Specificity of Organizational and Methodological Ensuring the Learning Process in the Information and Educational Environment
Bibliographic record
Abstract
The article identifies the main trends characterizing the modern educational space; analyzed the content characteristics of the informational educational environment as a pedagogical system that combines informational educational resources, computer learning tools, educational process management tools, pedagogical techniques, methods and technologies. Based on the analysis of the scientific works of leading scientists, the main characteristics of the informational educational environment (variability, contextuality, polyfunctionality, adaptability) are determined, and their explanation is given; the functions of the informational educational environment are determined and the structure is substantiated. It has been proven that the information and educational environment consists of the goals and tasks of the organization of the project process, as well as the program-methodical (normative support for the functioning of the educational system), information-knowledge (a set of competencies), communication (interaction of the subjects of the educational process), technological ( modern teaching aids) components. The specifics of the use of advanced educational technologies in the information and educational environment are clarified. The conclusion that the information and educational environment of higher education institutions in modern conditions solves the following tasks is substantiated: improving the quality of education and the level of professional competence formation; ensuring the availability of educational services; lifelong learning; preparing students for the use of information technologies in an open digital society; increasing the efficiency of the education system in general.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".