TFIS · EAI-CMM — Interactive Assessment

EAI-CMM — Ethical AI Educator Capability Maturity Model

Adapted from the SSA-CMM maturity-ladder pattern. Complete your baseline (S1) now; retake (S7) after the course to measure growth.

Session Load Scores are temporary until saved.

Scale: 0 Never/No · 1 Rarely · 2 Sometimes · 3 Usually · 4 Consistently/Institutionalized. Max 80.

LITERACY — Do I understand what this technology is and isn't?

#	Statement	1	2	3	4
1	I can explain in plain language how a large language model generates output (next-token prediction over training data — not database retrieval).	1	2	3	4
2	I can name and give discipline-specific examples of at least three failure modes: hallucination, bias, sycophancy/over-agreement.	1	2	3	4
3	I have personally used at least two different AI systems on real work tasks in the past month.	1	2	3	4
4	I can articulate which tasks in my discipline current AI does well, poorly, and unevenly — and I update this map as models change.	1	2	3	4

Statement

I can explain in plain language how a large language model generates output (next-token prediction over training data — not database retrieval).

I can name and give discipline-specific examples of at least three failure modes: hallucination, bias, sycophancy/over-agreement.

I have personally used at least two different AI systems on real work tasks in the past month.

I can articulate which tasks in my discipline current AI does well, poorly, and unevenly — and I update this map as models change.

PEDAGOGY — Do my teaching and assessment designs account for AI?

#	Statement	1	2	3	4
5	I have redesigned at least one assessment specifically in response to AI capability.	1	2	3	4
6	For each assessment I set, I can state the learning outcome it protects and why AI use would or wouldn't compromise it.	1	2	3	4
7	I use AI to augment my own teaching preparation (rubrics, examples, feedback drafts, differentiation) with a verification step.	1	2	3	4
8	I deliberately design assessments in tiers: AI-restricted, AI-permitted, AI-required.	1	2	3	4

Statement

I have redesigned at least one assessment specifically in response to AI capability.

For each assessment I set, I can state the learning outcome it protects and why AI use would or wouldn't compromise it.

I use AI to augment my own teaching preparation (rubrics, examples, feedback drafts, differentiation) with a verification step.

I deliberately design assessments in tiers: AI-restricted, AI-permitted, AI-required.

INTEGRITY — Is my integrity regime built on design or on policing?

#	Statement	1	2	3	4
9	My course documents state an explicit, per-assessment AI-use policy that students can act on without guessing.	1	2	3	4
10	My integrity evidence comes from process (drafts, version history, vivas, in-class components) rather than from detector scores.	1	2	3	4
11	I require disclosure/citation of AI assistance — and I model it by disclosing my own.	1	2	3	4
12	I can conduct a fair, non-accusatory conversation with a student about suspected misuse without a detector report as my only evidence.	1	2	3	4

Statement

My course documents state an explicit, per-assessment AI-use policy that students can act on without guessing.

My integrity evidence comes from process (drafts, version history, vivas, in-class components) rather than from detector scores.

I require disclosure/citation of AI assistance — and I model it by disclosing my own.

I can conduct a fair, non-accusatory conversation with a student about suspected misuse without a detector report as my only evidence.

DISCERNMENT — Can I evaluate AI output, and teach students to?

#	Statement	1	2	3	4
13	I verify AI factual claims and references against primary sources before they reach students or grading decisions.	1	2	3	4
14	I can quickly spot AI-typical failure signatures: fabricated citations, confident wrongness, plausible-but-hollow structure.	1	2	3	4
15	I actively check AI output for bias that would affect my students (language background, gender, culture) before use.	1	2	3	4
16	I calibrate trust to stakes: loose for brainstorming, strict for anything touching grades, references, or student records.	1	2	3	4

Statement

I verify AI factual claims and references against primary sources before they reach students or grading decisions.

I can quickly spot AI-typical failure signatures: fabricated citations, confident wrongness, plausible-but-hollow structure.

I actively check AI output for bias that would affect my students (language background, gender, culture) before use.

I calibrate trust to stakes: loose for brainstorming, strict for anything touching grades, references, or student records.

GOVERNANCE — Do I operate within (and contribute to) explicit rules?

#	Statement	1	2	3	4
17	I know which student data may and may not be entered into external AI tools, and I comply (including PDPA obligations).	1	2	3	4
18	I know my institution's current AI guidance — or I know it doesn't exist, and I document my own interim rules in writing.	1	2	3	4
19	Where AI materially shapes something students receive (feedback, materials, grades), I keep a record of how it was used.	1	2	3	4
20	I actively contribute to AI policy conversations at department, faculty, or senate level.	1	2	3	4

Statement

I know which student data may and may not be entered into external AI tools, and I comply (including PDPA obligations).

I know my institution's current AI guidance — or I know it doesn't exist, and I document my own interim rules in writing.

Where AI materially shapes something students receive (feedback, materials, grades), I keep a record of how it was used.

I actively contribute to AI policy conversations at department, faculty, or senate level.

Score sheet

Pillar	Subtotal /16	Delta (S7 vs S1)
Literacy	—	—
Pedagogy	—	—
Integrity	—	—
Discernment	—	—
Governance	—	—
Total /80	—	—
Band / Level	—
Biggest-moving pillar	—
Stubbornest item	—

Pillar

Subtotal /16

Delta (S7 vs S1)

Literacy

—

Pedagogy

—

Integrity

—

Discernment

—

Governance

—

Total /80

—

Band / Level

—

Biggest-moving pillar

—

Stubbornest item

—

Levels

Level	Name	Band	Signature
L0	Unaware	0–13	AI is rumor. Assessments unchanged since pre-2023. Integrity = hoping.
L1	Aware	14–27	Has opinions, not reps. Talks about AI more than uses it. Policy = "don't."
L2	Experimenting	28–41	Personal use begun; unverified. Syllabus mentions AI vaguely. Detector-reliant.
L3	Integrating	42–55	Redesigned assessments; tiered policies; verifies output; discloses own use.
L4	Governing	56–69	Systematized: documented workflows, process-based integrity, mentors peers.
L5	Stewarding	70–80	Shapes institutional policy; builds capability in others; instrument-rated practice.

Level

Name

Band

Signature

Unaware

0–13

AI is rumor. Assessments unchanged since pre-2023. Integrity = hoping.

Aware

14–27

Has opinions, not reps. Talks about AI more than uses it. Policy = "don't."

Experimenting

28–41

Personal use begun; unverified. Syllabus mentions AI vaguely. Detector-reliant.

Integrating

42–55

Redesigned assessments; tiered policies; verifies output; discloses own use.

Governing

56–69

Systematized: documented workflows, process-based integrity, mentors peers.

Stewarding

70–80

Shapes institutional policy; builds capability in others; instrument-rated practice.

Route to the next level

▶ L0→L1: One AI assistant, 20 min daily, two weeks, real tasks. Read one primary source (start: 2026 AI Index education chapter). No opinions until reps.

▶ L1→L2: Run your three most important assessments through an AI yourself. Score the outputs — you now know your exposure. Draft one per-assessment AI rule.

▶ L2→L3: Redesign your most AI-vulnerable assessment with the three-lane pattern. Replace detector reliance with two forms of process evidence. Add a disclosure norm — for students and yourself.

▶ L3→L4: Document your workflows so a colleague could run them. Keep verification logs. Take one integrity case through a design-based resolution. Teach one peer.

▶ L4→L5: Put your name on institutional guidance (S7's v0.1 is the vehicle). Run a department workshop. Establish a review cadence — you maintain a living policy product.

#	Statement	1	2	3	4
i1	A current, findable, institution-level AI-in-education policy exists.	1	2	3	4
i2	Policy distinguishes contexts (coursework / exams / research / admin), not one blanket rule.	1	2	3	4
i3	A student-facing plain-language version exists that students actually read.	1	2	3	4
i4	Assessment-design guidance exists (not just conduct rules).	1	2	3	4
i5	Integrity procedures specify what counts as evidence — and what doesn't (detector-score status explicit).	1	2	3	4
i6	Data rules govern what student information may enter which tools (PDPA-mapped).	1	2	3	4
i7	Staff development on AI is funded and recurring, not a one-off talk.	1	2	3	4
i8	Equity of access is addressed (institutional licenses, not bring-your-own-subscription).	1	2	3	4
i9	A named owner and review cadence exist (the policy has a maintainer).	1	2	3	4
i10	Students had a voice in drafting.	1	2	3	4