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.

The teaching method of flipped classroom (FC), gives students the opportunity to participate actively during class, while the teacher’s role is supportive than intrusive. The application of FC improves teaching and learning process, especially in applied sciences and technology, as literature study reveals. The current study aims to investigate the application of Unified Theory of Acceptance and Use of Technology (UTAUT) methodology, by applied sciences and technology teachers, who combine FC to improve learning results and better meet their teaching goals. To this end, we apply quantitative research, exploit, and discuss our data findings. A total number of 65 high school teachers, around the area of Central Greece, in the region of Thessaly, took part in our research. Our data is analyzed via Structural Equation Models (SEMs)which belong to a family of multivariable statistical analysis that refer to linear correlations among quantitative mainly variables, with confirmatory role. The results of our study reveal that social influence is significant for the prediction of teachers’ intention (current of future) to apply flipped classroom model approach. Additionally, our study claims to support that flipped classroom model plays a crucial role in updating educational demands of the 21st century, especially in guaranteeing the use of technology tools in equally during teaching and learning process. Finally, this study may assist teachers to adjust and reinforce flipped classroom’s approach, by distinguishing the technology acceptance factors inside a contemporary classroom.

Today, the Vocational Education and Training (VET) curriculum in Greece is state-regulated, combining school-based and work-based learning, and it is offered at upper-secondary and post-secondary levels. There is a need to prepare a new agenda for VET in Greece that follows the rapid technological developments of today. Our paper aims to enrich, redefine, and expand the current curricula and educational practices while proposing a complete plan for the overall reformation of VET’s learning conditions from the point of view of teaching and learning analytics. Through the evaluation of the existing changing institutional framework, the updated bibliographic references, and the experiential data of the educational reality, we can understand the expected needs of technological educators and decide how to address the priorities that must be determined. We focus on the preparation of the trainers and the overall redefinition of the role of education in preparing graduates. This paper’s main conclusions offer interpretations for the cognitive orientation of the existing curricula, as well as direction for the thinking and teaching skills of teachers, to build confidence in the prospects of technical education in Greece.

The rapid development of connected devices and the sensitive data, which they produce, is a major challenge for manufacturers seeking to fully protect their devices from attack. Consumers expect their IoT devices and data to be adequately protected against a wide range of vulnerabilities and exploits. Successful attacks target IoT devices, cause security problems, and pose new challenges. Successful attacks from botnets residing on mastered IoT devices increase significantly in number and the severity of the damage they cause is similar to that of a war. The characteristics of attacks vary widely from attack to attack and from time to time. The warnings about the severity of the attacks indicate that there is a need for solutions to address the attacks from birth. In addition, there is a need to quarantine infected IoT devices, preventing the spread of the virus and thus the formation of the botnet. This work introduces the exploitation of side-channel attack techniques to protect the low-cost smart devices intuitively, and integrates a machine learning-based algorithm for Intrusion Detection, exploiting current supply characteristic dissipation. The results of this work showed successful detection of abnormal behavior of smart IoT devices.