Ready-to-print. D7 (EAI-CMM score sheet) lives in eai-cmm.md.
Index card, collected at the door.
3 facts from today that survived contact with your skepticism 2 things you want to try with AI this week 1 question you need answered before Wednesday
S5 variant: one word — your redesigned assessment's weakest remaining point.
The log, not the output, is the graded artifact. Minimum 3 rows per workflow.
| Round # | What I asked | What was wrong / weak | What I changed |
|---|---|---|---|
| 1 | |||
| 2 | |||
| 3 |
Closing line: "The most useful thing I changed between round 1 and round 3 was ___________."
| Field | |
|---|---|
| Assessment name / course | |
| Protected learning outcome | |
| AI-audit grade before redesign (P09) |
| Component | Lane 🔴🟡🟢 | Process evidence | Weight |
|---|---|---|---|
Constraints: ≥1 🔴 component protecting the core outcome · 🟡 components name their process evidence · total student workload flat or lower.
| Swap-test | |
|---|---|
| Best exploit found by partner | |
| Patch applied |
≤200 words, individual, ungraded; three volunteers open Session 3.
Scenario: (your group's most-severe card) Decision: what I would do Principle invoked: which of the five, and why it dominates One concrete action: first step, with owner and date Owner: educator / student / institution
≤2 pages. Version block on page one. [LOCAL] = institution-specific body to be named by the owner.
INSTITUTIONAL GUIDELINE FOR ETHICAL AI USE IN TEACHING AND LEARNING
v0.1 · Owner: _______________ · Review date: _______________ (≤12 months)
1. SCOPE & DEFINITIONS
What counts as "AI use"; who and what is covered. Settle definition
fights here — most policy fights are secretly definition fights.
2. PRINCIPLES
Beneficence · Non-maleficence · Autonomy · Justice · Explicability —
localized. Principles survive model churn; rules below get versioned.
3. PERMISSION ARCHITECTURE
The three-lane vocabulary, institutionalized: every course declares
lanes per assessment (🔴 Restricted / 🟡 Permitted with disclosure /
🟢 Required). Default when a syllabus is silent: ____________.
4. DISCLOSURE STANDARD
One canonical AI-use statement format — used by students AND staff.
4b. INSTRUCTOR AI-USE DISCLOSURE (new)
Parallel to student disclosure: instructors disclose their own AI use
in teaching materials, feedback, and grading. Symmetry is credibility;
a double standard (faculty use AI while restricting students) erodes
trust. Mirror-test required: audit your own AI use before drafting
policy.
5. INTEGRITY PROCEDURE
Process evidence primary (version trails, vivas, in-class anchors).
Detector output: at most a screening signal, never sole evidence
(Liang et al., Patterns 2023 — citation stays in the policy).
6. DATA & PRIVACY RULES
PDPA 2010 floor: what student data may enter which class of tool
under what agreement. Institutional accounts over personal ones.
[LOCAL: data-protection officer / relevant committee]
Platform governance: logging and auditing of institutional AI-platform
usage, anonymization protocols, mental-health flag procedures
(per MIT report §3.3.8–9).
7. OWNERSHIP & REVIEW
Named owner · version number · review date · student representation
in review. Monitoring metrics: track AI-use adoption, campus
engagement, student satisfaction, post-graduation feedback sources.
[LOCAL: MQA/MOHE alignment; senate/faculty approval path]
8. ROLES, INFRASTRUCTURE & FUNDING (new — optional)
Designated AI Lead(s) per department or faculty · AI Implementation
Team or committee · AI Fellows or equivalent training capacity ·
Pilot Fund for AI-curricular experiments. Without infrastructure,
the policy is aspirational. (Per MIT report §3.3.1–4.)
v0.2 BACKLOG (from red-team review): ________________________________
AI-USE DISCLOSURE FOR THIS DOCUMENT: drafted with [tool] for [what];
verified and authored by the team named above.
| Horizon | Commitment | Owner/ally | Date |
|---|---|---|---|
| 7 days | Deploy one S4 workflow in a live course (already built — deployment is the only step left) | ||
| 30 days | Run the redesigned assessment (S5) with one real cohort; collect its process evidence | ||
| 90 days | Move Guideline v0.1 one institutional step (department meeting / faculty committee / senate paper) — named ally required |
Kill criterion (mandatory): "I will know this failed if ___________ by ___________." Plans without falsifiability are wishes.
7 min per person/team: 5 present + 2 panel questions. Panel: facilitator + one institutional leader + one rotating peer judge. Score 1–4 per criterion, max 20. Pass ≥12 · Distinction ≥17 · one "Ship It" award.
| Criterion | 4 — Exemplary | 3 — Proficient | 2 — Developing | 1 — Beginning |
|---|---|---|---|---|
| Evidence discipline | Every major claim tied to a named source or course artifact; limitations acknowledged unprompted | Key claims sourced; minor gaps | Mix of evidence and assertion | Assertion-driven |
| Design over policing | Integrity handled entirely through assessment design + process evidence; detector role explicitly bounded | Design-led with minor detector reliance | Policing instincts dominate | Detection/ban-centric |
| Deployability | 7/30/90 steps each have owner, date, and existing artifact; could start tomorrow | Concrete steps, minor dependencies unresolved | Directionally right, operationally vague | Aspirational only |
| Ethical reasoning | Principles applied to hard trade-offs (equity, privacy, learning-vs-performance) with positions taken | Principles correctly applied to clear cases | Principles named, not applied | Absent or decorative |
| Falsifiability | Kill criterion specific, dated, measurable; risks pre-mortemed | Kill criterion present, loosely specified | Vague success talk, no failure condition | No failure condition |
Rank all nine on a severity ladder (Critical / Serious / Manageable / Trivial) — strict ranking, no ties. Tag primary principle + primary owner.