AI-related professional learning does not clearly moderate the within-teacher demand–AI allocation association¶

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 moderation test is not significant (F(1, 48) = 2.06, p = .157); equivalence was not tested. → Holster 2026

Evidence¶

Holster 2026¶

Holster, J. (2026). Where Artificial Intelligence Enters Teacher Work. https://www.oecd.org/en/data/datasets/talis-2024-database.html doi:10.35542/osf.io/a39rp_v1

q2 · i? · associational · r2

Secondary supplementary analysis testing professional learning as a moderator of the within-teacher allocation association; the article reports "F(1, 48) = 2.06, p = .157" with no effect size, and treats the result as secondary.

"AI-related professional learning did not clearly moderate the within-teacher allocation association in the revised sample, F(1, 48) = 2.06, p = .157."

Discussion¶

Related Claims¶

• Perceived AI literacy does not moderate the indirect warmth and competence pathways from GenAI use to trust — related
• Perceived AI literacy does not significantly moderate the direct association between AI dependence and self-reported creativity — related
• Perceived AI literacy moderates the direct path: the negative GenAI use–trust association is significant at low literacy and non-significant at high literacy — related
• The within-teacher demand–AI-use association differs sharply across tasks, with only a modest positive planning gradient — related
• Among AI-using teachers, tasks experienced as relatively more demanding are more likely to be AI-supported overall — related
• Overall demand–AI-use alignment varies modestly across education systems, but task-specific association profiles show clear residual heterogeneity — related