Assessment Practices of Preparatory Year English Program (PYEP): Investigating Student Advancement through Third and Fourth Levels
Bibliographic record
Abstract
This small-scale mixed method research focuses on investigating the way Preparatory Year English Program (PYEP) female students in a Saudi tertiary level institution context are assessed and how they are advanced from level three (Pre-intermediate) and level four (Intermediate). A four-point agreement scale survey was conducted with fifteen English as a Foreign Language (EFL) teachers in the PYEP to critically investigate the issue from their own perspective. Furthermore, semi-structured interviews were conducted with eight EFL students studying in PYEP in the third and fourth levels. The analysis of the data indicated that teachers were lenient in grading students. They tend to adjust grading practices to the benefit of the students, so students were allowed to pass and progress to the next level up. Additionally, the interviewed students argued that teachers could help them by granting them up to five grace marks to pass their exams. The study also showed that teachers possessed sufficient power in assigning grades following assessment. They used this power to the advantage of their students to make them advance to the following level. The study concludes with suggestions and recommendations for further 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".