Evaluation of a mentored teleconferencing graduate course in psychosocial oncology research : iniated at four Canadian universities
Bibliographic record
Abstract
This report summarizes the evaluation process and outcomes of a thirteen-week McGill University mentored doctoral-level course, (NUR2 783) "Psychosocial Oncology Research." This seminar-based initiative in Psychosocial Oncology Research Training - PORT (Loiselle, Degner, Butler, Bottorff, 2003-2009, ST1-63285), is a core component of the CIHR-ICR/NCIC Strategic Training in Health Research program. The purpose of this study is to investigate the benefits of using, web-based learning environments and their effects and students' reactions to using instructional technologies for learning. This training course focused on evidence-based research developments in psychosocial oncology---the study of personal, contextual, and social factors that affect people's experience with cancer. The evidence base interventions were conferred through weekly seminars mediated through a videoconferencing medium broadcast within four Canadian Universities, a two-day face-to-face workshop and a computer-mediated communication system, WebCT. Data was collected through questionnaires and surveys, interviews and observations. Results showed the trainees had acquired effective learning strategies prior to the course, experience with computer based technologies especially an asynchronous medium such as electronic mail and learned best when the acquisition of knowledge was meaningful. The trainees indicated having gained a significant amount of knowledge to apply to their professional lives. The computer-mediated communication system made available to the trainees and mentors to provide a collaborative conference area, view the course syllabus, exchange ideas, confer through synchronous and asynchronous discussions, access information and documents, was quite inactive
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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 | 0.031 | 0.034 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".