Claims

Exploratory factor analysis supports a five-factor GAA-LS structure explaining 67.82% of variance

Claim · All claims
Evidence · 1 study · design r3 · q3
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.

q3 i? In Study 1 (n = 486), exploratory factor analysis of the 18 retained items supported a five-factor solution corresponding to the hypothesized dimensions, explaining 67.82% of the total variance. → Nie J 2026

Evidence

Nie J 2026

Nie J, Zhang Z, Lu X, Zhang Y and Zhang M (2026) Development and validation of the generative AI assessment literacy scale for higher education students: psychometric evidence and associations with feedback engagement and academic integrity. Front. Educ. 11:1934632. https://doi.org/10.3389/feduc.2026.1934632

q3 · i? · design · r3

Study 1 exploratory factor analysis with 486 students using principal axis factoring with oblimin rotation. Sampling adequacy was high: "The KMO value was .931", and Bartlett's test was significant, χ2(153) = 4,862.17, p < .001. Factor loadings ranged from .63 to .84.

"Exploratory factor analysis supported a five-factor solution corresponding to the hypothesized dimensions. The final 18 items explained 67.82% of the total variance."

Discussion

Page metadata
Field Value
type claim
id gaa-ls-five-factor-efa-structure
title Exploratory factor analysis supports a five-factor GAA-LS structure explaining 67.82% of variance
description Exploratory factor analysis supports a five-factor GAA-LS structure explaining 67.82% of variance
status review
evidence_strength moderate
newest_evidence 2026
generated by process:wiki-ingest on 2026-10-10
trust unverified — no one has confirmed this page's content
sources 1 — nie-j-2026

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