REFLEXÕES SOBRE A FORMAÇÃO DOCENTE E AS POSSIBILIDADES DE ENSINAGEM PARA A CULTURA MAKER
Bibliographic record
Abstract
The social distancing, a measure to combat the Pandemic caused by COVID-19, intensified the use of digital media in several areas of work. In education systems, it was necessary to adapt the strategies and methodologies to the new reality of teachers, students and pedagogical practices. These adaptations expanded the possibilities of pedagogical practices, demanding that new skills be considered in the training of teachers who work in these contexts and from these contexts. The present paper has the goal to problematize the epistemological base influence in the reconfiguration of knowledge and pedagogical practices, as well as the ways how it can affect the restructuring of teacher education. This discussion was implemented in three sections: (1) by the analyze of the methodological aspects and uses of technological resources necessary for the reformulation of pedagogical mediation in Pandemic contexts; (2) by the thematization of the processes of constitution of the student protagonism, like a consequence of the decentralization of the teacher's leading arising from these teaching modalities; (3) and by the presentation of the paradigm of maker culture, as a epistemological movement differentiated from traditional teaching processes, and its repercussions in the reconfiguration of teacher education and mediation. As a result of this study, it is highlighted that the redesign of methodological issues should be supported by another epistemological perspective guided by the maker culture, from the proposition of student protagonism as an element of pedagogical innovation that guides the reconfiguration of teacher education.
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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 | 0.009 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.013 | 0.025 |
| Scholarly communication | 0.019 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 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".