Impact of English Interaction upon Chinese EFL Teachers' Pragmatic Competence in a Study-Abroad Context
Bibliographic record
Abstract
This study is a longitudinal investigation in the effectiveness of interactive exposure on the acquisition of English requests in a study-abroad setting. Nineteen Chinese teachers, who taught English as a foreign language in China, attended a short-term teacher-training program in Canada and had access to opportunities for authentic interaction with native English speakers. Another 19 Chinese EFL teachers who had never been to an English speaking country served as the comparison group. Twenty English native speakers were also recruited to provide native norms for the pragmatics assessment measures. Three research questions were addressed in this study. First, I examined what kind of interactive exposure was accessible to the study abroad teachers, and investigated what types of interactive activities might contribute to pragmatics learning. Second, I examined whether study-abroad teachers demonstrated approximation to native speaker norms with regard to requesting through two tests: a written discourse completion task (WDCT) and an appropriateness judgment task (AJT). Finally, I explored whether the study-abroad experience had increased teachers’ confidence in teaching English pragmatics. The data analysis of the study-abroad teachers' logs showed that they were engaged in a much wider variety of English interactive activities than the at-home teachers. They also demonstrated a more significant growth in pragmalinguistic and sociopragmatic awareness in certain situations, but failed to acquire a full range of the native-like forms. Compared with native English speakers, the Chinese teachers used similar external modifiers, but less variety in request formulae and internal modification. They did not appear to realize that some strategies and formulae are context-based and scenario-specific. However, their confidence in teaching pragmatics was enhanced. The findings show that social interaction, cultural values, pragmatic transfer, social role, and living arrangement are factors affecting L2 pragmatic acquisition in a study-abroad context. The results also reveal that it is difficult for adult L2 learners to develop native-like pragmatic competence in a naturalistic setting, due to a lack of sufficient target language exposure, corrective feedback, and explicit pragmatic 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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".