AI Literacy in 15 Minutes a Day: Routines Any Teacher Can Run
You don’t need a new unit to teach AI literacy. Embed six quick routines—each 10–15 minutes—into the lessons you already teach. They build core skills (close reading, reasoning, argument, data sensemaking) while shaping healthy AI habits (verification, bias awareness, attribution).
What you’ll get below: clear goals, step-by-step directions, assessment micro-rubrics, differentiation ideas, and policy-friendly safety notes.
What “AI literacy” means in school (plain language)
AI literacy is not tool trivia. In K–12 it means students can:
Use AI within guardrails (clear prompts, constrained tasks).
Question AI (verify claims, spot gaps and bias).
Explain their process (what they used AI for, and how they checked it).
These are the same academic habits you already value—just made explicit.
Ground rules (so this works in any district)
Standards-first: Each routine targets an ELA/Math/Science/SS move.
Human-in-the-loop: AI is a draft assistant, never the source of truth.
No open web required: Use teacher-curated texts, data, or pre-generated AI samples.
Attribution & transparency: Students state if/where AI helped: Plan / Draft / Edit / Did not use.
Equity: Always provide a non-AI path (sentence frames, exemplars) so access and comfort aren’t barriers.
The 6 Routines (10–15 minutes each)
1) Claim–Evidence–AI (CEA) Quick Check
Great for: ELA, Science, Social Studies (gr. 5–12)
Goal: Strengthen close reading and skepticism by comparing an AI summary to a short source.
Steps:
Give students a short text, chart, or image you’ve selected.
Show a pre-generated 2–3 sentence AI “claim” about it.
Students mark each part: ✅ accurate, ⚠️ missing, ❌ wrong—with line or data references.
They revise one sentence and cite the fix.
Assess (micro-rubric): Accuracy • Text/Data citation • Clarity (1–2 comments max).
Differentiation: Provide a highlight key or sentence stems for corrections.
Safety note: Use only teacher-curated sources; no live searching or personal data.
2) Math Error Safari — AI Edition
Great for: Math (gr. 6–10)
Goal: Build reasoning by diagnosing a flawed “AI step” in a worked example.
Steps:
Provide a multi-step solution with one intentionally wrong step.
Students name the exact error (“unit drift,” “inverse slip,” etc.) and explain why.
They write the corrected step and a second valid strategy.
Assess: Error located • Reason explained • Corrected work shown.
Differentiation: Offer tiered problems or a hint card (diagram, counterexample).
Safety note: No tools needed in class; you supply the flawed step.
3) Bias & Perspective Mini-Audit
Great for: ELA/SS/Science (gr. 6–12)
Goal: Recognize how tone and framing change meaning.
Steps:
Show two short AI drafts responding to the same prompt but with different tones/perspectives.
Students highlight loaded language and identify missing voices.
They write one sentence that improves balance and precision.
Assess: Specific language flagged • Balanced revision produced.
Differentiation: Sentence frames for neutral phrasing; glossary for tone words.
Safety note: Avoid sensitive attributes; keep examples age-appropriate.
4) Prompt Repair Workshop
Great for: Any subject (gr. 5–12)
Goal: Teach structured, transparent prompting and process documentation.
Steps:
Show a vague prompt and its messy output (prepared beforehand).
Students repair the prompt by adding constraints: audience, must-use sources, length, format.
Compare outputs; annotate what improved and why.
Students save a “prompt recipe” card for future tasks.
Assess: Clear constraints • Verifiable sources • Output aligned to success criteria.
Differentiation: Provide a template with slots (context, constraints, criteria).
Safety note: No student identifiers in prompts; cite class texts only.
5) Source Sandwich
Great for: ELA/Science (gr. 6–12)
Goal: Practice synthesis and faithful paraphrase.
Steps:
Provide two short excerpts or a mini data set.
Students pull one fact from each source.
AI is allowed only to write a neutral connecting sentence.
Students label each sentence: [Human] or [AI] and peer-verify that no new facts slipped in.
Assess: Correct labels • Faithful paraphrase • Evidence cited.
Differentiation: Offer stems for the linking sentence; model a sample.
Safety note: Prohibit new claims not present in sources.
6) Reflection & Attribution Minute
Great for: Any subject (gr. 5–12)
Goal: Normalize transparency and metacognition.
Steps:
Students check one: Plan / Draft / Edit / Did not use.
Write one line: “How did I verify?” (page/line, dataset, calculation, peer check).
Assess: Process clearly stated • Verification is concrete.
Differentiation: Word bank for verification methods; icons for speed.
Safety note: No logins or personal data collected.
Weekly rotation (example)
Week 1: CEA Quick Check + Reflection Minute
Week 2: Math Error Safari + Prompt Repair
Week 3: Bias Audit + Source Sandwich
Week 4: Teacher’s Choice—repeat the routine that surfaced the most useful misconceptions
Micro-rubric you can apply to any routine
Score each quickly as Green / Yellow / Red and add one next-step note.
Correctness: Accurate • Partially accurate • Inaccurate
Evidence/Process: Clear citation/verification • Partial • Missing
Clarity: Concise & precise • Wordy/unclear • Needs model
Tip: Scan 6–10 samples mid-class to decide on a 3-minute whole-group reteach or a quick small-group pull.
UDL & differentiation moves (swap-ins, not rewrites)
Provide choice in output (bullet notes, diagram, short paragraph).
Offer scaffolded text levels or a shared class exemplar.
Encourage peer roles (reader/checker; scribe/verifier).
Keep materials light-tech: printed excerpts, teacher-prepared AI samples, or slides.
Policy-friendly language you can paste into a syllabus
“We may use AI as a drafting aid for limited, teacher-approved steps (e.g., outlining, neutral linking sentences). All final work must be verified with class texts, data, or approved sources. Students must include an attribution line indicating if/how AI helped and how they verified the result.”
Implementation checklist
✅Choose 2 routines that fit next week’s lessons.
✅Prepare one short text/data set and one pre-generated AI sample.
✅Print the micro-rubric on exit tickets.
✅Add the syllabus statement and a brief parent note.
✅Plan a 3-minute mid-class scan for formative decisions.
FAQ
Do I need devices?
No. You can run every routine with printed excerpts and pre-generated samples.
What if our district restricts AI tools?
Use only teacher-created examples and the verification steps. The literacy skills (skepticism, sourcing, bias detection) still apply.
How do I grade AI-assisted work?
Grade the learning target (argument/model/summary) and the process (attribution + verification). The green/yellow/red micro-rubric keeps it fast.
