TY - JOUR
T1 - Training and Preparing Tomorrow’s Workforce for the Fourth Industrial Revolution
AU - Bühler, Michael Max
AU - Jelinek, Thorsten
AU - Nübel, Konrad
N1 - Publisher Copyright:
© 2022 by the authors.
PY - 2022/11
Y1 - 2022/11
N2 - We call for a paradigm shift in engineering education. We are entering the era of the Fourth Industrial Revolution (“4IR”), accelerated by Artificial Intelligence (“AI”). Disruptive changes affect all industrial sectors and society, leading to increased uncertainty that makes it impossible to predict what lies ahead. Therefore, gradual cultural change in education is no longer an option to ease social pain. The vast majority of engineering education and training systems, which have remained largely static and underinvested for decades, are inadequate for the emerging 4IR and AI labour markets. Nevertheless, some positive developments can be observed in the reorientation of the engineering education sector. Novel approaches to engineering education are already providing distinctive, technology-enhanced, personalised, student-centred curriculum experiences within an integrated and unified education system. We need to educate engineering students for a future whose key characteristics are volatility, uncertainty, complexity and ambiguity (“VUCA”). Talent and skills gaps are expected to increase in all industries in the coming years. The authors argue for an engineering curriculum that combines timeless didactic traditions such as Socratic inquiry, mastery-based and project-based learning and first-principles thinking with novel elements, e.g., student-centred active and e-learning with a focus on case studies, as well as visualization/metaverse and gamification elements discussed in this paper, and a refocusing of engineering skills and knowledge enhanced by AI on human qualities such as creativity, empathy and dexterity. These skills strengthen engineering students’ perceptions of the world and the decisions they make as a result. This 4IR engineering curriculum will prepare engineering students to become curious engineers and excellent collaborators who navigate increasingly complex multistakeholder ecosystems.
AB - We call for a paradigm shift in engineering education. We are entering the era of the Fourth Industrial Revolution (“4IR”), accelerated by Artificial Intelligence (“AI”). Disruptive changes affect all industrial sectors and society, leading to increased uncertainty that makes it impossible to predict what lies ahead. Therefore, gradual cultural change in education is no longer an option to ease social pain. The vast majority of engineering education and training systems, which have remained largely static and underinvested for decades, are inadequate for the emerging 4IR and AI labour markets. Nevertheless, some positive developments can be observed in the reorientation of the engineering education sector. Novel approaches to engineering education are already providing distinctive, technology-enhanced, personalised, student-centred curriculum experiences within an integrated and unified education system. We need to educate engineering students for a future whose key characteristics are volatility, uncertainty, complexity and ambiguity (“VUCA”). Talent and skills gaps are expected to increase in all industries in the coming years. The authors argue for an engineering curriculum that combines timeless didactic traditions such as Socratic inquiry, mastery-based and project-based learning and first-principles thinking with novel elements, e.g., student-centred active and e-learning with a focus on case studies, as well as visualization/metaverse and gamification elements discussed in this paper, and a refocusing of engineering skills and knowledge enhanced by AI on human qualities such as creativity, empathy and dexterity. These skills strengthen engineering students’ perceptions of the world and the decisions they make as a result. This 4IR engineering curriculum will prepare engineering students to become curious engineers and excellent collaborators who navigate increasingly complex multistakeholder ecosystems.
KW - Artificial Intelligence (AI)
KW - Fourth Industrial Revolution (4IR)
KW - didactics
KW - emerging educational technologies
KW - ethics
KW - future of education
KW - future of engineering
KW - future of work
KW - game-based learning
KW - gamification
KW - metaverse
KW - online learning
KW - serious games
KW - skills gap
UR - http://www.scopus.com/inward/record.url?scp=85141787421&partnerID=8YFLogxK
U2 - 10.3390/educsci12110782
DO - 10.3390/educsci12110782
M3 - Review article
AN - SCOPUS:85141787421
SN - 2227-7102
VL - 12
JO - Education Sciences
JF - Education Sciences
IS - 11
M1 - 782
ER -