Role-play and dialogic meta-pragmatics in developing and assessing pragmatic competence
Bibliographic record
Abstract
Abstract Role-play as a bridging and integrating practice in language teaching and development of pragmatic competence in learners is well-established. In an EAP classroom ( Van Dyke & Acton, 2021 ) explored the impact of one fluency protocol, Cooperative Attending Skills Training, by which students were trained to listen attentively to shared personal stories, working toward more sophisticated strategies of conversational interaction. That system included dialogic, pragmatics-focused, spontaneous analysis and instructor-student discussion of interactional discourse features. With that experience, further modeling and conceptual input, participants in this study engaged in six role-plays, each involving a problem requiring pragmatic accommodation. The data from transcribed role-plays were analyzed in terms of pragmatic discourse functions and NVivo-based thematic threads. The generally successful application of the targeted skills and concepts by course end most likely resulted from the engaging meta-pragmatic interactions preceding the role-plays, and the formal and informal instructor feedback related to implicature, prosody, implicit understandings, direct conversation strategies, grammar, and vocabulary.
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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 | 0.018 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| 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".