Peer and teacher assessment of second-language writing in high- and low-stakes conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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 it