A meta-analysis of the effects of instruction and corrective feedback on L2 pragmatics and the role of moderator variables
Bibliographic record
Abstract
Abstract This paper reports the results of a meta-analysis of 39 published studies conducted during the last decade (from 2006 to 2016) on the effects of instruction and corrective feedback on learning second language (L2) pragmatics. The study meta-analyzed the effects of instruction in terms of several moderator variables including mode of instruction, type of instruction, outcome measures, length of instruction, language proficiency, and durability of the instructional effects. It was found that (a) computer-assisted instruction generated larger effects than face-to-face instruction, (b) instruction was generally more effective for L2 pragmatic comprehension than production, (c) instruction produced larger effects when tested by selected response outcome measures although different patterns were observed across explicit-implicit categories, (d) longer treatments generated a larger effect size than shorter treatments, (e) studies conducted with intermediate level learners produced larger effect sizes than beginner or advanced level learners, and (f) the observed effects of instruction were maintained.
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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 | 0.029 | 0.066 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.033 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".