The correlation between learning and teaching technologies is multidimensional and complex, thus, the digital tools that can help students turning information into knowledge define the crucial role of pedagogical practice. Open access to hardware and software tools is a focal point for advancing learning. In sciences, lab-based experiments constitute a vital part of curricula that bridge the gap between theory and practice. Access to remote lab tools is possible by pairing simulators, emulators and actual equipment, located in various geographical locations. Under this premise, Education 4.0 defines a new learning framework aligned with the fourth industrial revolution digital requirements. These constitute smart sensors, Artificial Intelligence (AI) and Robotics. In this context, University graduates need to prepare themselves with complex problem solving and interdisciplinary problems. To this end, contemporary Science, Technology, Engineering and Mathematics (STEM) teaching practices should be present along the way. Digitally competent students need to learn from a modern and adjustable curriculum tailored to cover necessary skills related to Internet of Things (IoT). Therefore, the digitization of University campuses, including smart IoT, Information and Communication Technology (ICT) and Fifth Generation (5G) automation infrastructures is necessary. In this work, we carry out an extensive STEM oriented survey which highlights and categorizes all contemporary digital tools and technologies needed to support future graduates. Moreover, we focus on contemporary pedagogical and didactic approaches to support Education 4.0 skills. We match contemporary methods with lab types, expected learning outcomes and open software and hardware tools, as imposed by the Education 4.0 framework. Our scenarios mainly focus on University education and consider smart sensors, IoT, 5G technologies, which are the basic building components for students’ digital competencies to meet Education 4.0 requirements.

The continuous evolution of Internet of Things (IoT) technologies presents significant opportunities and challenges within the domain of engineering education. This paper introduces a novel and comprehensive framework that extends the established Engineering Design Process (EDP) by incorporating a modular Digital Twin (DT) structure specifically tailored to smart building IoT applications in education. Unlike previous approaches, our framework enables real-time system feedback, simulation-based design iteration, and hands-on experimentation—all integrated within a pedagogical flow aligned with engineering curricula. It comprises seven distinct phases, providing a complete methodology that guides learners from fundamental concepts to advanced applications, including data visualization, real-time simulation, and system optimization. To demonstrate the applicability of the proposed framework, we design and experiment with a practical use case related to a meteorological station and data, which incorporate IoT-enabled sensors, actuators, and microcontrollers for real-time monitoring of environmental parameters and energy consumption within a smart building campus facility. Additionally, to support EDP extension, a hybrid pedagogical approach is introduced, which combines traditional engineering hands-on education methodologies with DT activities, to further foster experimental learning, iterative system design, and complex systems thinking development. To this end, our approach aims to bridge the gap between theoretical science and engineering knowledge, along with practical application use cases, contributing to a better preparation of future engineers capable of addressing interdisciplinary challenges associated with smart systems and digital transformation within the Industry 4.0 era.

Presents corrections to the paper, (Correction to “Digital Tools, Technologies, and Learning Methodologies for Education 4.0 Frameworks: A STEM Oriented Survey”).