The impact of collocational proficiency features on expert ratings of L2 English learners’ writing
Bibliographic record
Abstract
Abstract Lexical proficiency is a multifaceted phenomenon that greatly impacts human judgments of writing quality. However, the importance of collocations’ contribution to proficiency assessment has received less attention than that of single words, despite collocations’ essential role in language production. This study, therefore, investigated how aspects of collocational proficiency affect the ratings that examiners give to English learner essays. To do so, collocational features related to sophistication and accuracy were manipulated in a set of argumentative essays. Examiners then rated the texts and provided rationales for their choices. The findings revealed that the use of lower-frequency words significantly and positively impacted the experts’ ratings. When used as part of collocations, such words then provided a small yet significant additional boost to ratings. Notably, there was no significant effect for increased collocational accuracy. These findings suggest that low-frequency words within collocations are particularly salient to examiners and deserving of pedagogic focus.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.005 | 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".