<p>Layers of generality and types of generalization in pattern activities</p>
Why this work is in the frame
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Bibliographic record
Abstract
Pattern generalization is considered one of the prominent routes for introducing students to algebra. However, not all generalizations are algebraic. In the use of pattern generalization as a route to algebra, we —teachers and educators— thus have to remain vigilant in order not to confound algebraic generalizations with other forms of dealing with the general. But how to distinguish between algebraic and non-algebraic generalizations? On epistemological and semiotic grounds, in this article I suggest a characterization of algebraic generalizations. This characterization helps to bring about a typology of algebraic and arithmetic generalizations. The typology is illustrated with classroom examples. Niveles de generalidad y tipos de generalizaciones en actividades de patrones La generalización de patrones es considerada como una de las formas más importantes de introducir el algebra en la escuela. Sin embargo, no todas las generalizaciones de patrones son algebraicas. Como consecuencia, en el uso de patrones como recurso didáctico, se debe tener mucho cuidado en no confundir generalizaciones algebraicas con otras formas de generalización. Ahora bien, ¿cómo distinguir entre las unas y las otras? En este articulo, basado en ideas epistemológicas y semióticas, sugiero una caracterización de generalizaciones algebraicas. Dicha caracterización permite establecer una tipología, la cual es ilustrada a través de ejemplos concretos.Handle: http://hdl.handle.net/10481/3505Nº de citas en WOS (2017): 13 (Citas de 2º orden, 7)Nº de citas en SCOPUS (2017): 6 (Citas de 2º orden, 4)
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it