Production of Third-Person Singular –s And be Copula in Communication Tasks by Vietnamese EFL Learners: Acquisition Order and Learner Orientation to Form
Bibliographic record
Abstract
Research on the acquisition order of inflectional morphemes in English has shown that third-person singular –s (3SG–s) is challenging to acquire and acquired later than be copula by both L1 and L2 learners of English. In a departure from the usual practice of controlled elicitation, the current study investigated the production of these two forms by Vietnamese EFL learners in oral communication tasks performed in intact classrooms. Vietnamese L1 does not inflectionally mark 3SG–s although the construction of be copula in Vietnamese and English shares some features. These differences motivated the selection of the two target forms. Nine pairs of Vietnamese EFL university students were recorded performing five communicative tasks generated contexts for use of 3SG–s. over three weeks in their normal classes. Performance data were transcribed and analyzed for frequencies of production and omission of the two target forms in obligatory contexts. After completing the tasks, the students were interviewed about what they attended to when performing the tasks. Interview transcripts were analyzed thematically. Results show that the learners omitted 3SG–s in most obligatory contexts and across all tasks. They were better at accurately producing be copula than 3SG–s but accuracy rates varied between learners. Interview data revealed the conscious decisions learners made concerning the accuracy of their language production. The findings are discussed with reference to different theoretical models. The study advances understanding of acquisition of 3SG–s and be copula by EFL learners and offers pedagogical implications for how a focus on inflectional forms can be managed in oral communicative task performance.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".