Development of Higher Education of the XXI Century in the World Context in the Face of Global Challenges
Bibliographic record
Abstract
The article is devoted to the problem of higher education development in the twenty-first century in the context of global challenges. Since the scientific research did not include an empirical component, theoretical methods of scientific knowledge (analysis, synthesis, abstraction, etc.) became additional components of the methodological toolkit, and the analysis of relevant scientific publications on educational issues for the period of 2019-2023 was taken as a basis. For convenience, the materials were systematized according to the relevant topics: development and implementation of innovative methodology in the educational process; opportunities for integrating digital technologies into education, digitalization; stakeholder requirements for the personality of a specialist and their implementation in the educational process; problems and prospects for the development of the educational sector; transformation of higher education in Ukraine under the influence of a full-scale war. The purpose of the article was to analyze certain aspects of the development of higher education in the twenty-first century. The analysis of publications allowed us to identify visions of ways to solve educational problems and modernize higher education. Particular attention was paid to the peculiarities of the organization of higher education in Ukraine during the war and the factors that will stimulate/hinder the development of post-war Ukrainian higher education. The generalization of information obtained from relevant scientific sources made it possible to model the process of transformation of higher education today, to identify global factors, to point out the incentives and the path of development that the educational sector is currently moving along. The novelty of the proposed research lies in the attempt to systematize existing scientific studies and build a holistic vision of the transformation processes in higher education. The article is aimed at educators, students, educational reformers, and researchers and aims to draw attention to the importance of educational issues.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".