Designing a Cyber-Physical-Systems and Human Factors Engineering Course for Industry 4.0

Claudia Lizette Garay-Rondero, Ricardo Thierry-Aguilera, Andreas Koch Schneider, Rafael E. Bourguet-Diaz, Maria Lule Salinas, Genaro Zavala

Resultado de la investigación: Contribución a los tipos de informe/libroContribución a la conferenciarevisión exhaustiva

Resumen

This research presents a novel methodology and instructional, curricular design for the Cyber- Physical Systems and Human Factors Engineering course for an Industrial Engineering program in Higher Education. The research proposal offers a Competency-Based Education Model, Challenge-based Learning, and Experiential Learning design to create a curricular adaptation to prepare the future workforce for Industry 4.0, driven by digital technologies and strengthening the structure of Education 4.0 in pandemic times. The curricular design was explored and implemented in a national Industrial Engineering virtual course in five different facilities of a Higher Education Institution. Five professors participated in the exploratory study with 265 students in four country regions. The quantitative analysis provided positive findings regarding knowledge delivery and student competency development, confirming the good practices and standards in the proposed curricular design methodology. The final student evaluation results for the course have been favorable. They emphasized the importance of developing skills and knowledge about the enablers and components of Industry 4.0, such as Cyber-Physical-Systems and machine learning. Moreover, they remarked on the importance of human factors to develop a more sustainable society. The research contributes new ideas and perspectives for professors and instructional designers to shape the future of Higher Education. Furthermore, these new research paradigms for competencies in educational innovation shape the emerging virtual and hybrid educational practices in the COVID-19 pandemic and post-pandemic era.

Idioma originalInglés
Título de la publicación alojadaFuture of Educational Innovation Workshop Series - Machine Learning-Driven Digital Technologies for Educational Innovation Workshop 2021
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781665427630
DOI
EstadoPublicada - 2021
Publicado de forma externa
Evento1st Machine Learning-Driven Digital Technologies for Educational Innovation Workshop 2021 - Monterrey, México
Duración: 15 dic. 202116 dic. 2021

Serie de la publicación

NombreFuture of Educational Innovation Workshop Series - Machine Learning-Driven Digital Technologies for Educational Innovation Workshop 2021

Conferencia

Conferencia1st Machine Learning-Driven Digital Technologies for Educational Innovation Workshop 2021
País/TerritorioMéxico
CiudadMonterrey
Período15/12/2116/12/21

Áreas temáticas de ASJC Scopus

  • Teoría computacional y matemáticas
  • Interacción persona-ordenador
  • Software
  • Redes de ordenadores y comunicaciones
  • Informática aplicada
  • Educación

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