Engineers and engineering through the eyes of preschoolers: a phenomenographic study of children’s drawings
Bibliographic record
Abstract
This study aimed to explore how preschoolers perceive engineers and engineering by using their drawings. For this aim, phenomenography was used as a research approach. The data were collected using the draw-and-tell technique and through the drawing and explanation related parts of the Draw an Engineer Test. Totally, 436 preschool children from 16 different cities in Turkey were asked to draw an engineer and narrate their drawings. The data were analyzed using inductive content analysis. Findings indicated that some children did not reveal an understanding of engineer or engineering via their drawings (n = 50). A limited number of children (n = 17) had a perception of engineer parallel to the definition of the engineer in the literature. Most children (n = 199) tended to perceive engineering as a male-specific and physical work and represented engineers while working outdoors (n = 147); building structures or constructing machinery (n = 156). This research implies that preschoolers should have a higher amount of opportunity to explore engineering in everyday life with the empowerment of teachers, parents, and community members.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".