Student evaluation web sites as potential sources of consumer information in the United Arab Emirates
Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate the attitudes of students in the United Arab Emirates (UAE) towards non‐institutionally sanctioned student evaluation web sites, and to consider how educational institutions might respond to the demands of students for specific information. Design/methodology/approach The study involved a self‐completed questionnaire administered to 118 undergraduate students at a single university in the UAE. Findings Even though there exists no UAE‐based web site that carries student evaluations of faculty/teaching, 13 per cent of the survey participants had previously visited a site that held student ratings, 85 per cent said they would consider posting on one if it existed in the country, and just over a half of the students were in favour of such web sites being established in the UAE. Research limitations/implications Despite limitations, such as the sample size and convenience sampling strategy, it is clear that students appreciate information about course evaluations and that educational institutions should consider how students obtain this information. Practical implications The advent of student evaluation web sites in the UAE could bring a set of challenges and opportunities to educational institutions, but, whether they are established or not, institutions might benefit from developing effective strategies for the dissemination of course evaluation and other student‐related data in the near future. Originality/value Student evaluation web sites, such as RateMyProfessors.com, are popular in the USA, Canada and the UK, but it was unknown how students in a relatively conservative country such as the UAE would react to such web sites. Educational institutions can use the findings of this study to develop suitable policies and strategies that address the issues discussed herein.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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, 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".