Programa de fortalecimento da aprendizagem Aprender Mais Escola nos 2º anos do ensino fundamental: avaliação em duas escolas públicas municipais de Fortaleza-CE
Bibliographic record
Abstract
Currently, full-time education, its importance, and the challenges of its implementation are being discussed at the national, state, and municipal levels. There is a recurring concern regarding the school hours of students in public institutions, grounded in the principle of comprehensive student development. Based on this premise, this research evaluates the implementation of the Programa Aprender Mais Escola in the 2nd grade of Elementary Education during the period from 2022 to 2024, identifying its contributions and limitations to the teaching and learning process in two municipal schools in Fortaleza, Ceará. To this end, the methodology adopted privileges a qualitative approach, of a basic nature, grounded in Experiential Evaluation (Lejano, 2012). The research design includes a bibliographic study based on Moll (2012), Cavaliere (2007–2010), Oliveira (2023), Gadotti (2003), Laval (2021), and Jordão, Colares, and Fonseca (2023), as well as documentary analysis and empirical research conducted through questionnaires composed of open and closed-ended questions applied to program monitors/coordinators, teachers, and school administrators. The empirical analysis follows Bardin’s (2011) content analysis guidelines, complemented by participant observation and focus groups. The research findings show that the Programa Aprender Mais contributed to advances in students' reading proficiency but also revealed challenges, particularly in the context of the two schools analyzed. Based on the participants’ perceptions of the Programa Aprender Mais Escola, several weaknesses in its implementation became evident, including the need to adapt school facilities to accommodate students during extended hours, the inexperience of some monitors and coordinators due to a lack of training or direct connection to the field of education, and precarious volunteer hiring processes. These aspects highlight significant challenges to the effectiveness of the program and to ensuring quality educational services. Furthermore, the wealth of information produced by a study that evaluates an educational public policy broadens the possibilities for critical reflection and fosters discussions on the topic, contributing to the improvement of future practices and policies.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".