Design Future(s) Collective: New Directions for Educational Design Research
Bibliographic record
Abstract
Advancing new directions in design research is crucial, especially as our understanding of learning is confronted by novel semi-autonomous and AI technologies, social phenomena, and global environmental crises.This symposium seeks to advance a vision for the future(s) of educational design research and consider questions that rupture core assumptions about design in the learning sciences.These include who and what design agents are, how sustainability can become core to educational design, and how design processes and responsibilities can shift considering new design purposes and partners.The papers present four contributions to design research, allowing us to explore: (1) Commitments and groundings for design, (2) lifecycle approaches made visible when materials are treated as contributors, (3) the importance of new co-analysis approaches, and (4) the unfinished and unexpected nature of educational design.
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 | 0.090 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.041 |
| Scholarly communication | 0.031 | 0.070 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.011 | 0.015 |
| Insufficient payload (model declined to judge) | 0.020 | 0.003 |
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".