Exploring Students' Perspective on University Exit Exam
Bibliographic record
Abstract
The University Exit Exam is a pivotal assessment for graduating students, yet its effectiveness and relevance are subject of debate. This study investigates architectural engineering students' perspectives on the University Exit Exam at United Arab Emirates University (UAEU) to better understand its impact and identify areas for improvement. Responses were obtained from 26 architectural engineering students through a survey questionnaire comprising both structured and open-ended responses. The responses reveal mixed perceptions regarding the University Exit Exam. While the majority (53.8%) remained neutral, 34.6% agreed that passing the exit exam had a positive impact on their careers. This was primarily attributed to the method of implementing the exam, with a majority (76.9%) indicating a preference for a pass/fail system over a grading system. Over 70 % participants reported some level of stress when higher stake in terms of grades is allocated to the exit exam. It is suggested to rationalize the assessments along with supportive preparatory materials to alleviate anxiety and improve exam relevance. The findings can help improve the design and administration of University Exit Exams by addressing students' perspectives, concerns, and incorporating recommendations. This can enhance exam effectiveness and relevance, leading to improved educational outcomes benefiting both the academia and the professional sphere.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".