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Interpreting Item Analysis

Reference for language-placement-test-builder · 40 lines

Languages, Linguistics & Translation / Language Teachingv1.0.0Updated OCT 25 20262 references2 scripts

Statistics

StatisticMeaningGood range (placement / proficiency)
Facility (p)Proportion answering correctly0.2-0.9 overall; each level's items easiest for that level and above
Discrimination (D, upper-lower 27%)Do stronger test-takers get it right more often?0.30+ good; 0.20-0.29 acceptable; under 0.20 revise; negative = fault
Distractor share% choosing each wrong optionEach distractor chosen by at least 5%
Distractor directionWeaker group chooses it more than stronger groupAlways
KR-20 / Cronbach's alphaInternal consistency of the whole test0.80+ for placement; 0.90+ for high-stakes

Item statistics need data: under 30 test-takers treat them as indications; under 10 they are noise.

Diagnosing problem items

PatternLikely causeFix
Negative D, one distractor popular with the top groupMiskeyed, or two defensible answersCheck the key; rewrite the option
D near zero, facility near 0.5Item measures something else (trick, culture, reading load)Rewrite or drop
Facility above 0.9Too easy for this populationKeep only if it targets A1 in a test for beginners too
Facility below 0.2, D lowToo hard or ambiguousCheck level and wording
A distractor nobody picksImplausible optionReplace with a real learner error
Higher-level item easier than lower-level itemsItem mis-levelled, or tests a familiar chunkRe-tag or rewrite

Improving reliability

  • More good items (reliability rises with length).
  • Remove items with low or negative discrimination.
  • Spread item difficulty to match the levels you separate.
  • Clear instructions and examples; avoid speededness unless intended.

Workflow

  1. Pilot the test with 30+ learners across the levels (existing classes are ideal).
  2. python scripts/item_analysis.py responses.csv.
  3. Fix or drop IA001 and IA002 items; replace non-working distractors.
  4. Re-pilot changed items or run them as unscored trial items in live tests.
  5. Recalculate cut scores if items changed.
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