Effect of Differing PowerPoint Slide Design on Multiple-Choice Test Scores for Assessment of Knowledge and Retention in a Theriogenology Course
Bibliographic record
Abstract
Third-year veterinary students in a required theriogenology diagnostics course were allowed to self-select attendance at a lecture in either the evening or the next morning. One group was presented with PowerPoint slides in a traditional format (T group), and the other group was presented with PowerPoint slides in the assertion-evidence format (A-E group), which uses a single sentence and a highly relevant graphic on each slide to ensure attention is drawn to the most important points in the presentation. Students took a multiple-choice pre-test, attended lecture, and then completed a take-home assignment. All students then completed an online multiple-choice post-test and, one month later, a different online multiple-choice test to evaluate retention. Groups did not differ on pre-test, assignment, or post-test scores, and both groups showed significant gains from pre-test to post-test and from pre-test to retention test. However, the T group showed significant decline from post-test to retention test, while the A-E group did not. Short-term differences between slide designs were most likely unaffected due to required coursework immediately after lecture, but retention of material was superior with the assertion-evidence slide design.
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 | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".