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.

Computational Pedagogy is an instructional approach based on Computational Science and the Computational Experiment as well as on the CPACK model. Computational Science in Education engages students in computational modeling and simulation technology in alignment with the essential features of Inquiry based teaching and learning approach and the Computational Thinking dimensions (practices and skills). STEAM –content based epistemology- education is connected to Computational Pedagogy through the Computational Experiment leading to a proposed model called ‘Computational STEAM Content Pedagogy’ as a teaching and learning approach which can be implemented in a STEAM holistic interdisciplinary/trans-disciplinary epistemology approach to the curriculum for solving real computational problems.

Popular interest in robotics has increased significantly over the last years. It has been claimed that robotics can provide new benefits to the learning process at all levels of education. The main ideas of the present study adhered to the constructionist theory, according to which the learning process is not only transmitted from teacher to pupil, but rather constructed in the mind of the pupil in the form of active learning. The purpose of the present study was to implement a robotic toy (Lego Mindstorms NXT ^TM) in a Greek primary school, in order to teach twelve year-old children some of the basic concepts of geometry. The main hypothesis of the present study was that children who used the Lego Mindstorms NXT platform would score higher on an evaluation questionnaire than children who formed the control group. Descriptive statistical analysis was performed in order to evaluate the correct answers of the questionnaires. Statistical analysis revealed that children who participated in the experimental group performed better in the 21 items of the questionnaire. Moreover, they mentioned that the geometry course became more interesting and drew their attention in comparison to the courses that were taught through the standard teaching process. It is apparent that the present study follows the line of inquiries that supports that robotics can make a significant impact to education. Robots can be a tool that can enhance the skills of children.

Vehicle-to-everything (V2X) communications is an emerging branch of wireless communications and has recently gained a lot of interest not only from academia but also from the automotive and telecommunications industry. An important feature of V2X telecommunication systems is that the communication quality varies quickly in time due to the high mobility of the transceivers and due to the rapid change in the fading characteristics of the communication medium. For this reason, it is vital to maintain tolerable quality of service (QoS) in a V2X communication environment, in terms of communication reliability, power, end-to-end latency, data rate, communication range, throughput and vehicle density. A significant impact on the quality parameters of the system has been the coding scheme used by the V2X telecommunication system. For this purpose, we examine the effect that popular coding schemes have on the QoS of a V2X communication system. More specifically, the impact of fourth-generation long-term evolution (4G-LTE) turbo codes, fifth-generation new radio (5G-NR) polar codes and 5G-NR low-density parity-check codes (LDPC) on the QoS parameters of a V2X communication system is researched. Το this end, we employ stochastic V2X propagation models that simulate every possible V2X channel state and traffic environment, based on the third-generation partnership project (3GPP) Release 16 specifications. These propagation models form the basis of our study, since through them, at a first level, we analyze the frame error rate (FER) performance for different levels of signal-to-noise ratios (SNRs) for all the aforementioned coding schemes and 128-bit V2X-compatible data frames, and, at a second level, we investigate the impact of these propagation models and coding schemes on the V2X QoS parameters. Our analysis shows that turbo-based coding schemes satisfy all the QoS parameters and achieve overall communication quality comparable to polar and better than LDPC, making them suitable for small-frame 5G V2X services.