How Educational Developers can Re-engage Mid-Career Faculty Using SoTL
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
Mid-career faculty (MCF) currently make up a significant number of faculty at higher educational institutions. This group comprises key stakeholders with institutional history, diverse teaching and learning experiences, and strong relationships with colleagues. While faculty need different kinds of support and opportunities at different career stages, it has been reported that mid-career professional development is under-researched and overlooked. We contend that professional development for MCF is essential if these faculty are going to continue to grow as educators, leaders, and scholars. With the support of Educational Developers (EDs), the Scholarship of Teaching and Learning (SoTL) is one way for faculty to focus their professional development in the middle years of their career. Drawing on the literature about challenges for MCF and using the micro-meso-macro-mega framework, we explore ways in which EDs can use SoTL to re-engage MCF on a revitalized path. Our synthesis offers reflections on our career experiences as EDs and boundary-spanning points to ponder for both EDs and MCF as they enter into SoTL engagement.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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