Claims

Item discrimination screening removed eight items using a critical-ratio criterion above 3

Claim · All claims
Evidence · 1 study · design r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q2 i? Using the critical ratio for high-score versus low-score group differences (top and bottom 27%), eight items with nonsignificant or CR < 3 differences were removed, leaving 56 items. → Liu Qingqi 2026

Evidence

Liu Qingqi 2026

Liu Qingqi, Miao Wenjiao, Li Jingjing, Lei Yuju. (2026). The Six-Facet Artificial Intelligence Literacy Questionnaire (SFAILQ): Assessing AI Literacy in Adolescents, Young Adults, and Midlife Adults. Behavioral Sciences, 16(7), 1110. https://doi.org/10.3390/bs16071110

q2 · i? · design · r2

Item discrimination analysis in Sample 1 (N = 1217): participants ranked by total score, top 27% versus bottom 27% compared per item; items retained if absolute CR exceeded 3.00. Item 9 had an absolute CR of 9.23 and was retained.

"As a result, we removed a total of eight items (items 6, 7, 8, 16, 29, 30, 34, and 56), leaving a final count of 56 items."

Discussion

Page metadata
Field Value
type claim
id critical-ratio-item-discrimination-screening
title Item discrimination screening removed eight items using a critical-ratio criterion above 3
description Item discrimination screening removed eight items using a critical-ratio criterion above 3
status review
evidence_strength weak
newest_evidence 2026
generated by process:wiki-ingest on 2026-10-12
trust unverified — no one has confirmed this page's content
sources 1 — liu-qingqi-2026

Frontmatter is the page's machine-readable record — see the Schema & Guide.