A Technique for Obtaining Feedback from Students Using a Computer Program in a Veterinary Anesthesia Course
Bibliographic record
Abstract
INTRODUCTION: The College of Veterinary Medicine at Michigan State University has been using computer-aided instructional programs in our pre-clinical veterinary anesthesia course. We describe an embedded feedback collection module (FCM) that facilitates the process of formative evaluation of the program. METHODS: The instructional program was divided into discrete sections. The FCM was accessed easily from all sections of the program. Instructions for use of the FCM were delivered orally to all users of the instructional program and were included in the introduction section of the program. RESULTS: Feedback was obtained from successive classes of veterinary students over four years, using our computer-aided instructional program. Students in each class were required to use the program either in class or for review and to leave at least one comment in the FCM. Of the 653 responses, 293 were positive and expressed appreciation for the program, 209 contained specific comments or suggestions, and 151 were questions relating to the subject material contained within the program. Written survey feedback was also obtained from some students in these classes. CONCLUSION: Our FCM was effective and easy to implement. It proved an easy way to obtain user feedback, which was used in the ongoing process of program design and content improvement.
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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 | 0.002 | 0.001 |
| 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 | 0.001 |
| 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 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".