Mark dispersion narrowed in the treated half alone, with the Part 2 standard deviation falling from 7.09 to 5.03 while Part 1's was unchanged¶

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

Subclaims¶

q2 i? The Part 2 standard deviation fell from 7.09 to 5.03 (Brown–Forsythe p = 0.004) while the untreated Part 1 standard deviation moved from 4.32 to 4.67 (p = 0.873). → Dang 2026

Evidence¶

Dang 2026¶

Dang, C. T., & Nguyen, A. (2026). Verified, not generated: expert-verified AI study materials and the distribution of learning gains in a university course. https://arxiv.org/abs/2610.07097 doi:10.48550/arxiv.2610.07097

q2 · i? · causal · r2

Brown–Forsythe variance comparison in the distributional analysis of the same examination marks. The article adds that the treated half's interdecile range narrowed from 19.6 to 11.6 marks while the untreated half's widened from 10.0 to 11.6.

"The Part 2 standard deviation fell from 7.09 to 5.03 (Brown–Forsythe p = 0.004), while Part 1’s moved from 4.32 to 4.67 (p = 0.873)."

Discussion¶

Related Claims¶

• Access to expert-verified AI study materials is associated with a 2.34-mark difference-in-differences advantage on a 50-mark examination component, reflecting protection from a decline rather than a rise — related
• The share of marks below the upper-second classification boundary fell by 24.7 percentage points, with effects significant at every threshold from 23 to 31 marks and at none above — related
• Gains from verified AI materials are concentrated in the bottom quintile, which accounts for roughly three-quarters of the average effect — related