The way people travel, organise their time, and acquire information has changed due to information technologies. Artificial intelligence (AI) and machine learning (ML) are mechanisms that evolved from data management and developing processes. Incorporating these mechanisms into business is a trend many different industries, including education, have identified as game-changers. As a result, education platforms and applications are more closely aligned with learners’ needs and knowledge, making the educational process more efficient. Therefore, AI and ML have great potential in e-learning and higher education institutions (HEI). Thus, the article aims to determine its potential and use areas in higher education based on secondary research and document analysis (literature review), content analysis, and primary research (survey). As referent points for this research, multiple academic, scientific, and commercial sources were used to obtain a broader picture of the research subject. Furthermore, the survey was implemented among students in the Republic of Serbia, with 103 respondents to generate data and information on how much knowledge of AI and ML is held by the student population, mainly to understand both opportunities and challenges involved in AI and ML in HEI. The study addresses critical issues, like common knowledge and stance of research bases regarding AI and ML in HEI; best practices regarding usage of AI and ML in HEI; students’ knowledge of AI and ML; and students’ attitudes regarding AI and ML opportunities and challenges in HEI. In statistical considerations, aiming to evaluate if the indicators were considered reflexive and, in this case, belong to the same theoretical dimension, the Correlation Matrix was presented, followed by the Composite Reliability. Finally, the results were evaluated by regression analysis. The results indicated that AI and ML are essential technologies that enhance learning, primarily through students’ skills, collaborative learning in HEI, and an accessible research environment.

This research investigates blockchain technology, focusing on the influence of motivation on collaborative work, which positively influences learning performance in Higher Education Institutions (HEI). In addition, blockchain technology is correlated with decentralisation, security and integrity, and anonymity and encryption. It can also be perceived as a consensus mechanism, rewarding students, professors, and universities as a smart contract. Therefore, this technology has been used to improve higher education. It also allows less informed people to interact with better-informed peers and mentors. Finally, this study aims to enhance the current state of blockchain applications comprehension. The methodology used for this research includes document analysis, literature review, content analysis (blockchain platforms), the case study method, and the survey method. In statistical considerations, aiming to evaluate indicators, this research presents the Composite Reliability Analysis, Cronbach Alpha Coefficients, and the Bootstrapping method (Variance Inflation Factor). All these analyses aimed to present a designed research model. This exploratory research gathered data from 150 students at 3 universities in Serbia, Romania, and Portugal. As demonstrated, using student motivation has a significant and positive impact on the quality of student collaborative work. Student collaborative work also correlates with students’ higher level of engagement in the educational process, and the more engaged students are, the better their learning outcomes will be. As a result, in higher education, student involvement boosted learning outcomes. Researchers found that motivation, teamwork, and student involvement were important factors in improving student learning outcomes, as were blockchain-based tools. The results from the quantitative analysis indicate that Collaborative work, Motivation, Engagement, MOOCs, AR, VR, Gamification, and Online class were associated with learning performance.

Lifelong learning approaches that include digital, transversal, and practical skills (i.e., critical thinking, communication, collaboration, information literacy, analytical, metacognitive, reflection, and other research skills) are required in order to be equitable and inclusive and stimulate personal development. Realtime interaction between teachers and students and the ability for students to choose courses from curricula are guaranteed by decentralized online learning. Moreover, through blockchain, it is possible to acquire skills regarding the structure and content while also implementing learning tools. Additionally, documentation validation should be equally crucial to speeding up the process and reducing costs and paperwork. Finally, blockchains are open and inclusive processes that include people and cultures from all walks of life. Learning in Higher Education Institutions (HEI) is facilitated by new technologies, connecting blockchain to sustainability, which helps understand the relationship between technologies and sustainability. Besides serving as a secure transaction system, blockchain technology can help decentralize, provide security and integrity, and offer anonymity and encryption, therefore, promoting a transaction rate increase. This study investigates an alternative in which HEI include a blockchain network to provide the best sustainable education system. Students’ opinions were analyzed, and they considered that blockchain technology had a very positive influence on learning performance.

This study aims to provide a comprehensive overview of the XR challenges, opportunities, and future trends that will impact higher educational institutions. The article discusses (using observation, participatory observation and as well as document analysis) the potential for augmented reality to be used in higher education, having in mind characteristics of Millennials (Generation Y) and Post-Millennials (Generation Z) and raises issues about responsible innovation, the future of work, and formal education. Additionally, survey research was completed among students in Serbia and Romania (103 respondents) within selected generations regarding their knowledge of extended reality and their attitudes towards opportunities and challenges of extended reality in Higher Education Institutions, and thus this paper also utilises quantitative analysis. A correlation matrix, composite reliability, and regression model were used to code the data and extract knowledge. A thorough review of the existing literature on one hand and primary research as well, using the chosen scientific methods, the planned purpose of the research will be obtained: to gain a better-understanding of the education needs of Generation Y and Generation Z and the potential use of XR as a response to the needs observed. The results of the quantitative analysis confirmed our starting assumptions: XR is an excellent technology facilitating the teaching processes allowing learners to more actively control their learning strategies and supporting the interactivity and connectivity that students and faculties experience. Furthermore, Generation Z students are more applicative for stating XR’s opportunities (instead of challenges) in higher education institutions.

From the moment the Republic of Serbia declared a state of emergency in the summer semester of 2019/2020, higher education institutions (HEIs) used various teaching models from Distance Learning Systems (DLS), online platforms and modern information and communication technologies (ICT), to sending materials via student e-mails and notifications via faculty portals. Using survey research as a method, the paper describes the experiences of teachers and associates at HEIs in Serbia (780 respondents) regarding the efficiency of provided education services. In this article, we used the method of content analysis and participatory observation, as well. We analysed the attitudes of teachers and associates apropos the efficiency of providing educational services through the work from home (WFH) model and distance learning (DL) and other models used in response to COVID-19 epidemiological measures in education. During the WFH setup, we looked for factors that affect educational efficiency. When it comes to the statistical technique, factor analysis was selected. Technology, managerial support, and work–home conflict are all expected to impact process efficiency, so these were the first criteria considered when selecting potential factors. Principal Component Analysis (PCA) was used as the extraction method, and the Varimax rotation method was also used. We discarded all factors with eigenvalues below one. Four factors caught our attention: School management support, Family–work conflict, Home infrastructure, and Technology choice. The results showed that F1 (School management support) is positively correlated to F2 (Family–work conflict) and efficiency and negatively correlated to F3 (Home infrastructure). Conversely, F2 is negatively correlated to F3 and positively correlated to efficiency. The F4 factor shows no significant correlations to other factors.