Assessment of ESL Sociopragmatics for Informing Instruction in an Academic Context: From Australia to Canada
Bibliographic record
Abstract
This mixed methods study aimed to provide some validity evidence for the use of the ESL sociopragmatics test developed by Roever, Elder and Fraser (2014) for formative purposes. The test developers recommend further validation of the tool, originally developed for the Australian context. In this study, the test items were used to reveal areas of weakness in sociopragmatic knowledge in a group of learners of an academically oriented English Intensive Program in Canada. Analysis of the test scores revealed a lack of knowledge of norms of appropriateness and politeness in English, which was further targeted with an instructional unit informed by the items of the test. Two weeks after the instructional unit was delivered, the participants were asked to complete a follow-up questionnaire. The questionnaire results provided insight into the participants’ perceptions of usefulness of the instructional unit. The learners found explicit instruction on ESL sociopragmatics useful for their language learning experience as well as day-to-day interactions in English. Particularly, they claimed to feel more confident communicating in English after receiving explicit instruction on ESL sociopragmatics. They were able to use information from the lesson in situations such as talking to their language instructors, communicating with university personnel, and participating in service encounter interactions. Therefore, the test proved to have potential for developing instructional materials in an academic context. Based on the findings of the study, suggestions on incorporating sociopragmatic competence into the institution’s EAP curriculum were made.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".