AI Honor Code Case Prep: Documenting Evidence Without Bias

End-of-lesson check

10 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-educators-AI-and-honor-code-case-prep-adults

1. What is the main idea of "AI Honor Code Case Prep: Documenting Evidence Without Bias"?

   1. When AI cheating is suspected, AI can help structure the evidence and conversation — never deciding the case, and never anchoring on detector scores.
   2. Use AI as the final authority for the whole decision
   3. Avoid checking the answer once it sounds polished
   4. Focus only on speed instead of judgment

2. Which concept is most central to "AI Honor Code Case Prep: Documenting Evidence Without Bias"?

   1. AI cheating
   2. honor code
   3. evidence package
   4. due process

3. Which use of AI fits this topic best?

   1. Adjudicate or recommend a finding of academic dishonesty.
   2. Let the AI decide what matters without your review
   3. Structure an evidence package with submission, prior work samples, and timeline.
   4. Use the answer before checking whether it fits the situation

4. Which limitation should you watch for in this topic?

   1. Structure an evidence package with submission, prior work samples, and timeline.
   2. Explain the topic in plain language
   3. Organize a draft for human review
   4. Adjudicate or recommend a finding of academic dishonesty.

5. What should a careful learner remember about "Evidence package and conversation guide"?

   1. Use AI to draft or organize ideas about honor code, then verify before acting.
   2. Skip the context so the tool can guess faster
   3. Treat the output as private even after sharing it online
   4. Use the answer without checking the source

6. You want to use AI after this lesson. What is the safest next step?

   1. Act immediately because the AI answer is written clearly
   2. AI cannot replace teacher judgment, student privacy duties, or school policy.
   3. Hide uncertainty so the final answer looks cleaner
   4. Use private or sensitive details before checking permission

7. How should AI output about honor code be treated?

   1. As proof that no other source is needed
   2. As a replacement for context, consent, or expert review
   3. As a draft or helper output that still needs human judgment and verification
   4. As something that becomes correct when it sounds confident

8. Name one way to verify an AI answer about honor code.

9. Which action would help you apply "AI Honor Code Case Prep: Documenting Evidence Without Bias" responsibly?

   1. Substitute for institutional honor-code procedures and student rights.
   2. Use the tool to avoid thinking through the tradeoff
   3. Keep going even if the output conflicts with a trusted source
   4. Draft a non-accusatory student conversation guide focused on process.

10. Which choice is a bad use of AI for this lesson?

    1. Substitute for institutional honor-code procedures and student rights.
    2. Structure an evidence package with submission, prior work samples, and timeline.
    3. Ask for a plain-language explanation of AI cheating
    4. Compare the answer with a trusted source