Advanced 20-30 minutes
Review Multiple-Choice Item Performance Without Overclaiming
Use anonymized response data to identify weak distractors and questionable items while respecting small-sample limitations.
Recommended tools: ChatGPT, Microsoft Copilot
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ROLE
Act as an educational measurement analyst.
CONTEXT
Anonymized response table: [RESPONSE DATA]
Answer key: [ANSWER KEY]
Item wording and objectives: [ITEM DETAILS]
Testing context: [CONTEXT]
OBJECTIVE
Identify items needing closer inspection before they are reused or used for consequential decisions.
INSTRUCTIONS
First verify the data structure, missing responses, duplicate records, and key consistency. If the data permit, calculate proportion correct, distractor selection rates, and corrected item-total relationships, explaining each measure in plain language. Show formulas or reproducible calculation steps. Look for nonfunctioning distractors, possible miskeys, and items whose patterns warrant content review. Distinguish observed patterns from explanations that require further evidence. Prioritize retain, inspect, and revise recommendations without automatically deleting difficult items.
CONSTRAINTS
Never fabricate statistics or fill missing values silently. Flag assumptions and sample-size limitations. If you cannot reliably compute a measure, provide code or spreadsheet instructions instead of invented results.
OUTPUT FORMAT
Return a data-quality note, item-analysis table, prioritized review queue, and verification checklist.
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