Understanding Design Research–Practice Partnerships in Context and Time: Why Learning Sciences Scholars Should Learn From Cultural-Historical Activity Theory Approaches to Design-Based Research
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
Several points of contrast are highlighted between design-based research (DBR) as often practiced within the learning sciences and design partnerships inspired by cultural-historical activity theory (CHAT). It is argued that learning scientists can improve their work by learning from CHAT-inspired DBR in 4 particular ways: (a) by recognizing the oversimplification involved in the notion that classroom learning environments can be engineered; (b) by embracing open-ended partnerships driven more by long-term social aims than short-term funding opportunities; (c) by dispelling the myth of the heroic designer from our literature; and (d) by carefully examining and publishing about projects and partnerships that prove unsuccessful, or studying how successful projects fade and degrade over time.
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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 | 0.152 | 0.132 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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 it