Insights 4.0: Transformative learning in industrial engineering through problem‐based learning and project‐based learning

Abstract

This paper describes a methodological study carried out between 2018 and 2022, at Rey Juan Carlos University, focused on the subject monitoring and control systems within a master's program in Industrial Engineering. The study proposes an innovative teaching strategy using problem‐based learning and project‐based learning methodologies. The projects undertaken are based on Internet of Things (IoT) systems aimed at enhancing weather stations, services and facilitating real‐time decision‐making. Inspired by our experience in the development of Industry 4.0 projects, we have designed a methodological strategy for this subject that focuses on providing students with the necessary knowledge and skills in the field of Control and Monitoring Systems and the IoT to develop real monitoring and control systems. The approach emphasizes interdisciplinary problem‐solving, with students working collaboratively in stable teams. Throughout the 16‐week course, tasks of increasing complexity are completed, resulting in the development of a complete system. The practical approach of the course and its relation to real applications motivates students, resulting in better performance. The acquired techniques and skills from the course are broadly applicable across engineering disciplines.

Design and Assessment of an Active Learning-Based Seminar

“…Mz et al presented a seminar focused on problem-solving related to the role of sensor technologies and robots in the industry [32]. Rodriguez et al exposed a series of seminars aimed to introduce problem-based learning and project-based learning strategies to facilitate real-time decision making [33].…”