trained to support it. That framing sets up a live legal question many districts have not yet resolved: when a student uses an AI tool as a documented accommodation, a classroom-wide ban on AI use can create real tension with that student's rights under Section 504 and the ADA. Districts need a clear answer before a dispute forces one. FROM ETHICS TO EXECUTION: THE PBNJ FRAMEWORK Ethical grounding answers whether and when to use AI. It does not answer the separate question of how to get an AI tool to produce something actually useful for a specific student. That second question is the subject of research Zaugg co-authored with a team of educator-researchers at the University of Toronto. The study, published in 2025 in the journal AI and led by Faith, Zaugg, Stolys, Szabo, Haghi, Baldis, and Olmedo, spent fourteen weeks examining how pre-service teachers used AI for differentiated lesson planning. Its central finding runs against the intuition many teachers bring to AI: writing one long, highly detailed prompt and expecting a finished, usable lesson back does not work well. Even thorough single prompts tended to produce material teachers described as impersonal and, in the researchers' words, alien. What worked instead was iterative back-and-forth dialogue with the AI tool, an approach the re- searchers describe as jamming, in which a teacher builds a re- sult gradually, adds detail in stages, and keeps critical judgment engaged throughout the exchange rather than accepting a first draft wholesale. The study also found that prompting AI to act as a critical friend, explicitly asking it to challenge assumptions and surface blind spots, helped teachers notice gaps in their own planning, particularly for students with diverse needs. Underly- ing it all was a finding the research team returns to repeated- ly: teachers perform a kind of contextual alchemy, drawing on knowledge of an individual child, the physical classroom, timing, and relationships that no AI system can replicate. That research carries its own name: PBNJ, short for Persona, Break Glass, Name Plan, Jam. Rather than a separate teaching shorthand layered on top of the study, PBNJ is the four-step workflow the research itself produced, and any teacher can ap- ply it in under two minutes.
Letter
What It Prompts the Teacher to Do
Assign the AI a specific role suited to the task, such as an ex- perienced special education teacher creating differentiated materials. Start with the simple, direct version of the request, the basic ask before any refinement.
P - Persona
B - Break Glass
N - Name Plan Name the plan for the output: what it should cover, what format it should take, and what the student's spe- cific needs are.
Iterate through back-and-forth dialogue, treating the AI as a critical friend and refining the result gradually rather than accepting the first draft.
J - Jam
Table 2: PBNJ Framework The PBNJ prompting framework, from Faith, Zaugg, Stolys, Szabo, Haghi, Baldis, & Olmedo (2025), AI, 6(12), 310.
diately. The AI system is not smarter in the second example. The prompt is. MATCHING TOOLS TO STUDENT NEED Zaugg maintains a continuously updated, publicly available spreadsheet cataloging AI tools by student need, organized into more than twenty tabs and rated for privacy and compliance, us- ing a color code of green for compliant, yellow for use with cau- tion, and red for tools that do not meet standards. The resource reflects her broader teaching philosophy: organize tools around what a student needs rather than which AI product is trending. The available tools fall into four practical categories. For reading and text access, tools such as Diffit can instantly adapt a pasted article or text into multiple reading levels with vo- cabulary support, while general-purpose tools like ChatGPT or Claude can generate leveled passages from scratch when given a specific Lexile level, grade, and topic. Education-specific plat- forms such as MagicSchool AI include special-education-specific generators for goals and accommodations, and interactive tools such as Curipod build in differentiation for inclusive, whole-class lessons. For writing, IEP planning, and executive function sup- port, general-purpose AI tools handle sentence starters, graphic organizers, and rubric adaptation, while a free tool called Goblin Tools, built by a neurodivergent developer, breaks a complex as- signment into step-by-step chunks and has become a particular favorite among teachers for its intuitive grasp of executive func- tion challenges. Teachers generally do not need a different specialized tool for every task. A general-purpose AI assistant paired with the PBNJ framework can handle roughly 80 percent of what a special ed- ucation teacher needs day to day. The specialized, purpose-built tools are useful additions for specific recurring workflows, not a replacement for learning to prompt well.
(See Table 2: PBNJ Framework)
The framework makes a clear difference. A vague prompt asking simply for a reading worksheet about animals produc- es generic, grade-level material a teacher then spends twenty minutes editing to fit actual student needs. A PBNJ-structured prompt that assigns the AI a persona, opens with the basic ask, names a clear plan for a 150-word passage about ocean animals at a second-grade reading level with a defined Lexile score, three comprehension questions of specified types, and a five- word vocabulary list, and then jams with the AI to refine the result, produces a passage a teacher can print and use imme-
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