Propuesta didáctica para trabajar el número en educación infantil a través de su historia
Bibliographic record
Abstract
En este trabajo se va a profundizar en cómo la Historia de la Matemática puede contribuir \na la enseñanza del número durante la etapa de Educación Infantil. Se pretende perseguir un \nacercamiento a la Matemática por parte del alumnado y hacer de este un elemento motivador para \nel proceso de enseñanza-aprendizaje. En el documento se profundiza en el conocimiento de las \ndiferentes etapas por las que ha pasado el número hasta llegar al utilizado hoy en día, conociendo \nlas oportunidades didácticas que este proceso ofrece y su relación con el currículo de educación \ninfantil de Castilla y León. Con ello, se llevará a cabo una propuesta didáctica que pretende mostrar \nuna forma diferente de enseñar, poniendo en valor la Historia y la Matemática, dando especial \nimportancia al juego para que el alumnado se interese, se motive y sienta la curiosidad por seguir \nampliando sus conocimientos.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.023 | 0.005 |
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".