Comparing the Comprehension of the One Health Concept Among Veterinary Students in Online and Classroom Teaching Settings
Bibliographic record
Abstract
The integration of the One Health concept into veterinary education is critical for preparing future professionals to address the interconnectedness of human, animal, and environmental health. This study aimed to compare the comprehension of the One Health concept among veterinary students in online ( n = 48) and classroom ( n = 49) teaching settings and to assess changes in their awareness following instruction by administering pre- and post-course questionnaires to evaluate students’ attitudes and perceptions of the One Health concept. An enhancement was noted from before to after education in both settings. However, no significant differences between the online and classroom settings for any of the questions before or after education were detected ( p > .05). The students’ perspectives on the course methodology employed were not statistically different ( p = .25) between classroom teaching and online teaching. In conclusion, both online and traditional classroom instruction can effectively enhance veterinary students’ perceived comprehension of the One Health concept. This underscores the versatility of instructional modalities and emphasizes the need for flexibility in educational practice to meet the diverse needs of learners.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".