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Explorando a aprendizagem independente integrada e a inovação nos programas de pós-graduação brasileiros

2013· article· pt· W1955939153 on OpenAlexaff
Ronaldo Mota

Bibliographic record

VenueRevista Brasileira de Pós-Graduação · 2013
Typearticle
Languagept
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsUniversity of British Columbia
FundersCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsHumanitiesSociologyPhilosophy

Abstract

fetched live from OpenAlex

Este artigo apresenta observações sobre aprendizagem independente integrada, com ênfase no papel do professor, acompanhando as experiências de aprendizagem dos estudantes, e tendo os estudantes compartilhando com o professor a centralidade do processo ensino-aprendizagem. Essa estratégia de ensino, aplicável a qualquer nível educacional, inclusive aos cursos de pósgraduação, é apresentada como poderoso instrumento motivador para contribuir com a formação de profissionais capazes de enfrentar os desafios associados com o novo cenário brasileiro, em que inovação e empreendedorismo são prioridades centrais.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.129

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.004
Science and technology studies0.0060.005
Scholarly communication0.0070.003
Open science0.0010.007
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.071
GPT teacher head0.339
Teacher spread0.268 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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