special focus is given to vocational education and training (VET), where the teaching of these skills is at its very beginning. Also presented and analysed are survey results concerning VET students in Slovenia, Serbia, and North Macedonia, and their knowledge, interests, and prerequisites regarding data science and machine learning. These results confirm the need for development of efficient and accessible curricula and courses on these subjects in vocational schools.

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Open access article under the CC BY license.

Keywords
education machine learning data science vocational education and training survey

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INFORMATICS IN EDUCATION

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