A Multi-Institutional Alternative Assessment Faculty Learning Community: Supporting Teaching in Higher Education
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Faculty learning communities (FLCs) provide opportunities for professional development for faculty, teaching staff, and educational developers in a collaborative and open environment. In this essay, we describe our experience organizing, facilitating, and participating in a multi-institutional FLC with a theme of alternative assessments in STEM. We describe our goals and objectives, the recruitment process and composition, and the structure and scholarly process of the FLC. Based on focus groups conducted with FLC participants, we discuss our collective experience, highlighting outcomes and lessons learned and identifying challenges. Finally, we provide our recommendations for organizing and facilitating multi-institutional FLCs. <em>Primary Image:</em> Close-up photo of a laptop screen with one person’s hand shown using the trackpad and another person’s hand shown pointing at something on the screen, by user John Schnobrich on <a href="https://unsplash.com/photos/FlPc9_VocJ4">Unsplash</a>.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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