Persona, Break Glass, Name Plan, Jam (PBNJ): A New AI Workflow for Planning and Problem Solving
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
This self-study presents Persona, Break Glass, Name Plan, Jam (PBNJ), a human-centered workflow for using generative AI to support differentiated lesson planning and problem solving. Although differentiated instruction (DI) is widely endorsed, early-career teachers often lack the time and capacity to implement it consistently. Through four iterative cycles of collaborative self-study, seven educator-researchers examined how they used AI for lesson planning, identified key challenges, and refined their approach. When engaged, the PBNJ sequence—set a persona, use a ‘break glass’ starter prompt, name a preliminary plan, and iteratively ‘jam’ with the AI—improved teacher confidence, yielded more feasible lesson plans, and supported professional learning. We discuss implications for problem solving beyond educational contexts and the potential for use with young learners.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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