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Final Assessment

AI Tools for Content Creation — Final Assessment

Thirty questions across the orientation and ten modules — including scenario, prompt-critique, output-evaluation, assessment-design, visual/accessibility and responsible-use items. Every question explains why answers are correct or incorrect. Pass mark 80%. Attempt again after focused review if needed.

1. What is the course's core promise about using AI for content?

2. Educational content is best understood as what?

3. Why must a teacher review every AI output?

4. What must you never enter into a public AI tool?

5. Which parts make up a high-quality educational prompt?

6. What is the skilled response to a disappointing AI output?

7. Why ask AI to critique its own output?

8. A worksheet should be designed starting from what?

9. Why verify an AI-generated answer key?

10. What is the rule for slide text?

11. What is the risk of a vivid AI story for teaching?

12. What is the danger of a misleading analogy?

13. When should an image be used in a resource?

14. Why must AI-generated images be reviewed for text and labels?

15. What must every meaningful educational image have?

16. When is a concept map the right visual?

17. Why validate an AI-generated concept map?

18. Why does AI often produce a quiz that doesn't test the outcome?

19. What makes an MCQ distractor diagnostic?

20. What must you verify about an AI model answer?

21. When is an analytic rubric the better choice?

22. What makes a rubric criterion observable?

23. How does biased rubric language disadvantage students?

24. What do the six VERIFY steps stand for?

25. Which parts of AI content should you be most suspicious of?

26. Why must meaning never rest on colour alone?

27. How does localisation differ from translation?

28. What does an audit log provide?

29. What does the capstone content pack require of every included resource?

30. Across the whole course, who is accountable for AI-assisted content?

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