Formation of Social Intelligence of School Children Through the Integration of Subject Knowledge
Bibliographic record
Abstract
Social intelligence is essential for school children's development; it enables them to build meaningful relationships and explore complex social interactions. Therefore, the present study aims to determine the impact of integrating subject knowledge in the development of social intelligence among school children, looking at the growing importance of social competencies such as empathy, social skills, and conflict resolution. The study employed a quasi-experimental design involving 60 participants. The participants were divided equally into two groups: experimental and control groups. The experimental group received treatment on integrated subject knowledge, while the control group received instruction through conventional teaching instruction. This study has found generally significant gains in the experimental group, especially in areas such as conflict resolution and social skills, with minimal improvement observed in the control group. These findings suggest that subject integration not only enhances academic engagement but also strengthens interpersonal capabilities essential for collaborative learning and social adaptation. The evidence from this experimental study underscores several critical implications for educational practice in Kazakhstan. First and foremost, the observed improvement in students’ social intelligence highlights that integrating subject knowledge into instruction is not merely a curricular innovation but a practical necessity for holistic student development. The study recommends that policymakers and decision-makers in Kazakhstan should promote the systematic inclusion of integrated curricula in both primary and secondary schools, emphasizing activities that combine subject learning with social interaction, such as group problem-solving and interdisciplinary projects.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".