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AI Pioneers: Developing a Community of Practice for Artificial Intelligence (AI) and Vocational Education and Training

Authors: Attwell, Graham; Deitmer, Ludger; Bekiaridis, George;

AI Pioneers: Developing a Community of Practice for Artificial Intelligence (AI) and Vocational Education and Training

Abstract

This paper examines the implications of VET and for VET of digital and sustainable socio-economic development. It examines the dual challenge of AI as a tool for teaching and training in VET but also as a subject for learning in VET. It quotes UNESCO (2022) in saying AI has the potential to accelerate the process of achieving the global education goals through reducing barriers to accessing learning, automating management processes, and optimising methods to improve learning outcomes. It. Looks at current advances in AI including their potential impact on work organisation, work tasks and business processes and the potential and challenge for education and the research and social challenges this poses for research in Vocational education and Training. The research suggests everyone needs to be able to recognize AI and its influence on people and systems, and be proactive as a user and citizen. VET students should have the opportunity to use AI and big data to solve problems, for instance maintaining systems in the mechatronic occupations. Thirdly, VET dual students (higher level apprentices) should become skilled in computer science for developing AI systems. The paper goes on to examine the new skills and competencies needed by VET teachers and trainers and professional development requirements. It concludes with the aims of the Erasmus Plus AI Pioneers project to develop a community of practice around AI in VET.

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Keywords

VET students, vocational education and training, VET teachers, Artificial Intelligence (AI)

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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