A "sala de aula invertida" no contexto de inglês para fins acadêmicos
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.
Bibliographic record
Abstract
With the rapid diffusion of Digital Information and Communication Technologies (TDIC) within the classroom, there was a need for new approaches and teaching methodologies to emerge. This dissertation aims to contribute to studies on the teaching-learning relationship of an additional language, mediated by technologies, more specifically in the use of the Flipped Classroom (SAI) methodology, for teaching English for Academic Purposes (EAP) . A research was carried out in a mini-course for candidates to a postgraduate program at the Federal University of Uberlndia. The data were collected through electronic forms answered by student-participants in which they were able to reflect on the use of the Flipped Classroom methodology and how they could perceive barriers or opportunities, besides weekly evaluations in relation to the knowledge about the Language and the ability of reading in English, with reference to the Canadian Language Benchmarks (CLB). It is a qualitative perspective of research of an ethnographic nature, guided by the assumptions of Ecological Linguistics and the model of Andragogy education. The collected data were analyzed from the Content Analysis (CA) and show that the students perceived that the Flipped Classroom methodology can provide opportunities for the learning of an additional language, even without the physical presence of the teacher. In addition, there was an evolution in the self evaluation of knowledge about a language skills.
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 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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it