# Synthetic Sample Mission: Verify Before You Trust

**Purpose:** Demonstrate the complete mission loop without student, patient, course or institutional data.  
**Data class:** `TEACH-DATA-1` only.  
**Context:** Private Educator/Designer Mode → Teaching, Learning Design & Accessibility.  
**Role/hat:** Nurse Educator → synthetic workshop designer.  
**Starting EDENA:** Yellow because the lesson concerns responsible AI and sources; `absolute_stop=false`.  
**External actions:** Off.

## Situation

Create an accessible 30-minute synthetic workshop that helps nursing learners verify AI-generated citations. The artifact is a private draft. No real roster, submission, grade, course shell, patient story, institution policy or secure assessment item is used.

## 1. Assess

Verified inputs:

- AI systems can produce plausible but nonexistent or mismatched citations.
- A learner needs a repeatable method to find the original source, confirm author/title/date, inspect the primary text and compare the AI claim with what the source actually supports.
- Public, rights-verifiable sources and fictional examples are sufficient for this rehearsal.

Owner-provided information:

- Thirty minutes are available.
- The desired tone is encouraging and practical.
- The draft should work in a room or online.

Assumptions requiring review:

- Learners have web access and can open a persistent source identifier.
- The chosen example is accessible on mobile and with assistive technology.

Unknowns:

- Local AI-use policy and required disclosure wording.
- Actual learner technology/access needs.
- Who owns course approval and release.

Decision: proceed only with a generic synthetic draft. Create named review questions for the faculty lead and accessibility contact.

## 2. Diagnose or Define

The opportunity is not “learners trust AI too much.” That would infer motivation. The design problem is: learners need a visible, time-bounded verification routine and practice distinguishing a real source, an unsupported claim and an unresolved citation.

Root contributors considered: false fluency, limited time, unfamiliar databases, inaccessible source formats and ambiguous local AI expectations. No person is ranked, profiled or labeled.

Success for this sandbox is structural: a complete draft with aligned outcome, activity, check for learning, sources, rights notes, accessibility review list and limitations. It is not a learner-outcome or teaching-effectiveness claim.

## 3. Plan

Options:

| Option | Benefit | Burden/risk | Decision |
|---|---|---|---|
| Mini-lecture only | Fast | Little practice; false confidence possible | Reject |
| Guided verification of two fictional AI citations | Visible reasoning; low data risk | Requires rights-verified source examples and accessible links | Select |
| Use real learner submissions | Contextual | Prohibited learner payload and integrity risk | Absolute stop |

Plan:

- 3 minutes: purpose, boundaries and AI disclosure.
- 7 minutes: model the VERIFY routine—View record, Establish identity, Read original, Inspect claim, Flag uncertainty, Yield to current policy/human authority.
- 12 minutes: pairs examine two fictional AI outputs against public sources.
- 5 minutes: synthetic check for learning using “supported / qualified / contradicted / unresolved.”
- 3 minutes: reflection and human next step.

Safeguards: public or synthetic inputs only; no AI detector; no grading; no external send; captions/transcript; keyboard route; alt text; non-color status; plain-language printable fallback; source/version/rights record; owner review.

## 4. Implement

Create local drafts only:

1. one-page facilitator guide;
2. accessible learner checklist;
3. two fictional AI citation examples;
4. source/provenance cards;
5. synthetic check-for-learning key;
6. accessibility and Human Teaching anti-slop checklist;
7. release questions for the responsible faculty/accessibility humans.

Lifecycle status remains `Draft Artifact`. “Approved Plan” may be selected only after a named human reviews exact scope/content. Any real course upload, teaching, learner contact or distribution is outside TEACH. If it occurs, the app may store only a minimized verified external reference.

## 5. Evaluate

Before real use, evaluate the draft against:

- complete alignment between outcome, activity and check for learning;
- citation examples verified against primary source content;
- source version, applicability, rights and attribution;
- keyboard, screen-reader, captions/transcript, contrast, 200% zoom/reflow, mobile, print and reduced-motion checks;
- workload within 30 minutes;
- no learner/patient/person payload or inference;
- clear AI contribution and educator authorship review;
- no unsupported claim of accessibility compliance, learner improvement, validity, fairness or institutional approval.

Synthetic evaluation result: **Partial / Awaiting human review**. The draft structure is complete; local policy, accessibility testing and release authority are unresolved. Feed those gaps into the next Assess stage. Do not mark the mission Passed or Completed Action.

## What this demonstrates

The sample exercises all five stages, reversible iteration, EDENA/TEACH gates, source and rights discipline, accessibility, a prohibited-path stop, artifact truth and an external-only execution boundary. It earns no badge, credential or authority because it is synthetic starter activity.
