Claims

Perceived AI competence is best modeled as a latent factor over four dimensions after removing PF and AT

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · newest study 2025 · 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? A single-factor CFA over subscale means fits well only after removing the Professionalization (PF) and Attitude (AT) dimensions, meeting CFI, TLI and RMSEA criteria. → Delcker 2025

Evidence

Delcker 2025

Delcker, J., Heil, J., & Ifenthaler, D. (2025). Evidence-based development of an instrument for the assessment of teachers' self-perceptions of their artificial intelligence competence. Education Tech Research Dev. https://doi.org/10.1007/s11423-024-10418-1

q2 · i? · associational · r2

A single-factor CFA on the means of the six subscales, based on the survey of vocational school teachers. The one-factor model with all six subscales fit poorly (RMSEA = .269); removing PF and then AT yielded the final well-fitting model (χ2 = 3.373, DF = 2, RMSEA = .038, CFI = .998, TLI = .995).

"The final model meets the criteria of a good fit concerning the CFI and the TLI, as well as the RMSEA (see Fig. 2)."

Discussion

Page metadata
Field Value
type claim
id single-factor-model-without-pf-and-at
title Perceived AI competence is best modeled as a latent factor over four dimensions after removing PF and AT
description Perceived AI competence is best modeled as a latent factor over four dimensions after removing PF and AT
status review
evidence_strength moderate
newest_evidence 2025
generated by process:wiki-ingest on 2026-10-28
trust unverified — no one has confirmed this page's content
sources 1 — delcker-2025

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