O USO INTENSO DAS TECNOLOGIAS DA INFORMAÇÃO E COMUNICAÇÃO NA EDUCAÇÃO BÁSICA EM TEMPOS DE PANDEMIA: DO ESTRANHO AO POSSÍVEL
Bibliographic record
Abstract
The main objective of this work is to understand how the process of the use of technological resources by the school community in the educational offer mediated by Information and Communication Technologies (ICT) during the COVID-19 pandemic, identifying the main challenges faced.The research was developed within the scope of the master's degree, an integral part of the Postgraduate Program in Education (PPGE), of the Federal University of Mato Grosso (UFMT), in the research line School Organization, Training and Pedagogical Practices and is linked to the Research Group Laboratory of Studies on Information and Communication Technologies in Education (LêTECE).In the course of the work, we sought to understand the actions that directly impact public elementary schools in the offer of ICT-mediated education, to identify the main challenges faced, to know how the technological appropriations were made by the school community, which led us to the following guiding question: how was the process of using technological resources by the school community in the offer of ICT-mediated education and what were the main challenges faced during the COVID-19 pandemic?The research has as its methodological strategy the qualitative approach that was adopted through documentary analysis, forms, participant observation, and interviews.This research was conducted in two municipal schools located in the city of Cuiabá, in the state of Mato Grosso.In this environment of a health crisis, it seemed to be a propitious moment for an experiment of possibilities with the arrival of the COVID-19 pandemic, in which public and private schools, in an exceptional way, included in their formative environments the intensive use of ICT.It should be noted that from the research supported by the theoretical contribution, the analysis of the results was generated and summarized in three major themes on the intensive use of devices and applications, the "re"found of teaching and families and schooling in inequalities.The results of the research present a documentary analysis, the various uses of ICT employed during the supply of classes, besides alluding to the possibilities and challenges faced that were collected by the timeliness of the instruments of this research.We emphasize that the mapping of the ICT used, carried out by this research, may help in further research on the subject and support the analysis of pedagogical practices mediated by Information and Communication Technologies.
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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 | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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.
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".