COVID-19 e os efeitos na prática do ensino em contexto universitário: mudança e inovação em um ambiente de urgência: COVID-19 and the effects on teaching practice in a university context: change and innovation in an urgent environment
Bibliographic record
Abstract
O presente artigo foi redigido em resposta a dois questionamentos: 1) quais sao as principais consequencias da pandemia na pratica do ensino em contexto universitario? e, 2) quais sao as estrategias e respostas tecnologicas empregadas por professores de carreira e professores substitutos para fazer face a essa situacao de urgencia? O artigo apresenta a seguinte estrutura: descricao do contexto de transicao rapida e generalizada para cursos on-line; panorama da literatura sobre o ensino em cenarios de crise; descricao da metodologia de pesquisa; apresentacao e discussao dos resultados; recomendacoes; e conclusao. O objetivo deste estudo e de descrever e analisar a situacao tal como se apresenta segundo a otica de professores e alunos que vivenciaram no terreno a situacao de urgencia no quadro de uma pandemia. Apresentamos aqui um panorama da situacao vivida por professores e alunos em algumas universidades canadenses, nomeadamente Universite de Montreal. Como esta e uma situacao recente e alguns dos aspectos estudados sao em desenvolvimento quando elaboramos esse artigo, nao ha documentos cientificos ou academicos publicados tratando especificamente do assunto. Palavras-chave: Ensino universitario; pandemia; educacao a distância. Abstract This article was written in response to two questions: 1) what are the main consequences of the pandemic in the practice of teaching in a university context? and, 2) what are the strategies and technological responses employed by career teachers and substitute teachers to face this urgent situation? The article presents the following structure: description of the context of rapid and generalized transition to online courses; overview of the literature on teaching in crisis scenarios; description of the research methodology; presentation and discussion of results; recommendations; and conclusion. The aim of this study is to describe and analyze the situation as it appears from the perspective of teachers and students who experience the emergency situation in the context of a pandemic. Here we present an overview of the situation experienced by professors and students at some Canadian universities, namely Universite de Montreal. As this is a recent situation and some of the aspects studied are under development when we prepared this article, there are no published scientific or academic documents dealing specifically with the subject. Keywords: University education; pandemic; distance education
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".