Bibliographic record
Abstract
Despite the importance of pragmatics, the study of the acquisition of pragmatic competence seems to be an area of research that has been somewhat neglected.To broaden the scope of interlanguage pragmatics, this study was conducted to compare the effect of implicit versus explicit instruction in the development of pragmatic competence of EFL learners.To fulfill the purpose of the study, sixty intermediate learners of English were chosen from two language institutes and were randomly assigned to two experimental groups.The materials for the instruction were dialogues in which the speech act of 'apology' had been presented.The experimental group (1) received implicit instruction.The instructor read the dialogues and asked the learners to repeat them.The experimental group (2) received explicit instruction through explanation, list of apologies and five semantic formulae of 'apology'.Data were collected by means of a pretest and posttest administered before and after the training period that lasted thirteen sessions.Results of the two experimental groups denoted the positive effects of two kinds of instructions, although the explicit instruction group outperformed the implicit instruction group.In addition, this study adds to the small, but growing, body of research on interlanguage pragmatic development in foreign language.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.001 |
| Insufficient payload (model declined to judge) | 0.965 | 0.932 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".