Pedagogical AI competence is positively associated with teachers' AI use¶

Claim · All claims
Evidence · 1 study (2 entries) · associational r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? In a cross-sectional SEM of 224 teachers, pedagogical AI competence was significantly associated with AI use (β = 0.45, p < .001). → Feng 2026 q2 i? The SEM model showed excellent fit and explained 62% of the variance in AI use and 46% of the variance in pedagogical AI competence. → Feng 2026 (2)

Evidence¶

Feng 2026¶

Feng, S., Koch, M. J., & Carolus, A. (2026). AI Mindset – An empirically tested theoretical framework on the psychological factors shaping AI competence and AI use. Computers in Human Behavior: Artificial Humans. https://doi.org/10.1016/j.chbah.2026.100402

q2 · i? · associational · r2

Cross-sectional mediation SEM (robust maximum likelihood, final n = 205) of survey data from Bavarian teachers. The results section reports that "AI use was significantly associated with pedagogical AI competence (β = 0.45, p < .001)", with competence modelled as a latent variable indicated by Intelligent-TPACK and TPACK ethics scores.

"AI use was significantly associated with pedagogical AI competence (β = 0.45, p < .001)."

Feng 2026 (2)¶

Feng, S., Koch, M. J., & Carolus, A. (2026). AI Mindset – An empirically tested theoretical framework on the psychological factors shaping AI competence and AI use. Computers in Human Behavior: Artificial Humans. https://doi.org/10.1016/j.chbah.2026.100402

q2 · i? · associational · r?

Fit and variance-explained results of the same mediation SEM. The results section reports the model showed excellent fit (CFI = 1.00, RMSEA = 0.00, SRMR = 0.02) and that "The model explained 62% of the variance in AI use and 46% of the variance in pedagogical AI competence."

"The model explained 62% of the variance in AI use and 46% of the variance in pedagogical AI competence."

Discussion¶

Related Claims¶

• Review reports that teachers' beliefs, attitudes and TPACK—not AI knowledge alone—mediate AI integration — the general claim this finding bears on, with the studies behind it

• Teachers' expectancy beliefs about successfully using AI applications shape their motivation to use them (theoretical argument). — the general claim this finding bears on, with the studies behind it

• AI-related fear shows a differentiated pattern: positive direct association with AI use but negative association with pedagogical AI competence and negative indirect effect — related
• In SEM, all three self-efficacy dimensions are positively associated with AI use, with Excellence strongest (β = .47), followed by Communication (β = .31) and Attention (β = .22); the model explains 43% of variance — related
• Effort expectancy is associated with AI use only indirectly through competence, whereas hedonic motivation shows a direct positive association — related
• Habit shows the strongest direct and competence-mediated associations with teachers' AI use — related