Review Article
The Emergence and Functioning of the Modern Global University Ranking System
Issue:
Volume 15, Issue 3, June 2026
Pages:
108-112
Received:
21 October 2025
Accepted:
3 November 2025
Published:
8 May 2026
Abstract: This paper examines the prerequisites for the emergence and the stages of formation of the modern global ranking system for higher education institutions (HEIs). The study analyzes the key drivers behind the need for objective evaluation of university education quality at a global level, including internationalization processes, intensified competition among universities, and the expectations of employers and prospective students. Particular attention is paid to major international rankings, their methodologies, evaluation criteria, and their impact on university development. Both positive and problematic aspects of ranking systems are considered, including their influence on university strategy, academic mobility, funding, and research activities. Globalization has intensified competition among universities, increasing the significance of international rankings. These rankings affect institutional prestige, student choice, development strategies, and the global education market. Global rankings reinforce competition, influence academic reputation, attract investment, and shape international image. They serve as tools for attracting students, research talent, and strengthening educational exports. The diversity of ranking methodologies reflects differences in universities’ evaluation priorities. Indicators such as student-to-staff ratios do not always objectively reflect education quality. Evaluation of research activities relies on publication and citation metrics but suffers from methodological limitations, ranking adaptation, and commercialization. The integration of new indicators and big data analytics is required. Rankings remain significant in global education, influencing university strategies. University selection is a multi-level process in which reputation and academic positioning play a key role. Global rankings are applied in economic analyses to aggregate data, assess regional potential, evaluate the quality-to-cost ratio, and study public perception of rankings and their importance. In conclusion, the study emphasizes the role of rankings as a tool for global university positioning and highlights the need for their further refinement, considering regional context and specificities of national education systems.
Abstract: This paper examines the prerequisites for the emergence and the stages of formation of the modern global ranking system for higher education institutions (HEIs). The study analyzes the key drivers behind the need for objective evaluation of university education quality at a global level, including internationalization processes, intensified competi...
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Research Article
Towards a Comprehensive Model of AI-related Competences for Teachers: Insights from a Scoping Literature Review
Luca Mikula*
Issue:
Volume 15, Issue 3, June 2026
Pages:
113-132
Received:
17 April 2026
Accepted:
30 April 2026
Published:
30 May 2026
DOI:
10.11648/j.edu.20261503.12
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Abstract: The increasing integration of AI into educational practice places new demands on teachers and requires an expanded, systematically grounded competence profile. While numerous studies address AI in education, a structured overview of existing AI-related competence models for teacher education remains lacking. This scoping review aims to systematically examine and synthesise competence models that address AI-related competences for teachers, with a particular focus on their conceptual foundations and competence dimensions. Therefore, a scoping review was conducted across three databases (Web of Science, ERIC, and Fachportal Pädagogik). Forty-two studies published between 2016 and March 2025 were included, of which seventeen explicitly focus on AI. Both independently developed competence models and adapted frameworks, including those based on TPACK or DPaCK, were analysed using a deductive-inductive qualitative content analysis grounded in Weinert’s competence definition with the help of Rayyan and MAXQDA. The results reveal a strong emphasis on cognitive competence dimensions, particularly technical understanding of AI systems, ethical reflection, and the pedagogical use of AI tools. In contrast, motivational, volitional, and social dimensions, as well as explicit competences related to teaching about AI, are scarcely addressed. Additionally, few models provide a coherent structure that integrates AI as both a teaching tool and a curricular subject. Based on these findings, the paper proposes a conceptual, layered competence model that integrates (1) instructionally relevant AI knowledge, (2) AI-related curricular content, (3) a distinct dimension of AI didactics focused on teaching about AI, (4) subject-specific didactics, and (5) transversal motivational, volitional, and social dispositions, complemented by progression levels. This model offers a structured foundation for curriculum design, teacher education, and future empirical validation of AI-related teacher competences.
Abstract: The increasing integration of AI into educational practice places new demands on teachers and requires an expanded, systematically grounded competence profile. While numerous studies address AI in education, a structured overview of existing AI-related competence models for teacher education remains lacking. This scoping review aims to systematical...
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