<i>National Dietetic Registration Examination</i>: Perceptions of the Writing Experience
Bibliographic record
Abstract
PURPOSE: Dietitians must pass the Canadian Dietetic Registration Examination (CDRE) to practise. Writers' experiences with the exam were examined, along with factors associated with anxiety and coping mechanisms, preparation strategies, and if and how anxiety, coping, and preparation strategies are perceived to be related to exam performance. METHODS: An exploratory descriptive methodology with a researcher-designed questionnaire was used to collect data from a purposive sample in 1999 and 2000 (n=54), and from a convenience sample in 2005 and 2006 (n=11). Participants were CDRE writers from Nova Scotia, New Brunswick, and Ontario. RESULTS: Meaningful preparation was correlated with a more positive exam experience (p=0.023). Writers experiencing lower preparation anxiety were more confident they had passed (p=0.016). Successful coping strategies resulted in decreased writing anxiety (p=0.029). The 2005 to 2006 cohorts prepared less (p=0.004) and experienced less preparation anxiety (p=0.02). Five themes emerged, which extend our understanding of the exam-writing experience. CONCLUSIONS: Several strategies may positively influence writing anxiety and improve the overall writing experience. Individuals and organizations and/or writers can consider these findings as they engage in the exam process, revise and/or develop support material, give presentations, or provide advice.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".