The 28 GenAI literacy criteria function coherently as indicators of a single underlying construct in a Rasch partial credit analysis¶

Claim · All claims
Evidence · 1 study · associational r1 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person · recheck by 2029: tool and model accuracy changes quickly

Subclaims¶

q2 i? All 28 criteria thresholds showed weighted MNSQ fit values within the recommended 0.75–1.33 bounds, indicating a shared latent GenAI competency domain. → Oliveira 2026

Evidence¶

Oliveira 2026¶

Oliveira, E., English, N., Ryan, T., Misiejuk, K., dal Ponte, C., López-Pernas, S., & Saqr, M. (2026). The GenAI Skill Bypass: Mapping Divergent Pathways of University Students and Staff AI Literacy. Preprint. https://arxiv.org/abs/2607.05411 doi:10.48550/arxiv.2607.05411

q2 · i? · associational · r1

Rasch partial credit model analysis of the 28-threshold self-assessment responses (n=158) at item level. The authors report that "The weighted Mean Square (MNSQ) values for all items fell within the recommended bounds of 0.75 to 1.33", supporting a common latent dimension.

"The weighted Mean Square (MNSQ) values for all items fell within the recommended bounds of 0.75 to 1.33 (Wright, 1994)."

Discussion¶

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