Purpose: This paper aims to describe the popular trends and methods and ICT tools used for mapping and visualization of scientific domains as a research methodology which is attracting more and more interest from scientific information and science studies professionals. Science mapping or bibliometric mapping is a spatial representation of how disciplines, fields, specialties and individual documents or authors. The researchers analysed Bibexel, Pajek, VOSViewer, programmes used for processing and visualization of bibliographic and bibliometric data, within the framework of the implementation of IRNet research network project and activities and presented several examples of visualisation. Design/methodology/approach: Among the main indicators of research effectiveness – bibliometric indicators – is a powerful information tool to support the development of science. Practical research methods were prepared using the programs: Bibexel (metadata analyses), program Pajek: graph editing and visualization of the graph structure of co-authorship – using the method of Kamada-Kawai and VOSviewer: a computer program for creating maps based on network data and for visualizing and exploring these maps. The main features of VOSviewer can be summarized for creating maps based on network data, visualizing and exploring maps. Findings: The cited references and keywords are used to analyse in particular the intellectual base used by the research field or to analyse documents that cite the same references. Originality/value: The authors of the paper, who are researchers of the European IRNet project and international research network, described and analysed certain bibliographic results of these activities using methods of mapping and visualization of scientific domains.

Throughout human history, many significant advancements have emerged thanks to the efforts of great scholars such as Pythagoras, Da Vinci, Newton, Leibniz, Edison, Bell, and numerous others who laid the groundwork for scholarly communities and universities. Human intelligence has been a vital pillar of cultural evolution, technological innovation, and academic education. Classical scholars educated their apprentices individually, utilizing simple tools that eventually evolved into the pencil and paper we know today. Many scholars and educators today agree that the current generation of learners may lack either the ability or motivation to learn without smart devices. However, the process of learning and enhancing natural intelligence remains fundamentally similar to how it occurred many centuries ago. The principles of natural intelligence have inspired numerous scholars and researchers to develop tools for machine intelligence. Significant early advancements in computing included the first machines capable of performing simple calculations, such as adding 1 + 1 to equal 2. This chapter emphasizes the author's academic contributions. It offers a unified overview of the book's main insights and explains how the application of AI is revolutionizing modern educational practices and learning processes for today's Cyber Nomad generation of learners. The authors outline the epistemic layers that determine the legitimacy of AI in educational contexts. Given the geopolitical tensions and misinformation, this chapter emphasizes significant existential perspectives from renowned thinkers on AI while exploring the landscape for the coming decade. Central to the discussed landmarks are shifts in hermeneutics and belief systems that have shaped global acceptance of AI's semantic extrapolations, as illustrated by examples from OpenAI such as ChatGPT and ChatSonic. As recently proposed at the World Economic Forum and the U.S. Pentagon, users' awareness of the impact of metacognitive backgrounds is central to further AI evolution. From an architectural perspective, this is an opportune moment to advocate for nonsingular reflections. Predictions suggest that anthropomorphic imagination is a fleeting phenomenon likely to be overshadowed by metacognitive representations such as 'conceptual thinking' for aspiring professionals in industrial design and educational and vocational training policy considerations (Nijhof & Kommers, 1984).

Starting from the need for visualising the live biological process, we conducted a pilot project to develop a virtual reality learning environment. As a new technology, virtual reality has a good prospect as an alternative medium for teaching and learning. A virtual reality environment has some advantages in increasing the learning process and learning outcomes. We developed three prototypes for mammal blood circulation. An evaluation for those prototypes were conducted in order to know the virtual reality position for learning biology and also to know the students' appreciation of the virtual reality environment. Interesting results from the evaluation gave indications that a virtual reality environment can help the learner to visualise an abstract concept and ideas.

Artificial Intelligence (AI) is now one of the most important and contemporary directions of development of science in an interdisciplinary context. The EU’s approach to artificial intelligence centres on excellence and trust, aiming to boost research and industrial capacity while ensuring safety and fundamental rights (A European approach to artificial intelligence). Strengthening the fostering excellence in AI will strengthen Europe’s potential to compete globally. Simultaneously not yet solved are a lot of challenges and issues. The problem raised in the article is to explore and analyse computer science and education students’ attitude to educational, social, and ethical aspects of AI implementation. The purpose is to discover and analyse computer science students and pedagogical attitude towards education, social-, and ethical aspects of AI implementation. Students of two faculties of the University of Silesia in Katowice, Poland, were asked to respond to a survey. They were mainly students of two specializations – Computer Science and Pedagogy. As many as 103 students have been surveyed. The Kruskal-Wallis tests were used for verification. The main issues studied were the students’ level of competence in AI, their awareness of AI applications in various areas of life and economy, and the importance of the AI field. The study also included the level of confidence towards AI and the level of anxiety towards AI. Various types of dependencies and connections between these aspects were investigated. The hypotheses were mostly confirmed. Finally, the article presents the discussion and main conclusions.