Claims

A 200-student pilot showed strong content validity across relevance, comprehensiveness, comprehensibility, and face validity

Claim · All claims
Evidence · 1 study · design r3 · q2
Currency · newest study 2024 · not yet checked against its sources · not reviewed by a person · recheck by 2027: tool and model accuracy changes quickly

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? Pilot ratings on six content-validity questions were strong across all four assessed aspects. → Yueqiao Jin 2024

Evidence

Yueqiao Jin 2024

Yueqiao Jin, Roberto Martinez-Maldonado, Dragan Gašević and Lixiang Yan. (2024). GLAT: The Generative AI Literacy Assessment Test. https://arxiv.org/abs/2411.00283 doi:10.48550/arxiv.2411.00283

q2 · i? · design · r3

Pilot study with 200 higher education students rated six content-validity questions on five-point Likert scales (Cronbach's alpha = 0.81); Table 3 reports means from 4.22 to 4.62 across relevance, comprehensiveness, comprehensibility, and face validity.

"The content validity of the GLAT was assessed in a pilot study with a sample of 200 higher education students through six questions (Table 3) based on the Standards for Educational and Psychological Testing"

Discussion

Page metadata
Field Value
type claim
id glat-content-validity-pilot
title A 200-student pilot showed strong content validity across relevance, comprehensiveness, comprehensibility, and face validity
description A 200-student pilot showed strong content validity across relevance, comprehensiveness, comprehensibility, and face validity
status review
evidence_strength moderate
newest_evidence 2024
recheck_by 2027
generated by process:wiki-ingest on 2026-10-12
trust unverified — no one has confirmed this page's content
sources 1 — yueqiao-jin-2024

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