Expansive Learning in Inter-Institutional Communities of Practice for Teacher Educators and Policymakers
Bibliographic record
Abstract
The current study deals with participation in inter-institutional Communities of Practice (CoP) ( Wenger, 1998 ) as a form of professional learning for experienced teacher educators who hold leadership positions in their institutions. In these CoPs, collaboration between teacher educators and policymakers resulted in expansive learning, which is the creation of new practical and theoretical knowledge, and a change of practice rather than adoption of knowledge constructed elsewhere. The current study describes three such communities, the expansive learning cycles that each of them triggered, and shared characteristics that may have contributed to these outcomes. The multiple case study methodology was employed. Data sources were interviews with thirteen participants (coordinators, Ministry of Education representatives and additional members from each CoP), and documents (such as meeting minutes and research papers) that were produced in each CoP. The findings show that expansive learning occurred due to a shared vision, reflective and critical dialogue, trusting relationship, and mutual support among participants. Furthermore, the inter-institutional composition of the CoPs, and the influential position of the participants within their respective organizations enabled them to introduce coordinated changes that transformed their practice at the individual, organizational and national levels.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".