The Practice of Cross-Grading in Assessing Writing: The Case of EFL Teachers and Students in a Saudi Arabian Context
Bibliographic record
Abstract
This qualitatively based research study utilized a combination of multiple methods, which aimed at investigating the efficacy and reliability of employing cross-grading when assessing English as a Foreign Language (EFL) tertiary level learners’ writing. It further explored the perceptions of the EFL teachers and learners regarding the cross-grading practices to provide a clearer understanding of this relatively unexplored line of research enquiry. It was set to answer the following research question: In what ways does cross-grading practice contribute to assessing EFL writing? The participants of this study were conveniently selected where the sample included four language instructors from different ethnic and cultural backgrounds, as well as four Saudi EFL learners. Semi-structured interviews were individually conducted with all eight participants. In addition, four one-on-one feedback sessions between language instructors and learners were observed to assess feedback effectiveness after the cross-grading sessions. The data analysis revealed that instructors had difficulty explaining the feedback on their learners’ papers since they did not grade their students’ papers themselves. Furthermore, students felt they did not benefit from the feedback sessions because they could not fully understand the external grader’s markings and, thus inhibiting the learner’s ability to improve and develop their writing. The study concluded with some pedagogical implications for the EFL writing assessment context.
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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 | 0.004 | 0.131 |
| 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 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".