Artificial Intelligence Aided Engineering Education: State of the Art, Potentials and Challenges

Martín Núñez, José Luis ORCID: https://orcid.org/0000-0002-4102-6069 and Díaz Lantada, Andrés ORCID: https://orcid.org/0000-0002-0358-9186 (2020). Artificial Intelligence Aided Engineering Education: State of the Art, Potentials and Challenges. "International Journal of Engineering Education", v. 36 (n. 6); pp. 1740-1751. ISSN 0949149X.

Descripción

Título: Artificial Intelligence Aided Engineering Education: State of the Art, Potentials and Challenges
Autor/es:
Tipo de Documento: Artículo
Título de Revista/Publicación: International Journal of Engineering Education
Fecha: 20 Marzo 2020
ISSN: 0949149X
Volumen: 36
Número: 6
Materias:
Palabras Clave Informales: Artificial Intelligence; Engineering Education; ethical issues; optimization of resources; Project-based learning; Service learning; System
Escuela: E.T.S.I. Industriales (UPM)
Departamento: Ingeniería Mecánica
Licencias Creative Commons: Reconocimiento - Sin obra derivada - No comercial

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Resumen

Artificial intelligence (AI) is already starting to transform the way engineering systems are conceived, designed and managed, helping to maximize the chances of successfully achieving their goals. Engineering science, technology and research clearly benefit from AI and engineering educators should be able to make students aware of its potentials, teach them the necessary fundamentals of this field of study and guide them through the application of these algorithms and technologies to the development of real engineering projects, as necessary aspects in modern engineering programmes of study. However, the more relevant impact of artificial intelligence in engineering education goes beyond the application of a set of novel resources to solving specific engineering problems: In fact, the concept of artificial intelligence-aided engineering education'' refers to utilizing artificial intelligence techniques and resources for improving the teaching-learning process in higher education, especially in connection with scientific-technological studies. In this study, we concentrate on how AI techniques can support the teaching-learning process in engineering and we describe how AI can be swiftly introduced into any engineering programme. We also analyze the potential impact of AI on improving the overall operation of universities, as extremely complex systems managing myriads of data and countless processes and interactions.

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