The COVID‐19 crisis is having a significant impact on the quality of life and future of young people; it can also lead to disruption in education. A disruption would pose a severe threat to the entire society in the postcrisis period. Therefore, educational institutions must respond quickly and ensure the continuity of the educational processes. Our research goal has been to develop and implement a model enabling a rapid transition from the traditional to the distance learning model in a state of emergency. Our focus has been on conceiving technical, organizational, and pedagogical changes that educational organizations need to implement to enable different interaction methods, ensure continuity, and provide high‐quality education. We have defined and implemented a model, which is described in detail in this paper, thus giving guidelines for a rapid transition to distance learning, which is not restricted to the crisis times only. We have evaluated our approach by monitoring the IT solutions and surveying students and teachers at the School of Computing, Union University of Belgrade. The results indicate the high satisfaction of these participants in the educational processes. They imply the acceptability of prolonged distance learning, if needed, and embrace the hybrid education model for the next generation of students.

The academic and professional community has recently started to develop the concept of 6G networks. The scientists have defined key performance indicators and pursued large-scale automation, ambient sensing intelligence, and pervasive artificial intelligence. They put great efforts into implementing new network access and edge computing solutions. However, further progress depends on developing a more flexible core infrastructure according to more complex QoS requirements. Our research aims to provide 5G/6G core flexibility by customizing and optimizing network slices and introducing a higher level of programmability. We bind similar services in a group, manage them as a single slice, and enable a higher level of programmability as a prerequisite for dynamic QoS. The current 5G solutions primarily use predefined queues, so we have developed highly flexible, dynamic queue management software and moved it entirely to the application layer (reducing dependence on the physical network infrastructure). Further, we have emulated a testbed environment as realistically as possible to verify the proposed model capabilities. Obtained results confirm the validity of the proposed dynamic QoS management model for configuring queues’ parameters according to the service management requirements. Moreover, the proposed solution can also be applied efficiently to 5G core networks to resolve complex service requirements.

Purpose The purpose of this paper is to examine the usability of the dimensional view of data in the context of its presumed learnability. Design/methodology/approach In total, 303 participants were asked to solve 12 analytical problems in an experiment using the dimensional view of data for half of the problems and an operational view of data for the other half. Inferential statistics and structural equation modeling were performed with participants' objective results and affective reactions. Findings Showing that the order of exposure to the two views of data impacts the overall usability of ad hoc querying, the study provided evidence for the learnability potential of the dimensional view of data. Furthermore, the study showed that affective reactions to the different views of data follow objective usability parameters in a way that can be explained using models from affective computing research. Practical implications The paper proposes a list of guidelines for use of the dimensional view of data in business analytics. Originality/value This study is the first to confirm the learnability of the dimensional view of data and the first to take a deeper look at affective reactions to an ad hoc business analytics solution. Also, it is one of few studies that examined the usability of different views of data directly on these views, rather than using paper representations of data models.