Developing Communities of Praxis: Bridging the theory practice divide in teacher education
Bibliographic record
Abstract
Teacher education in universities is under pressure. In many new education policies there is a renewed focus on teacher quality, and therefore quality initial teacher education. In some countries this renewed focus has led to a resurgence of “alternative approaches” to teacher education such as Teach for America / Australia. One of the most persistent complaints about pre-service teacher education is that educational theory presented in these programs does not relate sufficiently to the real work of teachers. In an attempt to overcome these real or perceived divides, tertiary drama educators at the University of Sydney constructed a professional experience program based on both the community of practice model (Lave and Wenger, 1991) and Frierean notions of praxis (1972). Thecommunity of praxisapproach emphasises the importance of integrating theory and practice to support the development of beginning teachers. This article outlines the development, implementation, and evaluation of this approach, including the reasoning behind its foundation and the theoretical and practical significance of such an approach for teacher-educators.
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 | 0.059 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.015 | 0.041 |
| Scholarly communication | 0.017 | 0.023 |
| Open science | 0.003 | 0.029 |
| Research integrity | 0.005 | 0.007 |
| 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".