3D models of urban areas have found use in modern world such as navigation, cartography, urban planning visualization, construction, tourism and even in new applications of mobile navigations. With the advancement of technology there are much better solutions for mapping earth's surface and spatial objects. 3D city model enables exploration, analysis, management tasks and presentation of a city. Urban areas consist of terrain surfaces, buildings, vegetation and other parts of city infrastructure such as city furniture. Nowadays there are a lot of different methods for collecting, processing and publishing 3D models of area of interest. LIDAR technology is one of the most effective methods for collecting data due the large amount data that can be obtained with high density and geometrical accuracy. CityGML is open standard data model for storing alphanumeric and geometry attributes of city. There are 5 levels of display (LoD0, LoD1, LoD2, LoD3, LoD4). In this study, main aim is to represent part of urban area of Novi Sad using LIDAR technology, for data collecting, and different methods for extraction of information's using CityGML as a standard for 3D representation. By using series of programs, it is possible to process collected data, transform it to CityGML and store it in spatial database. Final product is CityGML 3D model which can display textures and colours in order to give a better insight of the cities. This paper shows results of the first three levels of display. They consist of digital terrain model and buildings with differentiated rooftops and differentiated boundary surfaces. Complete model gives us a realistic view of 3D objects.

Regarding the fact that the entire spring semester in higher education was based on online teaching realized at the state University of East Sarajevo, and that the students thus gained a completely new experience, the aim of this research is to identify and study the e-learning critical success factors (CSF) on the basis of the students' perceptions. A number of 356 students of all 17 faculties with in the University participated in the research. The students' attitudes were collected by the instrument containing 36 items, constructed on the basis of a comprehensive review of previous researches of the e-learning critical success factors and semi-structured interview with the students. Seven factors were extracted and studied by the factor analysis: quality learning materials, student's attitude toward e-learning, teacher's attitude toward e-learning, technological support, classroom interaction, student's activities and teacher's attitude towards students. In response to the pandemic, universities are expected to change their traditional concept of learning and offer models of distance learning in the future. Therefore, the results of this research may be of key importance for the selection and implementation of the appropriate e-learning applications and platforms.

The goal of this study was to create a model for predicting the factors that influence graduates’ decisions to continue their studies at the master's level within the same institution. The research was conducted on the entire population of students ( N = 663) who started their studies at the Faculty of Education, University of East Sarajevo between 2008 and 2018 and completed their studies by 2021. Part of the data was collected from the faculty information systems and part through questionnaires. The results showed the artificial neural network had the highest classification accuracy while variables, the personal factors, the faculty offers quality, applicable and useful study programs, time to degree and place of residence have the best predictive value. This model can enable other institutions of higher education to create an inclusive environment that enhances student wellbeing, improves educational results, and increases institutional efficiency.

Assessing giftedness is one of the inevitable processes in the identification of gifted schoolchildren which involves all the actors included in the direct contact with schoolchildren. Since the assessments are regarded as a subjective opinion of the assessor, our aim is to determine the level of certainty that we can take into account when assessing giftedness identification. In relation to that, the research is based on the validation of compliance in the giftedness assessments of schoolchildren by: teachers, parents, peers and schoolchildren’s self-assessment.The research was conducted on 115 schoolchildren aged 8 and 9 in Bosnia and Herzegovina. The instruments for giftedness assessment were based on the theory of multiple intelligences. The instruments passed several validations, and their metric characteristics were determined. The content validity has been established, and it shows in a high-quality manner that the measuring instrument provides the possibility of appropriate measurement of multiple intelligences, while the reliability of the instrument is confirmed by Cronbach’s alpha coefficient. The positive correlation among the perceptions of teachers, schoolchildren, peers, and the self-assessment is confirmed by Pearson’s correlation analysis. The Kruskal–Wallis test, with the Dunn’s post-hoc test, indicates that there is a high congruence between the assessments of all four groups of assessors. The greatest agreement in assessments was found in musical intelligence, whereas the greatest differences in assessments were detected in the combination of parents with other assessors. The findings in this research will be used for creating a software for giftedness assessment.

The aim of this paper was to analyze the socio-demographic determinants of fertility in Bosnia and Herzegovina that affect the number of live births in Semberija. The paper focuses on work and educational statuses, economic crisis and unemployment, and other relevant factors that affect desired family sizes and lead to negative demographic trends. The relevant data were collected through a survey questionnaire filled by a verified sample of 1000 women in their reproductive period (aged 15–49). In order to evaluate the role of each research variable in predicting fertility intentions, the arithmetic mean, frequency of responses in percentage, Pearson’s coefficient, and a logistic regression model were used to explore the related factors of fertility behaviors among women in this population. The results showed that employment status, poor housing conditions, and financial support from the state statistically significantly impact future birth trends. Those socio-demographic factors affect desired family sizes and have proven essential to future fertile behavior.

In order to prevent the interruption in the education process during the first wave of the Covid-19 pandemic, which would inevitably lead to serious socio-economic consequences, the universities from low-income countries, including those from Bosnia and Herzegovina, shifted to “emergency remote teaching,” a type of teaching that is different from high-quality online education by its name and implementation method. A case study has been designed to research the role of teachers in creating an efficient learning community in the cases of emergency remote teaching. The aim of this study was to assess the perception of students with regard to the teachers’ role in “emergency remote teaching.” The process of collecting data from students started two weeks before the end of the term. The research results suggest that the crucial role of teachers in building learning communities in postwar and low-income countries is to advocate and implement the changes in their education systems, as well as the changes in understanding the concept of social responsibility that should lead to the transformation of “emergency remote teaching” model into pre-planned online learning in near future.