Development of Higher Education Institutions and Online Communication with Students in Modern Conditions
Bibliographic record
Abstract
The conditions that have developed in the educational sphere since the beginning of the Russian military aggression in Ukraine have significantly complicated the implementation of the educational process, the establishment of professional communication – from contacts with the immediate environment to global and intercultural ties. The stress burden experienced by both teachers and students includes the forced relocation of participants of the educational process to other regions, the participation of teachers and students in hostilities, territorial defence units and volunteer movements, the loss of relatives and friends, etc. In such conditions, teachers in higher educational institutions should react quickly and take corrective measures in order to restore professional and pedagogical communication. The purpose of the academic paper is to characterize, clarify the advantages, disadvantages and determine the features of certain types of online communication of higher educational institutions with students in modern conditions. In the course of the present research, a number of general and special methods of analysis of scientific sources were applied, as well as an online survey was used to study the standpoint of participants of the educational process, namely, students and teachers of higher educational institutions, regarding the features of online communication of higher education institutions with students in current conditions. Based on the results of the research, the main characteristics of the communication processes taking place in the online mode in higher education were studied, and the standpoint of the participants of the educational process regarding the priority components of the organization of the educational online system was clarified.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".