The increasing integration of digital technologies in higher education raises important questions about their real pedagogical value in teaching practice. The aim of this research was to examine students’ attitudes about the use of digital technologies, their representation in teaching, and their influence on the perceived pedagogical value of teaching at the technical faculty, examined through correlational and regression analyses. The research also included an analysis of the relationships among digital technologies, student engagement, and students’ assessments of teachers’ digital competence, particularly under conditions of limited technical resources. The research was conducted on a sample of 375 students in engineering study programs. Data were collected using a structured questionnaire and analysed using exploratory factor analysis, reliability analysis of the measurement scales (Cronbach’s alpha and, for the two-item scale, the Spearman-Brown coefficient), correlation analysis and regression models. The results show that, although students generally have a positive perception of digital technologies and teachers’ digital competence, exposure to advanced digital tools in teaching remains limited. Student engagement showed as the most significant predictor of the perceived pedagogical value of digital technologies, along with the institutional support and students’ digital competencies, which also made significant contributions. In contrast, teachers’ digital competence and level of exposure to digital technologies were not significant predictors when considered alongside other variables. These results demonstrate that the perceived pedagogical value of digital technologies primarily depends on the ability to encourage students’ interaction and active participation in the teaching process. The research also provides empirical evidence from the technical faculty context and contributes to understanding the conditions under which digital technologies enhance teaching quality.

Radiological screening of construction materials is conventionally performed on bulk samples, yet occupants are exposed to fine, abradable, and respirable fractions. This study examines how particle-size distribution (PSD) governs the redistribution of ²²⁶Ra, ²³²Th, ⁴⁰K, and anthropogenic ¹³⁷Cs in construction materials and in ash from domestic biomass heating. In total, 27 materials were analysed by high-resolution HPGe gamma spectrometry, with granulometric segregation at coarse (PSD3) and fine (PSD7) resolution. PSD3 showed no monotonic effect, whereas PSD7 revealed a systematic rise of the activity concentration index toward the finest fractions. ⁴⁰K and ¹³⁷Cs showed the strongest particle-size dependence, indicating preferential accumulation in the fines; ¹³⁷Cs was detected only in biomass-ash pellets, where it was enriched in the fines (EF = 2.73 relative to bulk; a single-material case study). Two models are proposed: a physically grounded surface-controlled model and a descriptive granulometric enrichment factor for material ranking, both fitted to the present dataset. A fraction-resolved dose assessment showed that the internal hazard index (Hin) rises toward the fines and exceeds unity (≈1.1) in the respirable ash and fireclay fractions even though their bulk values remain acceptable. Bulk screening, therefore, underestimates the dose-relevant burden carried by the fine fractions that workers and households actually inhale.

The properties of percolation of objects of various shapes on a two-dimensional triangular lattice is studied by means of Monte Carlo simulations. Depositing objects of various shapes and sizes are made by directed self-avoiding walks on the lattice. Anisotropy is introduced by positing unequal probabilities for orientation of depositing objects along different directions of the lattice. This probability is equal p or (1−p)/2, depending on whether the randomly chosen orientation is horizontal or not, respectively. It is found that the percolation threshold θp increases with the degree of anisotropy, having the maximum values for fully oriented objects.