During the last two decades, profound technological changes have taken place around us, supported by disruptive advances, both on the software and hardware sides. An amalgamation of information, communication, and artificial intelligence is taking place, as well as the cross-fertilization of a wide range of concepts, referred to as the digital transformation. While the discussion on how to operationalize the new intelligent systems of the fourth industrial revolution, Industry 4.0, is still going on; the dominant characteristics of the fifth industrial revolution, Industry 5.0 – going beyond producing goods and services for profit – requires all to think and act differently. As a result of the convergence phenomenon, the boundaries between different disciplines are eroding, necessitating a thorough discussion on what engineering education should be like in the future. In this paper, after presenting a brief history of engineering education, the recent paradigm changes are discussed, which essentially stress that skills must prevail over degrees to deal with challenges posed by the trends of the fifth industrial revolution. Later, before concluding the paper four strategies are presented such as lifelong learning and transdisciplinary education (1), sustainability, resilience, and human-centric design modules (2), hands-on data fluency and management courses (3) and human-agent/machine/robot/computer interaction experiences (4).

在过去的二十年里，在软件和硬件方面的颠覆性进步的支持下，我们周围发生了深刻的技术变革。信息、通信和人工智能正在融合，以及广泛概念的交叉融合，被称为数字化转型。虽然关于如何操作第四次工业革命工业 4.0 的新智能系统的讨论仍在继续；作为第五次工业革命的主要特征，工业 5.0——超越为盈利而生产商品和服务——要求所有人以不同的方式思考和行动。由于趋同现象，不同学科之间的界限正在被侵蚀，需要彻底讨论未来工程教育应该是什么样子。本文在简要介绍了工程教育的历史后，讨论了最近的范式变化，主要强调技能必须胜过学位，以应对第五次工业革命趋势带来的挑战。之后，在结束本文之前，提出了四种策略，例如终身学习和跨学科教育 (1)、可持续性、弹性和以人为本的设计模块 (2)、实践数据流畅性和管理课程 (3) 以及人类代理/机器/机器人/计算机交互体验（4）。从本质上讲，要应对第五次工业革命趋势带来的挑战，技能必须胜过学位。之后，在结束本文之前，提出了四种策略，例如终身学习和跨学科教育 (1)、可持续性、弹性和以人为本的设计模块 (2)、实践数据流畅性和管理课程 (3) 以及人类代理/机器/机器人/计算机交互体验（4）。从本质上讲，要应对第五次工业革命趋势带来的挑战，技能必须胜过学位。之后，在结束本文之前，提出了四种策略，例如终身学习和跨学科教育 (1)、可持续性、弹性和以人为本的设计模块 (2)、实践数据流畅性和管理课程 (3) 以及人类代理/机器/机器人/计算机交互体验（4）。