A Call for Expanding Inclusive Student Engagement in SoTL
Bibliographic record
Abstract
Scholars in higher education increasingly recognize the transformative potential of student-faculty partnerships focused on inquiry into teaching and learning. However, some students tend to be privileged in SoTL initiatives while others are discouraged, implicitly or explicitly, from engaging in this work. In this paper, we consider why certain students tend to be excluded from SoTL, summarize the possible developmental gains made by students and faculty when diverse student voices are included, and highlight strategies for generating a more inclusive SoTL. We call for expanding student engagement in SoTL by encouraging a diversity of student voices to engage in co-inquiry with faculty. Inclusive engagement has tremendous potential to enhance student and faculty learning, to deepen SoTL initiatives, and to help redress the exclusionary practices that too often occur in higher 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 | 0.063 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.031 |
| Scholarly communication | 0.023 | 0.026 |
| Open science | 0.004 | 0.067 |
| Research integrity | 0.009 | 0.014 |
| Insufficient payload (model declined to judge) | 0.011 | 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".