The impact of anxiety on undergraduate students’ outcomes during prosthetic exam
Bibliographic record
Abstract
Introduction: Anxiety is a natural reaction to stress, and anxiety due to a test impair knowledge and negatively influence examination performance.The subject of prosthetic dentistry is vast and difficult, requiring a high level of specialized expertise in areas of clinical dentistry that involve very difficult processes.Objectives: To evaluate the impact of exam's anxiety on students' experience and performance during pros thodontics exam.Material and methods: There were 790 students enrolled into the study.Before opening the exam papers, all students completed a questionnaire.Likert scale, ranging 1 to 5, was used to assess the amount of anxiety.Link between student's degree and student's anxiety was determined with Kandall's tau test, and comparison between genders was determined using independent sample ttest.Level of significance was set at p < 0.05.Results: Between student's degree and anxiety level, there was a significant link (p < 0.05).Male and female degrees differed significantly (p < 0.05); male degrees (16.45) were higher than female degrees (15.33).Males experienced normal levels of anxiety, whereas females experienced anxiousness.Conclusions: Anxiety can affect dentistry students during prosthodontic exams.All pupils experienced anxious ness showing a mean level of anxiety.Male outcomes were better than females' , and males experienced typical levels of anxiety, whereas females experienced anxiousness.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".