Multiple Layers: Education Faculty Reflecting on Design-Based Research focused on Curricular Integration
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
What insights emerge through researcher reflections on a Design-Based Research (DBR) curricular integration project that contribute to the professional learning of education faculty/ researchers? To answer this question, two researchers captured their debriefing discussions and reflections after monthly meetings with participating teachers. The meetings familiarized the teachers with DBR methods and enhanced teachers’ understanding of integrating literacy and science instruction. Data were open coded, collapsed into sub-categories and interpretations were then clustered into three themes. The first theme is our acknowledgement of the layers that needed to be peeled back to understand teacher participants’ planning and assessment. The second theme is the realization that the teacher participants were novices with respect to understanding and practicing curricular integration. The final theme honors the value of DBR as a research and professional learning method. Findings are discussed in light of the scant literature that describes the experience of DBR educational researchers.
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.
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 | 0.059 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it