Caracterização de práticas de ensino e delineamentos de recursos didáticos para área curricular de matemática no ensino fundamental
Bibliographic record
Abstract
The proposal and curricular guidelines for elementary school of Mathematics and São Paulo Student Performance Appraisal System (Sistema de Avaliação do Rendimento Escolar de São Paulo) -SARESP suggest curriculum content and learning expectations expressed as skills which could be assessed at the end of Cycles I and II.Basing on the Behavior Analysis theories, this study aimed to analyze video recorded 4th and 8th grade classes, considering two goals: 1) to characterize the educational practices of public school teachers, when teaching contents in mathematics with emphasis on identifying and describing consistencies among the recorded teaching contingencies, the contents taught as well as the skills explained in the documentation specified above and 2) to verify if the characterization of these teachers' educational practices would constitute in a favoring condition for the instructional design of educational resources for teaching mathematics contents provided in the same documentation previously mentioned The first goal justified the realization of the Analysis and Description Procedure, completing the three stages concerned, according to the following sequence: video recording selection of two teaching units (TUs) and linking skills and competencies parameterized by SARESP to the teaching practices of two teachers; descriptions and analysis of the observed interactions; synthesis of both TU analysis, pointing the most frequent actions in the teachers' educational practices.Through the synthesis referred, it was found that the teachers have chosen not (1) to provide conditions in which students could develop their own answers to the proposed activities and (2) to present immediate consequences related to the students' answers, (3) to explore possible relations for controlling the answers given by students who differed from those predicted previously.For the second goal, the Proposals Procedure for the Educational Resources was established and developed in three stages as well: a) description of the educational program of each TU observed; b) summary of the main characteristics of the educational practices, c) teaching resource design.The designed resources had as a subsidy the characteristics identified in the analysis of the teachers' educational practices.Two resources were proposed, one for each teacher and subject taught in the TUs.These resources have explored the proposition of the effective teaching considering the three characteristics identified above and derived from the performance observation for each teacher.According to the analyses, it was inconclusive to estimate correspondences between the observed performance of the students with respect to the development of the predicted competencies and skills, because the elaborated learning conditions and the way they were conducted did not provide sufficient subsidies for such a conclusion.The characterization of possible contingence relations based on the analysis of the student interactions -teaching materials -teacher that occur in this environment, is shown as an alternative to the development of educational resources, since they can be designed to address the professional performance characteristics of the teacher, as well as to expand the possibilities of presenting the behavioral repertoires which define the desired learning.
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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 | 0.003 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".