GenAI-RTS subscale reliability is acceptable to good (ω = .75–.88)¶

Claim · All claims
Evidence · 1 study · design r2 · 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? Subscale reliability of the GenAI-RTS, assessed with McDonald's omega, falls in the acceptable-to-good range. → Hossain 2026

Evidence¶

Hossain 2026¶

Hossain, S., & Nawmi, T. A. (2026). Measuring How Students Rely on Generative AI in Academic Writing: Development and Multi-Source Validation of the Generative AI Reliance Types Scale (GenAI-RTS). https://arxiv.org/abs/2607.14301 doi:10.48550/arxiv.2607.14301

q2 · i? · design · r2

Internal consistency was assessed with Cronbach's alpha and McDonald's omega per subscale in the validation sample of 382 undergraduates. The article reports "ω = .75–.88" across subscales; sensitivity analyses omitting 28 longstring-flagged cases shifted reliabilities by at most −.033.

"Subscale reliability was acceptable to good (ω = .75–.88), and scalar measurement invariance held across gender, first-generation status, and STEM/non-STEM majors"

Discussion¶

Related Claims¶

• Rasch analysis indicates a five-point response format would improve the GenAI-RTS's category functioning — related
• The 28 GenAI literacy criteria function coherently as indicators of a single underlying construct in a Rasch partial credit analysis — related
• Scalar measurement invariance of the GenAI-RTS holds across gender, first-generation status, and STEM/non-STEM majors — related