The 3M National Teaching Fellowship: A High Impact Community of Practice in Higher Education
Bibliographic record
Abstract
The 3M National Teaching Fellowship is a national teaching award program that has recognized over 300 teachers at more than 80 Canadian universities for their teaching excellence and outstanding educational leadership. Despite its rich, 30 plus-year history, its impact has remained largely anecdotal. In this study, we build on Hannah and Lester’s (2009) original, multilevel approach that looks at interactions between the individual, network, and systems levels to explore the impact of the 3M National Teaching Fellowship program on furthering and enriching teaching and learning in higher education. Through the analysis of a large collection of program artefacts corroborated with in-depth interviews with 11 fellows (key informants), we were able to gain a deeper understanding of the ways in which the program has had impact at the individual (micro), departmental (meso), institutional (macro), and national/international (mega) levels. In this article, we outline our scholarly exploration of the program’s influence and explore its role as a high-impact community of practice in higher education.
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.
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 | 0.033 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.009 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.007 |
| 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".