Bibliographic record
Abstract
This research seeks to further knowledge on student and faculty evaluation of teaching within a small Asian university, with the aim of exploring the relationship between students and faculty perceptions of teaching. It seeks to establish faculty perception of fairer mechanisms or collective mechanisms for evaluating teaching, learning, and curriculum course materials towards evaluating the faculty. This contrasts with common use of student evaluation of teaching as a single approach. Faculty perceptions of student evaluations of teaching have been well researched in several contexts but less so in Middle Eastern universities with highly transient faculty drawn from different countries across the world.Mixed methods, secondary and primary data of student and faculty evaluations of teaching are studied. Course materials and instruction ratings are found to be moderately correlated. Faculty are satisfied with the use of the student evaluation and faculty self-evaluation of teaching. However, outcomes of faculty self-evaluation and student evaluation of teaching are moderately positively correlated. Outcomes of student and faculty evaluations of teaching are found to be clustered at the upper end of the Likert scale. The implication is that there are small differences between scores from student evaluation and faculty self-evaluation of teaching. However, findings from the qualitative comments provide more valuable policy arguments. The findings indicate that half of the faculty agree or strongly agree with the use of SETs for customer satisfaction or as a control tool. However, a model that combines multiple evaluation tools is suggested by faculty for a holistic evaluation.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
| gpt | no category Domain: not available · Genre: Other About the Canadian research system: no · About a Canadian topic: no | Theoretical or conceptual | low |
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 | 0.135 | 0.104 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.015 | 0.007 |
| Science and technology studies | 0.005 | 0.016 |
| Scholarly communication | 0.030 | 0.022 |
| Open science | 0.005 | 0.021 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".