We Pretend to Have Some Solutions …But Do We Understand the Problematics as a Whole?

Journal Article (2025)
Author(s)

Imre Horváth (TU Delft - Cyber-Physical Systems)

Research Group
Cyber-Physical Systems
DOI related publication
https://doi.org/10.1177/10920617251346927
More Info
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Publication Year
2025
Language
English
Research Group
Cyber-Physical Systems
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Abstract

Engineering education is an evergreen challenge. It is supposed to follow the scientific progression, aggregation of knowledge, development of technologies, industrial demands, social trends, personal interests, affordances of computerization, evolution of educational practices, and so forth. From time to time, it must renew itself to comply with the changing situations, growing complexities, and quality expectations. The presented work was driven by the conjecture that next-generation engineering education (NG-EE) cannot be designed and implemented without understanding it as a holistic problematics. Therefore, this article attempts to consider the whole of engineering education and make propositions concerning its probable future based on a survey of the current literature and the author's long-term experiences. It is structured according to five fundamental questions: (i) Why is innovation in engineering education a challenging problematics (again)?; (ii) What are the currently typical approaches to engineering education?; (iii) What can be utilized as enablers for NG-EE?; (iv) What can we expect from the offerings of generative artificial intelligence tools?; and (v) What sort of new mind-set is needed for NG-EE? The main findings of the literature survey are discussed in detail, and propositional answers are formulated to these questions. It is advocated that NG-EE (i) is becoming increasingly transdisciplinary, (ii) needs novel conceptual models, methodological frameworks, and management scenarios, (iii) should impose a holistic rather than a reductionist view on systems, (iv) should consider increased diversification of engineering jobs, (v) should equip with the competencies of autonomous learning, and (vi) should offer a constructive but critical attitude to using artificial intelligence technologies.