Is There a Better Time to Focus on Form? Teacher and Learner Views
Bibliographic record
Abstract
This study investigated the views of teachers and learners regarding the timing of grammatical instruction, conceptualized as a distinction between isolated and integrated form‐focused instruction ( FFI ) proposed by Spada and Lightbown (2008). Both types of FFI are described as taking place in primarily meaning‐based communicative classrooms. They differ in that isolated FFI occurs separately from communicative activities, whereas integrated FFI occurs during communicative activities. Using this theoretical distinction, the researchers developed teacher and learner questionnaires and validated them as measures of both constructs supported by factor analysis. The questionnaires were administered to explore the views of teachers and learners in two contexts, ESL in Canada and EFL in Brazil. Quantitative and qualitative analyses of the questionnaire data indicate a distinct preference for integrated FFI across groups (i.e., teachers and learners) and contexts (i.e., EFL and ESL ). At the same time teachers and learners also acknowledged the value of isolated FFI . These views recognizing the important roles played by both integrated and isolated FFI are consistent with those discussed in the instructed second language acquisition literature. Teachers and learners also drew attention to contextual and individual differences that may have an impact on decisions about the timing of grammatical instruction.
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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 | 0.006 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".