Bibliographic record
Abstract
Proformação is a distance teacher certification course aimed at providing training to 27,000 uncertified teachers in 15 Brazilian states. This innovative program organizes human and technical resources for delivering distance education in a cost-effective manner. Different from other institutional systems – which typically employ their own dedicated content, design, and instructional resource personnel, and accompanied by a large pool of administrative staff – Proformação leverages pre-existing learning resources such as content experts, technology specialists, instruction, and student support systems from several institutions. Proformação goal is to create a viable teacher certification course to upgrade thousands of non-certified teachers working in the field. Proformação is coordinated by an administrative unit of the Brazilian Ministry of Education. To support the program, an information system was implemented to continuously and consistently monitor the program’s activities and results. Results of an external evaluation have been positive; Proformação is regarded by some as an innovative model for delivering decentralized training opportunities to large student numbers. Therefore, the findings in this article may prove interesting to those charged with implementing distance learning initiatives in developing countries, in that the lessons learned in Brazil may help others interested in implementing similar distance training programs. Key Terms: distance teacher training, distance education, in-service teacher training, distance education in developing countries
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".