A partnership between an undergraduate student and a university faculty member
Bibliographic record
Abstract
In this reflective essay, we discuss a partnership between a 4th-year undergraduate student and a faculty member in developing and teaching a 3rd-year inquiry-based learning (IBL) course. This partnership, characterized by shared decision-making, introduced a newly defined role: the student course coordinator (SCC). Through this collaboration, a student’s voice was integrated into every stage of the process, from course development and delivery to end-of-course reflection and evaluation.. In many ways, this partnership was akin to an education practicum in which a student gains valuable experience in coordinating and co-teaching a course while developing skills essential for an effective mentor and educator. In this essay, we highlight the context, practicalities, benefits, and challenges of such a partnership and provide our reflections on the experience. We hope the reflections and experiences shared here will provide an account of the value of student voices and partnership in education.
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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 | 0.018 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.025 | 0.017 |
| Scholarly communication | 0.021 | 0.013 |
| Open science | 0.003 | 0.027 |
| Research integrity | 0.007 | 0.014 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".