An answer is not the same as understanding

Di Tran’s book asks students to develop human abilities alongside AI skills. Begin with a simple distinction: having an answer on your screen is not the same as understanding it. You demonstrate learning when you can explain a reason, correct an error, or apply an idea to a new situation. Useful technology can support that work; it cannot make your practice unnecessary.

AI can produce explanations, examples, or possible questions. It can also make mistakes, invent sources, and sound certain when evidence is weak. Foundational knowledge still matters because it helps you notice those problems. Teachers, textbooks, and guided practice remain important. This course treats claims that AI knows everything or guarantees success as rhetoric, not reliable facts.

Choose one modest goal you can observe: explain a percentage calculation, compare two sources, or write a clear request. Try it before asking for help, then try a different example afterward. You can do every activity here without an AI account. Use the worked examples, paper, approved learning materials, and help from an appropriate person.