Use of Facebook as a Teaching Tool in a Veterinary Communications Course
Bibliographic record
Abstract
First-year veterinary students enrolled in a Professional Development course were invited to join a Facebook group with the goal of having the instructor use that tool to promote student practice of client communication skills. All members of the class were surveyed to determine any difference in educational outcomes between those students who joined the Facebook group (FB) and those who did not (non-FB). Fifty-one students joined the Facebook group out of a class of 99, and 33 responded to the survey. Forty-four of the non-FB students completed the survey, for a total response of 77%. There was no difference between groups in their general use of Facebook. The only educational outcome that differed between the groups was increased practice of communication skills outside of school by the FB group. Students in the FB group cited interest and desire to access all course materials as the most common reason for joining. They were much more likely to read postings than to post anything themselves. Barriers to greater use of the tool by the FB group included lack of time and hesitance to post when others were not. Students were ambivalent about the use of Facebook as an educational tool. The instructor was unaware of the extent of use of the tool until survey results were gathered and felt that it would be most useful as a teaching tool for those instructors who already used Facebook as part of their personal routine.
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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".