Development of a synchronous online microscopic anatomy course using virtual microscopy
Bibliographic record
Abstract
The use of virtual microscopy has become a well established and accepted tool for microscopic anatomy instruction. This tool has been tested for its educational effectiveness and it has shown to be as effective as traditional microscopes. The popularity of distance education (DE) courses continues to increase as more students become comfortable with this method of teaching and as more courses are offered. Using the Wimba Collaboration Suite videoconferencing software, we are combining the technologies of virtual microscopy with synchronous videoconferencing to create an online microscopic anatomy course. Our institution has offered a traditional comprehensive microscopic anatomy course for decades. This course includes both lectures and traditional laboratories using microscopes. With online technologies, it is possible to offer the same course, including the laboratory exercises, as a DE course. Synchronous online courses allow many of the benefits of face to face instruction where the instructor can ask questions to check for understanding or the class can have a discussion. The combination of technologies allows this course to be offered to a much wider audience, including participants that are unable to attend campus. Grant Funding Source : Not available
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".