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Proces digitalne transformacije zahvata sve segmente društva. Od proizvodnje, pružanja usluga, kanala komunikacije i distribucije informacija, sve do institucija visokoškolskog obrazovanja i promena u procesu učenja. Kako bi se proces digitalizacije sproveo, neophodno je identifikovati da li se posmatrano okruženje može prilagoditi ovom tehnološkom napretku. Ovaj rad predstavlja istraživanje digitalnog okruženja za učenje na Fakultetu tehničkih nauka u smeru identifikovanja i definisanja svih njegovih koncepata na osovu kojih se predlaže model savremenog digitalnog okruženja za učenje.

Although previous research on the e-learning system acceptance has been conducted using UTAUT, no study followed the longitudinal approach. Accordingly, this research examines the engineering students' (N = 291) elearning system acceptance by three years of study. The structural equation modelling analysis confirmed UTAUTrelationships in each year. Effort expectancy and social influence resulted as significant predictors of behavioural intention in all three years. In contrast, performance expectancy influence got lower in later usage. Altogether, our longitudinal study presented that the UTAUT model has weakened over time. Therefore, we propose extending the UTAUT model in future research to better understand user satisfaction and positively contribute to system acceptance. Our research findings can be used for university leaders to investigate and evaluate any implemented information system acceptance through the years.

We are witnessing how digital technologies can be used to transform everyday life – launch new or grow incumbent companies, change teaching and learning environment, and research. The latest literature research has overwhelmingly positively assessed the use of digital technologies in higher education, indicating certain challenges in this regard. In the modern era, higher education institutions need to evolve steadily, following the digital transformation. Overall, the emphasis is on the encouragement and promotion of digital technology in the learning process. However, a small number of research papers addressed the learning environment’s digital transformation in the past decade. With the aim of contributing to a relevant topic, this paper presents a systematic literature review of related articles published on learning environment digital transformation in ten years. Accordingly, significant and eminent results are discussed, together with guidelines for future research.

This study investigated the crucial factors for measuring the success of the information system used in the e-learning process, considering the transformations in the work environment. This study was motivated by the changes caused by COVID-19 witnessed after the shift to fully online learning environments supported by e-learning systems, i.e., learning emphasized with information systems. Empirical research was conducted on a sample comprising teaching staff from two European universities: the University of Novi Sad, Faculty of Technical Sciences in Serbia and the Polytechnic Institute of Castelo Branco in Portugal. By synthesizing knowledge from review of the prior literature, supported by the findings of this study, the authors propose an Extended Information System Success Measurement Model—EISSMM. EISSMM underlines the importance of workforce agility, which includes the factors of proactivity, adaptability, and resistance to change, in the information system performance measurement model. The results of our research provide more extensive evidence and findings for scholars and practitioners that could support measuring information system success primarily in e-learning and other various contextual settings, highlighting the importance of people’s responses to work environment changes.

In recent years the Internet of Things, in addition to use cases in 'smart cities', has also increasingly been used in precision agriculture. As in the rest of the world, it has been a growing reality in Portugal. In an agricultural environment, where energy resources can be scarce and dispersed, the implementation of a LoRa network with autonomous sensor nodes must consider the limitations imposed by the energy consumed by the sensor node, when powered by a battery and a solar panel. For this, experimental tests must be carried out so that there is enough data for the implementation and optimization of the devices. This article presents a work focused on the study of the autonomy and energy efficiency of the sensor device, using algorithms capable of managing energy consumption as a function of the luminosity of the place. Preliminary results attest to the relevance of this approach, keeping the sensor node in operation without interruptions.