Teachers’ Engagement with Educational Research: Toward a Conceptual Framework for Locally-Based Interpretive Communities
Bibliographic record
Abstract
In this article, I re-visit the gap between educational research and practice, by reviewing some initiatives that have been taken to bridge the gap. I argue that most of these initiatives do not pay due attention to local contexts of research use. They tend to focus more on the management of researchers’ theoretical knowledge than on the generation of teachers’ pedagogical knowledge. For the development of meaningful pedagogical knowledge, I recommend that teachers be provided with appropriate opportunities to engage directly with educational research. However, I note that such engagement with research is not without challenges and constraints. Borrowing from Denzin and Lincoln (2005), I discuss three challenges—of representation, legitimation, and praxis—to teachers’ engagement with research. To overcome these challenges, I propose that teachers work as locally-based interpretive communities, in which they negotiate a communicative validity of research findings through dialogue with one another.
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 | 0.103 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.014 | 0.006 |
| Science and technology studies | 0.020 | 0.125 |
| Scholarly communication | 0.031 | 0.047 |
| Open science | 0.009 | 0.031 |
| Research integrity | 0.010 | 0.010 |
| 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".