MétaCan
Menu
Back to cohort
Record W2897557211

Quais os interesses e as motivações para a busca de cursos de graduação através do sistema semipresencial

2018· article· pt· W2897557211 on OpenAlexvenueno aff
Marcia Regina Balbino, Taitiâny Kárita Bonzanini

Bibliographic record

VenueINFOR Information Systems and Operational Research · 2018
Typearticle
Languagept
FieldSocial Sciences
TopicEducation and Digital Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesSociologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Resumo O presente estudo objetivou discutir os “Interesses e as motivacoes para a procura de um curso de Educacao a Distância (EaD)”. Tal pesquisa foi realizada com os alunos do Curso Semipresencial de “Licenciatura em Ciencias” oferecido pela Universidade de Sao Paulo – USP, em parceria com a Universidade Virtual do Estado de Sao Paulo – UNIVESP, por meio de questionarios disponiveis no ambiente virtual de aprendizagem. Visto que o objetivo principal do curso em questao e a formacao de professores para atuar no Ensino Fundamental, o questionario buscou recolher dados sobre a profissao docente e perspectivas profissionais, qual a possivel satisfacao e expectativa dos alunos do Curso Licenciatura em Ciencias, e o interesse na continuidade dos estudos. Os principais resultados apontaram que o curso atingiu os objetivos propostos, principalmente no que se refere a formacao de professores que queiram atuar no Ensino Fundamental, garantindo para tal uma formacao de qualidade. O estudo ampliou as discussoes a respeito da motivacao na procura pelo curso na modalidade a distância, sua eficacia e aplicabilidade de estrategias.

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)0.013
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0050.004
Scholarly communication0.0090.004
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0170.003

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 head0.188
GPT teacher head0.468
Teacher spread0.280 · 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 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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueINFOR Information Systems and Operational ResearchSame topicEducation and Digital TechnologiesFrench-language works237,207