What are student inservice teachers talking about in their online Communities of Practice? Investigating student inservice teachers’ experiences in a double-layered CoP
Bibliographic record
Abstract
This qualitative case study is the first phase of a large-scale design-based research project to implement a theoretically derived double-layered CoP model within real-world teacher development practices. The main goal of this first iteration is to evaluate the courses and test and refine the CoP model for future implementations. This paper demonstrates the potential synergies between two major approaches to teacher professional development practices: i) teachers’ CoPs development and ii) online teacher education courses. The double-layered CoP model could provide a practical integration of the two approaches by providing student inservice teachers in an online graduate course with meaningful opportunities to participate in two different teachers’ CoPs: i) an internal course CoP and ii) an external professional CoP. Our analysis of student inservice teachers’ CoPs experiences shows that the two layers of CoPs supported each other iteratively through the course period. Several design considerations for the second iteration of the online course design are also addressed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".