Exploring Veteran Teachers' Collaborative Action Research Experiences Through a School-University Partnership: "Old Dogs" Try New Tricks
Bibliographic record
Abstract
This article shares insights from the experiences of three high school practitioners and two university faculty who participated in a school-university-based action research program as a voluntary part of the teachers’ professional development. The three high school practitioners conducted action research projects around questions that stemmed from and were relevant to their own teaching practice. As part of the action research program, the practitioners were paired with university faculty to support the research. Building on practitioner inquiry traditions and critical case study methodologies, this study used qualitative methods to explore the experiences of practitioner action research processes. Drawing on in-person meeting notes and reflective memos, four key ideas emerged: Infrastructure, We are all Partners in Education, Engaging Pathway for Experienced Teachers, and Challenges. Insights gained from this inquiry will have implications for professional practices in the areas of school-university partnership, professional development, and action research process.
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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 | 0.033 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.037 | 0.031 |
| Scholarly communication | 0.016 | 0.011 |
| Open science | 0.004 | 0.019 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.003 | 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".