Brick classroom & Block classroom: preschoolers’ spatial and architectural design skills during constructive play
Bibliographic record
Abstract
Constructive play, where children manipulate materials to create and build something, is a prevalent form of play in preschool settings. Children can greatly benefit from engaging in constructive play, specifically by developing spatial and architectural skills. Therefore, the current study aim was to examine ways preschoolers used spatial and architectural design skills during constructive play. Participants were observed via the Spatial – Geometric – Architectural (SPAGAR) Coding System and included 31 preschool children aged five-year- old with 16 boys (M = 63.06, SD = 2.112) and 15 girls (M = 62.93, SD = 1.907) from two separate classrooms. While children in one classroom (brick classroom) played with plastic snap-together bricks, children in the other classroom (block classroom) played with non-interlocking wood blocks. Findings indicated that children’s construction-based designs varied. Children who played with blocks usually created designs that included line symmetry, patterning, engineering, and trabeated constructions (i.e. using horizontal beams). Whereas children who played with building bricks created designs that commonly included line and plane symmetry. Although, the types of play materials could have influenced children’s design preferences, children in both classrooms were found to engage in constructive play where various spatial and architectural design skills were practiced over the 10-day observation period.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".