Interactions Between Children in Educational Services and their Implications for Learning at the Preschool Education Level: A Literature Review
Bibliographic record
Abstract
This research addresses the interactions of children at the preschool education level in educational services and their implications for or repercussions for learning. We aimed to determine the state of the art of interactions of children at the preschool education level in educational services and their implications for learning. The results of the bibliographic review indicate that this topic has been scientifically approached since 1975, with a growing and fluctuating trend. The countries that theoretically contribute the most to these topics are the United States, the United Kingdom, Australia, Russia, Canada, Italy, Taiwan, Brazil, Germany and Norway. Research results are shared through original scientific articles and are approached from the perspective of the social sciences, medicine and psychology. Finally, the clusters in the scientific maps show variables such as social interaction, education, learning, interpersonal relationships, emotions and cooperation. The analytical reading of the publications indicates the need for a comprehensive approach to children at the preschool education level in educational services, where it is key to educating children in the future. A broader approach that takes into account various needs, which involves social-emotional competencies for children, which are vital components of the comprehensive development of children, is needed. Received: 12 July 2024 / Accepted: 25 October 2024 / Published: 05 November 2024
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".