A scoping review and network analysis of the characteristics of peer collaboration in early educational settings from studies using diverse methodologies
Bibliographic record
Abstract
Peer collaboration is a complex skill that emerges in early childhood. However, researchers and practitioners lack a shared understanding/definition of what peer collaboration means and how to observe it in early educational settings. This review aimed to examine definitions of peer collaboration and the behaviours observed in research on peer collaboration in children zero to six years of age. The current scoping review follows the Joanna Briggs Institute’s methodology. The search syntax was applied in PsycInfo, Education Resource, ERIC, and Child Development and Adolescent Studies. This scoping review includes 123 articles on children engaged in peer collaboration in early educational settings. Inductive and deductive thematic coding was conducted, followed by descriptive statistics. Four domains from the definitions of peer collaboration were identified. These were: “Achieving a Greater Objective”, “Verbal Communication”, “Prosocial Skills”, and “Knowledge Exchange”. Co-occurrences between these domains were identified using a network analysis. The following six domains, describing how collaboration was observed in young children, were identified across the literature: “Interactive Characteristics”, “Communication”, “Activity Structure”, “Assessment of Performance”, “Reciprocity”, and “Cognitive Skills”. Finally, we identified whether observations of collaboration focused on collaborative processes (i.e. behaviours occurring during collaboration) or products (i.e. outcomes). We found that peer collaboration in early educational settings was more commonly viewed as a collaborative process (although this varied by domain). We conclude by offering a synthesised definition of collaboration and a framework to begin thinking about measuring collaboration based on the findings from this study.
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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 | 0.057 | 0.216 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.061 | 0.058 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".