Global Trends in Assessing Social and Emotional Development in Early Childhood Education: A Bibliometric Analysis (2020–2025)
Bibliographic record
Abstract
This bibliometric study uses extensive Scopus database records and VOS viewer software for detailed visualisation to examine worldwide research trends in the evaluation of social and emotional development in early childhood education from 2020 to 2025. In addition to highlighting important contributors like the University of Toronto, Macquarie University, and Temple University, the study finds notable increases in scholarly attention during this time frame. It also reveals changing research priorities that integrate digital media, mental health, and nutrition into developmental assessments. The study highlights the growing use of interdisciplinary approaches in the fields of public health, psychology, and education by identifying prevalent and developing themes using systematic keyword co-occurrence analysis. The results show that interdisciplinary research and cooperative efforts have grown significantly, making significant contributions to the advancement of international educational policies and practices. This research highlights the significance of evidence-based practices and international collaboration in promoting holistic child development, in addition to outlining the vast area of early childhood development assessment and offering crucial insights for educators and policymakers. The study’s findings point to a dynamic movement in early childhood education frameworks towards the integration of technology and holistic health views, providing a roadmap for future research and real-world applications.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.096 | 0.203 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".