Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/32021
Title: Data Science and Machine Learning Teaching Practices with Focus on Vocational Education and Training
Authors: Nadzinski, Gorjan
Gerazov, Branislav 
Zlatinov, Stefan
Kartalov, Tomislav 
Dimitrovska, Marija Markovska
Gjoreski, Hristijan
Chavdarov, Risto
Kokolanski, Zivko
Atanasov, Igor
Horstmann, Jelena
Sterle, Uros
Gams, Matjaz
Issue Date: 19-Apr-2023
Publisher: Vilnius University Press
Journal: Informatics in Education
Abstract: <jats:p>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.</jats:p>
URI: http://hdl.handle.net/20.500.12188/32021
DOI: 10.15388/infedu.2023.28
Appears in Collections:Faculty of Electrical Engineering and Information Technologies: Journal Articles

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