Comparison of Traditional Lecture-Based Learning versus Interactive Electronic Book Learning in Veterinary Student Comprehension of Inhalant Anesthetic Administration, Uptake, and Elimination
Why this work is in the frame
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Bibliographic record
Abstract
The administration, uptake, and elimination of inhalant anesthetics is a challenging topic in the veterinary curriculum, and lecture-based learning is often insufficient to ensure that students understand these concepts. We hypothesized that the use of an interactive electronic book (e-book) would enhance student comprehension of the material. Two sequential Doctorate of Veterinary Medicine student cohorts participated in a prospective controlled study. The first cohort received traditional lecture-based learning while the second cohort was taught the topic using an interactive e-book. Student comprehension of the material was assessed twice during the course via multiple-choice questions: five questions in a midcourse quiz and seven within the final exam. At the end of the course, students also completed a Likert survey assessing their confidence regarding the topic. Averaged across assessment types, students taught using the interactive e-book scored higher than those taught via the traditional method (p < .001). Final exam scores were significantly higher in the e-book cohort compared with the lecture-based cohort (p < .001). However, there was no difference in quiz scores between groups (p = .109). No significant difference was found between groups in responses to the Likert survey. In conclusion, students using the interactive e-book had better comprehension of the material than students in the traditional lecture group as measured by their scores on multiple-choice question assessments. Future studies are needed to determine whether this advantage persists later in the curriculum when students apply these concepts in the clinical year.
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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 | 0.003 | 0.002 |
| 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 | 0.001 |
| 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 it