Radiation <scp>O</scp>ncology <scp>T</scp>raining <scp>P</scp>rogram <scp>C</scp>urriculum developments in <scp>A</scp>ustralia and <scp>N</scp>ew <scp>Z</scp>ealand: Design, implementation and evaluation – What next?
Bibliographic record
Abstract
INTRODUCTION: The Australian and New Zealand Radiation Oncology Training Program has undergone major changes to align with pedagogical principles and best-evidence practice. The curriculum was designed around the Canadian Medical Education Directives for Specialists framework and involved structural programme changes and new in-training assessment. This paper summarises the work of programme design and implementation and presents key findings from an evaluation of the revised programme. METHODS: An independent team conducted the evaluation during the last year of the first 5-year curriculum cycle. Opinions were sought from trainees, supervisors and directors of training (DoTs) through online surveys, focused interviews and group consultations. One hundred nineteen participated in surveys; 211 participated in consultations. All training networks were represented. RESULTS: The new curriculum was viewed favourably by most participants with over 90% responding that it 'provided direction in attaining competencies'. Most (87/107; 81%) said it 'promotes regular, productive interaction between trainees and supervisors'. Adequacy of feedback to trainees was rated as only 'average' by trainees/trainers in one-third of cases. Consultations revealed this was more common where trainers were less familiar with curriculum tools. Half of DoTs/supervisors felt better supported. Nearly two-third of all responders (58/92; 63%) stated that clinical service requirements could be met during training; 17/92 (18.5%) felt otherwise. When asked about 'work-readiness', 59/90 (66%) respondents, including trainees, felt this was improved. CONCLUSION: Findings suggest that the 'new' curriculum has achieved many of its aims, and implementation has largely been successful. Outcomes focus future work on better supporting trainers in using curriculum tools and providing useful feedback to trainees.
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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 | 0.016 | 0.054 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".