Bibliographic record
Abstract
The impact of a peer teaching exercise for an online histology course has been assessed using a mixed method approach. Students signed up for a time they would be available to meet live in the virtual classroom. Each week, students were given specific virtual slidebox assignments which they uploaded into the classroom with full annotations. At their group meeting time, members would log into the classroom and take turns presenting their slides; presentations were archived for future reference. Other students were free to ask questions and the course instructor was either present live or viewed the presentation archive at a later time to ensure accuracy or provide clarification. Laboratory grades improved significantly compared to the previous year when peer teaching was not included (+9.4% (p<0.05)). Student surveys indicated that students believed that teaching others was “very helpful” (67%) or “helpful” (33%) for enhancing their understanding of course material compared to 100% who found attending presentations “helpful” for enhancing their understanding. In summary, we have shown that peer teaching in the online environment is an effective means to enhance student learning. Grant Funding Source : Social Sciences and Humanities Reseach Council of Canada
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 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 | 0.008 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".