Peer and teacher assessment of second-language writing in high- and low-stakes conditions
Bibliographic record
Abstract
Abstract This study aimed to compare second-language (L2) students’ ratings of their peers’ essays on multiple criteria with those of their teachers’ under different assessment conditions. Forty EFL teachers and 40 EFL students took part in the study. They each rated one essay on five criteria twice, under high-stakes and low-stakes assessment conditions. Multifaceted Rasch Analysis and correlation analyses were conducted to compare rater severity and consistency across rater groups, rating criteria and assessment conditions. The results revealed that there was more variation in students’ ratings than the teachers’ across assessment conditions. Additionally, both rater groups had different degrees of severity in assessing different criteria. In general, students were significantly more severe on language use than were teachers; whereas teachers were significantly more severe than were peers on organization. Student and teacher severity also varied across rating criteria and assessment conditions. The findings of this study have implications for planning and implementing peer assessment in the L2 writing classroom as well as for future research.
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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 | 0.010 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".