Children's (Mis)understanding of the Balance Beam (Online Edition)
Bibliographic record
Abstract
The balance-scale task, proposed by Inhelder and Piaget, illustrates children understanding of weight-distance relationships. Piaget used the clinical interview method in order to investigate children's reasoning. Over the last five decades, Siegler's Rule-Assessment Approach has been used to explain children reasoning in the balance-scale task according to rules children would use to solve the task. However, this approach does not take into account some key perceptual properties of the task. This study evaluates whether different task demands would alter children's errors. Forty children (twenty children aged 4-5 years and twenty children aged 9-10 years) predicted the movement of both arms of 16 balance-scale problems administered online. Nine 4-5-year-olds produced non-plausible responses whereas none of the 9-10-year-olds provided non-plausible responses. These results seem to indicate a basic misunderstanding of the scale from some younger children, one that eludes traditional measures used with this task.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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".