# Playbook sample-artifact content (5 pages, authored verbatim)

Each block is the inner HTML for one `<div class="category-block">` rendered right after that category's card. Structure is identical across all five (the Papers prototype was approved). Author verbatim. No dashes in prose.

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## Discussions: Model Artifacts

```html
<h3 class="category-title">Discussions: Model Artifacts</h3>
<p class="body-text" style="margin-bottom:10px;">Share these with students up front as the models (the Criteria component of TILT). Both come from a weekly discussion that asks students to apply a chapter concept to the assigned case.</p>

<p class="subsection-heading">AI-Forward Model: Critique an AI Post</p>
<p class="body-text" style="margin-bottom:6px;">Use this when AI is permitted and you grade the student's judgment about it.</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">The AI post the student critiqued:</b> "Groupthink is when a group agrees too much and makes a bad decision. The Challenger disaster is an example. Teams should talk openly to avoid it."</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">The student's critique:</b> "This is generic and partly wrong. Janis defines groupthink as the suppression of dissent for cohesion, not simply too much agreement. The post names the Challenger but cites no specific pressure. In our case the engineers did raise concerns, so the failure was management overriding dissent, not the absence of disagreement. A stronger reading uses Janis's symptom of self-censorship and quotes the meeting notes on page 3."</p>
<p class="body-text" style="margin-bottom:0;font-size:12.5px;"><b style="color:var(--accent);">Why it earns credit:</b> the student names the exact concept error, corrects it from the assigned definition, and grounds the correction in the specific case.</p>

<p class="subsection-heading" style="margin-top:14px;">AI-Resistant Model: A Cohort-Anchored Post</p>
<p class="body-text" style="margin-bottom:6px;">Use this when the securing move is specificity that a reusable prompt cannot predict.</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">The student's post:</b> "In the Week 4 case the product team shows Janis's illusion of unanimity. The meeting notes record no objection, yet two engineers later said they disagreed (case, p. 3). Building on Maria's point about the deadline, the self-imposed launch date created the incentive to self-censor. The fix is not more meetings but a named devil's advocate, which our reading ties to lower groupthink."</p>
<p class="body-text" style="margin-bottom:0;font-size:12.5px;"><b style="color:var(--accent);">Why it earns credit:</b> the post cites the specific case and page, answers a named peer, and applies a precise concept a generic response could not predict.</p>
```

---

## Quizzes and Exams: Model Artifacts

```html
<h3 class="category-title">Quizzes and Exams: Model Artifacts</h3>
<p class="body-text" style="margin-bottom:10px;">Share these with students up front as the models (the Criteria component of TILT). Both use a first-year contracts topic.</p>

<p class="subsection-heading">AI-Forward Model: Open-AI Verification</p>
<p class="body-text" style="margin-bottom:6px;">Use this when AI is permitted and you grade the student's correction, not recall.</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">Question:</b> An offer says "open for 10 days." On day 3 the offeror sells the item to someone else and says nothing. On day 5 the offeree accepts. Is there a contract?</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">The AI answer the student corrected:</b> "Yes. The offer said 10 days, so it stayed open, and the day-5 acceptance formed a contract."</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">The student's correction:</b> "This is wrong. A promise to hold an offer open is not binding without consideration, so the 10 days did not create an option. Selling to a third party is an indirect revocation once the offeree learns of it (Dickinson v. Dodds). If the offeree knew of the sale before accepting, no contract formed. The AI applied the wrong rule."</p>
<p class="body-text" style="margin-bottom:0;font-size:12.5px;"><b style="color:var(--accent);">Why it earns credit:</b> the student applies the correct doctrine to the facts, names the authority, and states exactly what the AI missed.</p>

<p class="subsection-heading" style="margin-top:14px;">AI-Resistant Model: Recall Item Rebuilt as Application</p>
<p class="body-text" style="margin-bottom:6px;">Use this when the securing move is application items drawn from a randomized pool.</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">Weak, AI-easy recall item:</b> "Define consideration in contract law."</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">Rebuilt application item:</b> "Jordan promises to paint Alex's fence as a favor, for free. Relying on the promise, Alex buys 200 dollars of paint. Jordan backs out. State whether consideration exists and which doctrine, if any, lets Alex recover." Draw each student's version from a pool that varies the parties, the amounts, and the promised act.</p>
<p class="body-text" style="margin-bottom:0;font-size:12.5px;"><b style="color:var(--accent);">Why it earns credit:</b> the student applies the rule to a novel fact pattern and chooses among doctrines, which a lookup does not finish, and randomization means no two students share the item.</p>
```

---

## Projects: Model Artifacts

```html
<h3 class="category-title">Projects: Model Artifacts</h3>
<p class="body-text" style="margin-bottom:10px;">Share these with students up front as the models (the Criteria component of TILT). Both come from a team research project.</p>

<p class="subsection-heading">AI-Forward Model: AI-Use Log Entry</p>
<p class="body-text" style="margin-bottom:6px;">Use this when AI is permitted and you grade the judgment the team applied to it.</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">The entry:</b> "Week 3. We asked an AI tool to draft survey questions for our user research. It produced five. Two were leading, including 'Do you agree the app is easy to use?' We rejected those and kept two after rewording them for neutrality. Our methods reading says leading questions bias responses, so we removed them. The AI drafted, and we decided what to keep."</p>
<p class="body-text" style="margin-bottom:0;font-size:12.5px;"><b style="color:var(--accent);">Why it earns credit:</b> the entry names what AI produced, what the team rejected and why, and ties the decision to a course concept.</p>

<p class="subsection-heading" style="margin-top:14px;">AI-Resistant Model: Milestone and Contribution Record</p>
<p class="body-text" style="margin-bottom:6px;">Use this when the securing move is a verifiable development trail with individual accountability.</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">Milestones:</b> scope proposal (Week 2), midpoint check-in with the client (Week 5), final delivery (Week 8).</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">Contribution statement:</b> "I built the data pipeline and wrote the limitations section. My commits from October 3 to October 20 show the pipeline take shape. My teammate ran the interviews and coded the transcripts."</p>
<p class="body-text" style="margin-bottom:0;font-size:12.5px;"><b style="color:var(--accent);">Why it earns credit:</b> dated milestones and per-member contributions tied to commit history create a record one AI submission cannot fake.</p>
```

---

## Presentations and Oral Assessments: Model Artifacts

```html
<h3 class="category-title">Presentations: Model Artifacts</h3>
<p class="body-text" style="margin-bottom:10px;">Share these with students up front as the models (the Criteria component of TILT). Both come from a recorded recommendation talk.</p>

<p class="subsection-heading">AI-Forward Model: Prep-Use Disclosure</p>
<p class="body-text" style="margin-bottom:6px;">Use this when AI is permitted in preparation and disclosed.</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">The disclosure:</b> "I used an AI tool to outline my talk and to suggest counterarguments. I kept the outline structure but rewrote every slide in my own words. I added the counterargument about cost, which the AI raised and I had not considered, and I answered it with our project's data. I did not use AI during the live question and answer."</p>
<p class="body-text" style="margin-bottom:0;font-size:12.5px;"><b style="color:var(--accent);">Why it earns credit:</b> the student states what AI contributed, what they changed, and where they did not use it, and the disclosure is graded as part of the talk.</p>

<p class="subsection-heading" style="margin-top:14px;">AI-Resistant Model: Targeted Reflection</p>
<p class="body-text" style="margin-bottom:6px;">Use this when the securing move is a reflection tied to specific feedback.</p>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">The reflection:</b> "After peer feedback I changed my central recommendation from adding staff to redesigning the intake form. My peer pointed out that our own data showed the bottleneck was duplicate data entry, not headcount (their comment on slide 6). Making the change meant rewriting my cost section, but it fits the evidence."</p>
<p class="body-text" style="margin-bottom:0;font-size:12.5px;"><b style="color:var(--accent);">Why it earns credit:</b> the student names a specific change, the exact feedback that drove it, and the evidence, which requires engagement a generic reflection lacks.</p>
```

---

## Papers and Written Assignments: Model Artifacts (approved prototype)

```html
<h3 class="category-title">Papers: Model Artifacts</h3>
<p class="body-text" style="margin-bottom:10px;">Share these with students up front as the models (the Criteria component of TILT), so a student who has never produced one can aim at the target. Both come from the same assignment: a short persuasion-analysis paper on an advertisement the student chose.</p>

<p class="subsection-heading">AI-Forward Model: AI-Use Appendix</p>
<p class="body-text" style="margin-bottom:6px;">Use this when AI is permitted and you grade the student's judgment about it.</p>
<table class="considerations-table" style="margin-bottom:8px;">
  <thead><tr><th style="width:28%;">Prompt the student used</th><th>What the AI suggested</th><th style="width:15%;">Decision</th><th style="width:26%;">Why</th></tr></thead>
  <tbody>
    <tr><td>"List Cialdini's six principles of persuasion with a one-line definition."</td><td>An accurate list of the six principles.</td><td>Kept; rewrote in own words</td><td>Correct but generic. I needed my own framing to apply it to my ad.</td></tr>
    <tr><td>"Analyze this Nike ad using the scarcity principle."</td><td>Claimed the ad used scarcity (a "limited-edition drop").</td><td>Rejected</td><td>My ad shows no scarcity cue. The AI invented one. I analyzed social proof instead, which the athlete endorsements actually show.</td></tr>
    <tr><td>"Draft a thesis about emotional appeal in advertising."</td><td>A broad thesis about ads and emotion.</td><td>Changed</td><td>Too general. I narrowed it to my ad and the reciprocity principle it relies on.</td></tr>
  </tbody>
</table>
<p class="body-text" style="margin-bottom:4px;font-size:12.5px;"><b style="color:var(--accent);">Why it earns credit:</b> the student names each prompt, rejects a fabricated claim with a reason from the reading, and ties every decision to the specific ad. That judgment is what the appendix grades.</p>

<p class="subsection-heading" style="margin-top:14px;">AI-Resistant Model: Process Trail</p>
<p class="body-text" style="margin-bottom:6px;">Use this when the securing move is documented authorship and the task needs no AI.</p>
<table class="considerations-table" style="margin-bottom:8px;">
  <thead><tr><th style="width:24%;">Stage</th><th>What the student submitted</th></tr></thead>
  <tbody>
    <tr><td>Proposal (Week 1)</td><td>"I will analyze the reciprocity principle in a Dove Real Beauty ad from my own Instagram feed."</td></tr>
    <tr><td>Annotated draft (Week 3)</td><td>Draft carrying the instructor note "tie the reciprocity claim to a specific frame," with the student's two marked changes in response.</td></tr>
    <tr><td>Final and revision note (Week 5)</td><td>"I changed my thesis after peer feedback, from a general emotional appeal to reciprocity, because a peer showed the ad offers self-worth before it asks for brand loyalty."</td></tr>
  </tbody>
</table>
<p class="body-text" style="margin-bottom:0;font-size:12.5px;"><b style="color:var(--accent);">Why it earns credit:</b> the dated development record, the self-chosen ad, and the documented thesis change are authorship evidence a generic AI submission cannot produce.</p>
```
