Personal innovativeness, technology anxiety, and growth mindset in technology each significantly predict AI literacy after external resources and digital competence are controlled, adding 6% of variance¶

Claim · All claims
Evidence · 1 study · associational r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? The three psychological variables significantly improved prediction of AI literacy beyond external resources and digital competence (H3 supported; total R2 = 0.39). → Chow Tak Sang 2026

Evidence¶

Chow Tak Sang 2026¶

Chow Tak Sang, To Ken, Lam Bess Yin Hung, Lau Kung Wong. (2026). A Multidimensional Analysis of AI Literacy Determinants: External Resources, Digital Skills, and Psychological Profile Among University Students. Behavioral Sciences. https://doi.org/10.3390/bs16081448

q2 · i? · associational · r2

Final step of the hierarchical regression added personal innovativeness, technology anxiety, and growth mindset in technology. The article reports "The R-square value of model 4 is 0.39 in contrast with 0.32 in model 3" and states all three psychological variables significantly predicted AI literacy; multicollinearity checks showed no concern.

"The model shows significant improvement over the third model ∆F (3, 294) = 10.93, p < 0.001. The R-square value of model 4 is 0.39 in contrast with 0.32 in model 3"

Discussion¶

Learner Variables¶

• Mindset — predictor: learners who differ on it differ in outcomes

Related Claims¶

• The meta-analytic correlation between growth mind-set and academic achievement is weak (r = .10) — the general claim this finding bears on, with the studies behind it
• Prior digital competence significantly predicts AI literacy after external resources are controlled, adding 3% of variance — related
• Technology anxiety's positive association with AI literacy is confined to critical evaluation and ethical competence and absent from the three performance-oriented subdimensions — related
• Predictors operate selectively across AI literacy subdimensions: digital competence fails to predict technical proficiency or communication proficiency, and perceived resources predict only communication proficiency and creative application — related
• Technology anxiety is a positive predictor of AI literacy once other determinants are controlled, despite a negative zero-order correlation — related
• GenAI literacy dimensions predict critical monitoring beyond traits, use frequency, and perceptions, with critical-ethical awareness the strongest predictor — related