Особливості професійної підготовки фахівців для забезпечення сімейної форми здобуття середньої освіти в Україні та світі
Bibliographic record
Abstract
The article describes the results of the research on the current state of professional training to ensure the successful implementation of family (home) form of secondary education in Ukraine and other countries. The target audience of the study are scientists, teachers and other professionals whose activities are aimed at supporting families with children in home schooling. The issue is urgent because the family form of education is a recent innovative introduction into the practice of secondary education in Ukraine, whereas the process of training specialists to work in this alternative form of education appeared to be imperfect. That is why the purpose of the article is to study the worldwide experience in the training of specialists to work with children in home schooling to identify the possibility of implementing the experience of leading countries in domestic practice. To achieve this purpose, the following tasks were formulated: 1) to conduct a survey of parents of secondary school students in order to determine their attitude to the family form of education; 2) to find out whether there is a need for professional support when a family homeschool a child; 3) to analyze the current state of teacher training for family education all around the world, and in Canada in particular; 4) to compare the state of the problem in Ukraine and the world and determine the possibility of implementing the experience with positive results in the system of training in Ukraine. To solve all the problems mentioned above such general research methods were used as namely empirical methods of comparison and systems analysis; and theoretical methods, like continuous sampling methods and analogies. The study identified the need for curricula and additional training courses for working with families in which children receive home-based secondary education. The experience of foreign countries on the introduction of family education and training must be taken into account when organizing the educational process in Ukraine. It should also be noted that the interest is both positive and negative world experience. The results of the study are important for further theoretical research on the identified problem and important practical importance for the organization of a successful process of training to provide family education as an innovative alternative form of secondary education in Ukraine.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".