Faculty Development

Item Analysis for Faculty: Reading Your Exam Stats

About this module

Difficulty, discrimination, distractor analysis, reliability — what your exam statistics actually mean, and what to do about flawed items. Pairs with the SI Med School exam analytics dashboard.

Related LCME elements

Every module states its LCME elements explicitly. Tags link to the SILME standards reference (March 2026 edition); element numbers and titles below are quoted from that data.

Element 9.4 Element 8.4 Element 4.5

Learning objectives

By the end of this module, participants will be able to:

• Interpret p-values and discrimination indices
• Read a distractor analysis
• Decide when an item needs faculty review

Module outline

1. Why item stats matter for fairness
2. Difficulty (p-value): too easy, too hard, just right
3. Discrimination: does the item separate strong from weak students?
4. Distractor analysis: what wrong answers tell you
5. Negative discrimination: flag for review, never auto-delete
6. Hands-on: read a sample item-analysis report

Discussion prompts

• What is your current process for reviewing flagged items?
• Who owns item quality at your school?

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