A Comparative Genre Study of Spoken English Produced by Chinese EFL Learners and Native English Speakers
Bibliographic record
Abstract
Previous research within the field of argumentation has established that argumen- tation plays an important role in a variety of professions. Written argumentation has been extensively explored and investigated to examine its various aspects, in- cluding argument structures and schemes, argumentative strength, the role of au- dience, the evaluation of argument, argumentative persuasiveness and force, and so on. It appears, however, that few studies have been carried out to address the issues of spoken argumentation. To fill the gap, this article attempts to compare elements of the spoken argumentative genre produced by Chinese EFL learners to those in their native English-speaking counterparts. Findings from the study show that the former group generally produced an exposition genre focusing on one side of the argument, whereas the latter group noted two or more sides of the argument in order to balance the issue. In addition, Chinese EFL learners tended to use a formulaic argument structure, whereas native English speakers used a more discursive pattern. Pedagogical implications and potential directions for future studies on spoken English argumentation are suggested in the conclusion.Des recherches antérieures dans le domaine de l’argumentation ont établi que cette capacité joue un rôle important dans diverses professions. L’argumentation par écrit a été intensément explorée et ses divers aspects bien étudiés, y compris la structure et les schémas, la force des arguments, le rôle du public, l’évaluation du raisonnement, le pouvoir de persuasion, et ainsi de suite. Toutefois, il semble que peu de recherches ont porté sur l’argumentation orale. Afin de combler cette lacune, cet article a comme objectif de comparer des éléments de l’argumentation orale d’apprenants chinois d’ALE à ceux de leurs homologues anglophones. Les résultats de l’étude indiquent que les premiers produisaient, de façon générale, un exposé traitant d’un côté de l’argument alors que les deuxièmes en évoquaient deux aspects ou plus de sorte à équilibrer la question. De plus, les apprenants chinois tendaient à employer une structure argumentative basée sur des formules tandis que les anglophones avaient recours à une structure plus discursive. La conclusion de l’article offre des incidences pédagogiques et des orientations pos- sibles pour la recherche portant sur l’argumentation orale en anglais.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".