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Module 8: AI for Learning and Everyday Work

Learn to choose useful AI assistance, ask for hints, inspect claims and retain control of actions. No programming, live AI service, paid subscription or API key is required. The core route uses clearly labeled authored response fixtures. Start after basic reading/arithmetic readiness; use Modules 4–5 for source evaluation and clear questions. A live account is an optional comparison, not a gate.

Outcomes​

  • Distinguish a model's response from inspected evidence and completed tool actions.
  • Write a bounded task with checkable success criteria.
  • Use an attempt–hint–revision–independent-transfer cycle.
  • Audit numerical and source claims, minimize private data and reject unauthorized actions.
  • Keep an honest assistance record, including an offline-fixture route.

Concept and practice route​

A Practical AI Model​

Learning With Assistance​

Human Control​

After each cluster, complete its matching practice. Then use the guided lab, worked examples, exercises, case studies and mistake clinic. Attempt the independent assessment before the calibration.

Workload and evidence​

Lessons/selective sources 2–3 hours; three cluster practices 1–2; candidate-audit lab 2–3; assessment and one repair 1. Total 6–9 focused hours. No separate waiting period is imposed: put the later independent attempt into an already planned study session. Record active work once. Programming-based evaluation belongs to Semester 00.

Completion​

Each of the three rubric dimensions must reach 2/2 on observable evidence. A high average cannot compensate for a missing practical or independent check. Repair with a fresh variant. See Launchpad integration for evidence reuse and sequencing.

Full-book reading is not required. Use reading guidance, reference and resources selectively. These are authored lessons awaiting independent review and learner pilots; site checks do not establish educational effectiveness.