Canadian Journal of Education Toward a Praxeology of Teaching
Bibliographic record
Abstract
Despite much research on teaching, (preservice) teachers in the field still experience a considerable gap between theory and the prescriptions for teaching and their own day-today practice. We conceptualize this gap in terms of the difference between descriptions of practice and practice itself. Descriptions are problematic because they (a) can not include the tacit understanding (background, practical sense) against which specific acts of teaching become meaningful and (b) are inherently out of synchrony with unfolding practice. Using a number of exemplary vignettes from an extensive video database documenting our own and our collaborators ’ teaching, we illustrate how Bourdieu’s notion of habitus accounts for the generation of appropriate actions in situations where there is no “time out ” and how co-teaching can support (preservice) teachers’ development of this habitus. Toward a praxeology of teaching 2 It was hard, for I remember at the university you’re hearing all these ways and methods and these idealistic ways. When you actually get out there it’s different, putting it into actions... I don’t know what anybody else did, but I was sort of
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 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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.013 | 0.017 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.063 | 0.006 |
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".