Faculty Learning Processes: A Model for Moving from Scholarly Teaching to the Scholarship of Teaching and Learning
Bibliographic record
Abstract
This essay explores the development and conceptual validation of the Faculty Processing Model for SoTL through anecdotal reports gathered from six institutions and additional survey data collected from three institutions. The results identified how faculty learning occurred through faculty development activities across various campuses and how that faculty learning cumulatively represented distinctive developmental stages that led to both cognitive and affective transformations for the professors’ and their students’ learning. This analysis provided a first step in understanding the efficacy of faculty development activities in relation to their impact on student and faculty learning and upon practicing the Scholarship of Teaching and Learning.
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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 | 0.066 | 0.153 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.026 | 0.000 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.020 |
| 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; both teacher heads agree on what is shown here.
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".