Claims

The self-report measure supports a refined 13-item, four-factor model with good fit

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · no dated study recorded · 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? CFA of the self-report measure supported a theoretically coherent four-factor structure (Concept, Use, Evaluate, Ethics), with the refined 13-item model showing good fit (CFI = .970; TLI = .961; RMSEA = .054; SRMR = 0.04). → sr-cfa

Evidence

sr-cfa

Shan Zhang, Ruiwei Xiao, Anthony F. Botelho, Guanze Liao, Thomas K. F. Chiu, John Stamper, and Kenneth R. Koedinger. 2026. How to Assess AI Literacy: Misalignment Between Self-Reported and Objective-Based Measures. In LAK26: 16th International Learning Analytics and Knowledge Conference (LAK 2026). ACM, New York, NY, USA. https://doi.org/10.1145/3785022.3785088

q2 · i? · associational · r2

CFA of the 13-item self-report model in the full sample (N = 288) demonstrated "good fit in the full sample" with the printed indices. Standardized loadings ranged from .62 to .83; overall Cronbach's alpha was 0.889; three items with loadings below .50 were removed to improve fit.

"This optimized model demonstrated good fit in the full sample (N= 288; 𝜒 2(59)= 109.29,𝑝<. 001; 𝜒 2/𝑑𝑓= 1.85; CFI = .970; TLI = .961; RMSEA = .054; SRMR = 0.04)"

Discussion

Page metadata
Field Value
type claim
id sr-measure-four-factor-cfa
title The self-report measure supports a refined 13-item, four-factor model with good fit
description The self-report measure supports a refined 13-item, four-factor model with good fit
status review
evidence_strength moderate
generated by process:wiki-ingest on 2026-10-10
trust unverified — no one has confirmed this page's content
sources 1 — sr-cfa

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