Putting Students in Charge: A Symposium on Student-Centered Learning
Bibliographic record
Abstract
BACKGROUND: Many symposia and workshops are held to discuss issues of student-centered learning, but few put students in charge. DESCRIPTION: An international meeting was held at McMaster University, Hamilton, Ontario, Canada, to discuss Student-Centered Learning in the Life and Health Sciences where there were no plenary, oral, or poster presentations. Sessions were run in a problem-based, small-group format. Educational problems written specifically for the symposium served as springboards for learning. Undergraduate and graduate science students took center stage by taking an active role in the planning and organization of the event and serving as chairs and facilitators for the sessions. In addition, they summarized the sessions in written reports, which thus enabled their opinions to be documented. Eminent educators from several countries (Australia, Denmark, Spain, Portugal, Finland, the UK, and the United States) participated in these sessions as both learners and content experts. EVALUATION: A questionnaire as well as comments suggested that the participants enjoyed the learning experience, which gave faculty, staff, and students opportunity to discuss in-depth educational issues related to process, content, and delivery of curricula.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.017 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.007 | 0.012 |
| Insufficient payload (model declined to judge) | 0.018 | 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".