Canine Theriogenology for Dog Enthusiasts: Teaching Methodology and Outcomes in a Massive Open Online Course (MOOC)
Bibliographic record
Abstract
A massive open online course (MOOC) in canine theriogenology was offered for dog owners and breeders and for veterinary professionals as a partnership between the University of Minnesota and Coursera. The six-week course was composed of short video lectures, multiple-choice quizzes with instant feedback to assess understanding, weekly case studies with peer evaluation to promote integration of course materials, and discussion forums to promote participant interaction. Peak enrollment was 8,796 students. The grading policy for completion was strict and was upheld; completion rate for all participants was 7.5%. About 12% of participants achieved a grade of over 90% in the course, with those who had any deficiency mostly missing one quiz or assignment. Ninety-nine individuals were enrolled in a for-cost, credentialed pathway, and 50% of those individuals completed all required course components. Pre- and postcourse surveys were used to demonstrate that learning objectives were met by the participants and to identify that lack of time to commit to study was the biggest impediment to completion. Positive aspects of the course were active engagement by participants from all over the world and the ability of this university and instructor to reach those learners. Negative aspects concerned technical support and negative feedback from some participants who were unable to meet course requirements for reasons beyond the control of the instructor.
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 | 0.005 | 0.006 |
| 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".