Grammar Correction in the Writing Centre: Expectations and Experiences of Monolingual and Multilingual Writers
Bibliographic record
Abstract
Although most writing centres maintain policies against providing grammar correction during writing tutorials, it is undeniable that students expect some level of grammar intervention there. Just how much students expect and receive is a matter of speculation. This article examines the grammar-correction issue by reporting on a survey of L1, L2, and Generation 1.5 (Gen 1.5) writing-centre attendees. Results reveal that while all groups expected grammar help, L2 students expected the most. In addition, L1 and Gen 1.5 writers reported receiving more grammar help than they expected. These findings suggest that tutors may not distinguish the language needs of L1 writers from those of Gen 1.5 and L2 writers; meanwhile, they may generally provide more grammar support to all tutees than writing-centre training and ideology recommend. The findings of this study may help writing centres craft more nuanced grammar policies and provide critical tutor training to better match students’ needs and expectations.
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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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".