Information and Analytical System of Control, Planning, and Management of the Educational Process in Educational Institutions
Bibliographic record
Abstract
In the context of the rapid informatization of the economy, the issues of effective information support for the management of higher education institutions (hereinafter HEIs) are of paramount importance. Their complexity and relevance are determined by the intensive development of the multi-vector nature of HEIs' activities, the variety of funding sources, and a large number of types and forms of educational, research, production, and economic activities. This indicates the need to manage higher education institutions at a qualitatively new level, to create appropriate functional and organizational models. These models should envisage a combination of regional and national educational management systems, and the development of a modern concept of information support based on networked computer technologies and modern software tools. The article aims to define the basic principles and main trends of research in the scientific literature on issues related to the implementation of control, planning, and management systems for the educational process of HEIs in terms of their information and analytical support, and to clarify certain practical aspects of HEIs management. Methodology. In the course of the study, the analytical and bibliographic method was used to study the scientific literature on information and analytical support for the management of the educational process of HEIs. Induction, deduction, analysis, synthesis of information, system-structural, comparative, logical, and linguistic methods, abstraction, and idealization were used to study and process data. Moreover, the authors of the study conducted an online questionnaire survey to practically clarify the most important issues related to the research topic. Results. According to the results of the study, the main most important theoretical components of the information and analytical system for managing the educational process in higher education are identified. The perspective of scientists and managers of HEIs on the key aspects of this issue is also studied.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.014 | 0.009 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".