O jogo nas proposições davydovianas para o ensino da matemática
Bibliographic record
Abstract
The purpose of this article is approach the game and their grounding for teaching mathematics as an interface in preschool and in the first year of the basic school. The focus of this paper is in the appearance of this inter-relation in Davyidov’s proposal for the teaching of Mathematics. The research question is: Which tasks, according to Davydov’s way of organizing the teaching of mathematics for the first school year, present the content of game as a manifestation of the transition from game to study activities, which evinces human development according to the historical, cultural theory? The tasks selected for this analysis were extracted from a doctoral theses about the expression of Davydov’s proposal for the teaching of mathematics in the first school year. This article brings evidence of the presence of tasks with the following characteristics of games: rhymes, riddles, games of make-believe, and practical jokes. The content of game play in the first school year is guided to the appropriation of the theoretical basis of the mathematical scientific concepts, not the commonplace concepts, as happen to be seen in preschools.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.011 | 0.014 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".