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Record W3203940803

Análise preliminar do impacto da BNCC no Ensino Médio, no contexto do ensino de Geografia

2021· article· pt· W3203940803 on OpenAlexaboutno aff
Gabriel de Lima Germano, Clevisson Junior Pereira, Ramon de Oliveira Bieco Braga

Bibliographic record

Venuenot available
Typearticle
Languagept
FieldEnvironmental Science
TopicEnvironmental Sustainability and Education
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhilosophyPolitical science
DOInot available

Abstract

fetched live from OpenAlex

O objetivo desta pesquisa foi analisar os impactos da reforma curricular da educacao basica brasileira, normatizada pela Base Nacional Comum Curricular (BNCC), sobretudo no tocante ao ensino da Geografia no Ensino Medio. Para isso, foi utilizada uma metodologia documental tendo como base as leis as leis de Diretrizes e Bases da Educacao Nacional (BRASIL, 1996), o Plano Nacional da Educacao (BRASIL, 2014), a Reforma do Ensino Medio em tempo integral (BRASIL, 2017) e a BNCC (BRASIL, 2018), aliado as reflexoes cientificas acerca do ensino de Geografia, ancorado em Girotto (2016), Guimaraes (2018), Corti (2019), Freire (2019) e Laval (2019). Destarte, foi constatado que a homologacao da BNCC (BRASIL, 2018) ocorreu em meio a uma disputa de interesses a respeito do papel da educacao na sociedade. Nessa perspectiva, constatou-se que o papel do componente curricular Geografia sofreu impacto direto ficando aquem do seu potencial pedagogico, pois sem assegurar uma discussao pedagogica com os(as) docentes e estudantes de Geografia em todo territorio brasileiro, o Ministerio da Educacao (MEC) impos a reducao da carga horaria do componente curricular Geografia no curso de Ensino Medio, restringindo e diluindo o volume de conteudo a uma perspectiva interdisciplinar entre os componentes curriculares que compoe as Ciencias Humanas, isto e, Geografia, Historia, Filosofia e Sociologia. Desse modo, nesta reflexao teorica, sao indicados os tensionamentos politicos e pedagogicos existentes no processo de ensino e aprendizagem do componente curricular Geografia, a luz da reforma curricular estabelecida pela BNCC (BRASIL, 2018).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0860.014

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.

Opus teacher head0.018
GPT teacher head0.283
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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