AI Grading and Feedback for Teachers Quiz

Answers and explanations appear as you take the quiz.

1. According to the guide, which AI grading job is safer and more useful?
   • Assigning final report card grades
   • Drafting rubric-based feedback that the teacher reviews
   • Deciding academic misconduct cases
   • Ranking students against each other
2. Which accuracy problem involves the AI praising sentences not in the student's work?
   • Score drift
   • Length bias
   • Invented evidence
   • Rubric overfitting
3. What does the guide say about AI writing detectors?
   • They are unreliable, and some disproportionately flag non-native English writers
   • They are fully accurate for essays
   • They are required by FERPA
   • They only flag plagiarism from books
4. How does Gradescope's answer-grouping feature work, as described in the guide?
   • It assigns final grades automatically with no teacher input
   • It writes essays for students
   • It detects cheating using webcams
   • It groups similar answers so the teacher grades each group once
5. What automated check catches invented evidence in AI feedback?
   • Counting the words in the feedback
   • Confirming that every quoted passage actually appears in the submission
   • Running a spell-checker on the rubric
   • Checking the file size
6. What is calibration in the context of adopting an AI grading tool?
   • Adjusting the screen brightness
   • Letting students grade the AI
   • Scoring papers teachers already graded and comparing results criterion by criterion
   • Increasing the randomness setting
7. Why does the guide say AI grading is not objective just because it is automated?
   • It applies patterns learned from data, including that data's biases
   • Computers cannot count
   • It only works in English class
   • It is always stricter than teachers
8. For which type of work does the guide say AI feedback works best?
   • Final exams
   • College admission decisions
   • Suspension hearings
   • Frequent, low-stakes formative feedback