Instrução-focada-na-forma, lingualização e aprendizagem de ILE por aprendizes brasileiros Form-focused instruction, languaging and the learning of English as a foreign language (EFL) by Brazilian learners
Bibliographic record
Abstract
Este estudo examina o conceito de lingualização (Swain, 2006) em contexto de instrução-focada-na-forma e o seu papel como uma importante ferramenta a ser utilizada por aprendizes de brasileiros de língua estrangeira, sejam avançados ou de nível elementar, se o objetivo é a precisão linguística. Com o apoio da teoria sociocultural da mente de Vygotsky (1978) e com base nos estudo desenvolvidos por Swain no contexto canadense, assim como nos de Vidal (2003) em contexto brasileiro, ambos com alunos avançados, a investigação mostra como aprendizes brasileiros de língua inglesa de diferentes níveis de proficiência e de diferentes realidades instrucionais se beneficiam com a lingualização _ o processo de se construir significado e moldar conhecimento e experiência por meio da própria língua-alvo. Análise qualitativa de diálogo colaborativo e de feedback corretivo fornecem evidências para a reivindicação. Sugere-se que a instrução-focada-na-forma via reflexão consciente sobre uso de língua parece um recurso pedagógico muito atraente para ajudar aprendizes de ILE a aprender a língua-alvo, assim como a desenvolver sua interlíngua. This paper examines the concept of languaging (Swain, 2006) in the context of form-focused instruction and its role as an important tool for Brazilian foreign language learners, both at advanced level and at elementary level, if linguistic precision is the target. Supported by the Vygotskian sociocultural theory of mind (Vygotsky, 1978) and based on studies developed by Swain (2006) in the Canadian context and by Vidal (2003) in the Brazilian scenario, both with advanced learners, the paper shows how Brazilian learners of English of different levels of proficiency and from different instructional realities benefit from languaging _ the process of making meaning and shaping knowledge and experience through target-language use. A qualitative analysis of both collaborative dialogue and corrective feedback provide evidence for the claim. It is suggested that form-focused instruction via conscious reflection on language use seems to be a very attractive pedagogical resource to help learners EFL to develop their interlanguage further as well as it serves language learning
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".