The Intersection of Student Assessment and Faculty Learning
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
The primary aim of institutional learning outcomes assessment is the creation of a culture of assessment where faculty use evidence-based data to validate and improve teaching and learning for the benefit of students. Faculty are key to these processes and yet, they are often woefully disengaged from them. This paper presents findings from an action research project that utilized a collaborative self-study approach to engage faculty in the strategic assessment of institutional learning (SAIL). SAIL is an immersive professional development opportunity that bridged quality assurance with meaningful improvements in the classroom. Findings indicated that cross-disciplinary dialogue about assessment increased faculty awareness of the (mis)alignment between course, program, and institutional learning aims while also identifying and informing potential gaps in curriculum and program design. SAIL is an excellent mechanism to engage faculty in an immersive assessment of student achievement that may then lead to meaningful improvement in teaching and learning.
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 | 0.004 | 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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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