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Data Science and Machine Learning Teaching Practices with Focus on Vocational Education and Training

Authors :
Gorjan Nadzinski
Branislav Gerazov
Stefan Zlatinov
Tomislav Kartalov
Marija Markovska Dimitrovska
Hristijan Gjoreski
Risto Chavdarov
Zivko Kokolanski
Igor Atanasov
Jelena Horstmann
Uros Sterle
Matjaz Gams
Source :
Informatics in Education, Vol 22, Iss 4, Pp 671-690 (2023)
Publication Year :
2023
Publisher :
Vilnius University, 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.

Details

Language :
English
ISSN :
16485831 and 23358971
Volume :
22
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Informatics in Education
Publication Type :
Academic Journal
Accession number :
edsdoj.0cc7205b58814c32bd84f4755c90bf82
Document Type :
article
Full Text :
https://doi.org/10.15388/infedu.2023.28