4. Responding to the Challenging Dilemma of Faculty Engagement in Research on Teaching and Learning and Disciplinary Research
Bibliographic record
Abstract
Over the past two decades, the scholarship of teaching and learning (SoTL) has received increased attention in academe. Broadly conceptualized as an area which combines the experience of teaching with the scholarship of research, and the dissemination of this knowledge such that the broader academic community can benefit from this scholarly product, SoTL has been regarded as a primary means to increase the quality and value of teaching in higher education. This paper explores five challenges which contribute to the dilemma of faculty engagement in research on teaching and learning: limited expertise, the graduate studies culture, terminology (SoTL is widely misunderstood), reward and recognition, and time constraints. Responses to these challenges are presented in hopes of contributing to a positive dialogue for change, where faculty engagement in research on teaching and learning not only continues to grow, but becomes firmly grounded as an essential scholarly activity within 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 | 0.127 | 0.163 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.033 |
| Scholarly communication | 0.034 | 0.016 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.015 | 0.011 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".