THE DEVELOPMENT OF A MULTIMEDIA WEB SITE FOR INSTRUCTION OF PEDIATRIC ONCOLOGY.
Bibliographic record
Abstract
Purpose Deficiencies in pediatric oncology (PO) training for residents have been identified internationally. One of the main reasons for this is lack of exposure to pediatric patients during residency training. The goal of this project is to develop a series of Web-based learning modules to supplement current teaching in this area. Methods A Web-based survey was sent to Canadian radiation oncology (RO) program directors and Canadian RO residents. The survey was designed to identify the limitations of current training curriculum and supplemental materials to enhance it. Survey results guided Web site development. The curriculum was developed using teaching modules to focus on specific pediatric tumor sites. Modules followed a common format, reviewing the epidemiology, pathology, radiology, and treatment planning for each tumor. A self-assessment tool was included at the end of the modules, allowing learners to evaluate their grasp of topics. Results Survey results indicated a need for novel teaching methods in pediatric RO. One hundred percent (10/10) of Canadian RO program directors and 66% (69 of 106) of Canadian RO residents responded to the survey. More than 55% (38 of 69) of residents felt that teaching in pediatric RO was inadequate in comparison with other areas of RO. Fifty-five percent (15 of 27) of senior residents felt unprepared for questions in pediatric RO on qualifying board examinations. Over 90% (63 of 69) of respondents felt that a Web-based teaching tool would be a useful supplement to traditional teaching methods. Four modules have been written to date. Theses include brain tumors, sarcomas, Wilms9 tumor, and pediatric specialty tumors. Web development for the project is continuing. Efforts are being made to increase the use of problem-based learning and clinical skills in the Web site. Preliminary results indicate that users find this Web site useful to supplement their learning in PO. Conclusions This is a unique project utilizing Web-based learning modules to teach pediatric RO. This educational program will allow self-directed study in the area of pediatric RO, providing more effective learning of this challenging yet essential area of study.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".