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Record W2260778724 · doi:10.22456/1679-1916.61427

Um estudo sobre as variáveis para predição de alunos não concluintes em cursos suportados por Ambientes Virtuais de Ensino e Aprendizagem

2016· article· pt· W2260778724 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRENOTE · 2016
Typearticle
Languagept
FieldComputer Science
TopicOnline Learning and Analytics
Canadian institutionsDouglas College
Fundersnot available
KeywordsPhysicsHumanitiesPsychologyPhilosophy

Abstract

fetched live from OpenAlex

Os alunos não concluintes são aqueles que não apresentam presença ou desempenho suficiente ao final de uma disciplina ou curso. Em sala de aula, cabe ao professor perceber o comportamento do aluno a fim de identificar seu interesse e progresso. Entretanto, os ambientes virtuais de aprendizagem nem sempre dispõem das informações de maneira simplificada ao professor. Com base em uma análise na literatura, este artigo propõe sete variáveis que podem predizer a conclusão ou não do aluno. Ainda, dados de 1168 alunos concluintes e não concluintes em 89 disciplinas de 5 cursos de uma instituição de ensino foram estatisticamente comparados a fim de verificar diferenças significativas. Os resultados mostraram que concluintes e não concluintes possuem aproveitamento diferentes, isto é, que as variáveis propostas podem ser utilizadas em um modelo de predição de alunos não concluintes.

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.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.736
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 studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.017
GPT teacher head0.286
Teacher spread0.270 · 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