Pandemia da covid-19 e os impactos nas atividades acadêmicas no brasil
Bibliographic record
Abstract
A pandemia COVID-19 intensificou a diversidade de tecnologias de aprendizagem na educação superior, de maneira impositiva, desmistificou usos remotos, à fronteira da totalidade do ensino à distância a todos cursos superiores, em atendimento aos protocolos sanitários. Todavia, os eixos de aprendizagem (Ensino-Pesquisa-Extensão), tiveram que se adequar ao emprego das tecnologias educacionais. Sob essa abordagem, emergem questões, buscando examinar impactos que os docentes vivenciaram na pandemia para assegurar continuidade de tais eixos. Os dados contaram com 560, respostas válidas, de docentes da educação superior, distribuídos em todas regiões do Brasil. O estudo de abordagem quantitativa contou com o método da estatística não paramétrica, teste qui-quadrado, teste exato de Fischer e U de Mann Whitney. Resultados demonstraram que a adaptação e adoção de novas estratégias aos eixos de aprendizagem foram superadas pelos docentes sem identificações de impactos notórios que gerassem barreiras ou impeditivos. Entretanto, as relações familiares e sociais, assim como a saúde mental e física dos docentes, despertaram como impactos percebidos. Estudos foram sugeridos empregando expectativas diversas, sob contextos que analisem a exclusão digital e a saúde mental como interseccionalidade e enfoque de discussão em período pandêmico e pós-pandemia em países em desenvolvimento. The pandemic COVID-19 intensified the diversity of learning technologies in higher education, in an imposing way, demystified remote uses, to the border of the totality of distance learning to all higher education courses, in attendance to sanitary protocols. However, the learning axes (Teaching-Research-Extension) had to adapt to the use of educational technologies. Under this approach, questions emerge, seeking to examine the impacts that the teachers experienced in the pandemic to ensure the continuity of these axes. The data counted on 560 valid answers from teachers of higher education, distributed in all regions of Brazil. The quantitative approach study relied on the non-parametric statistical method, chi-square test, Fischer's exact test, and Mann Whitney's U test. Results showed that the adaptation and adoption of new strategies to the learning axes were overcome by the teachers without the identification of notorious impacts that would generate barriers or impediments. However, family and social relationships, as well as the mental and physical health of the faculty members aroused as perceived impacts. Studies were suggested employing diverse expectations under contexts that analyze digital exclusion and mental health as intersectionality and focus of discussion in pandemic and post-pandemic period in developing countries.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".