Enterprise AI Analysis

OER Policy Direct Impact

The empirical findings reveal a pattern that challenges simplistic assumptions about the immediate transformative potential of open educational resource policies while simultaneously establishing important baseline evidence. The fixed effects specification for primary completion rates cannot estimate the direct OER policy coefficient due to collinearity with country-specific trends, a methodological limitation arising from the concentration of policy adoption near the observation endpoint.

The difference-in-differences analysis indicates that OER-adopting countries experienced completion rate increases averaging 0.52 percentage points relative to non-adopting countries in the post-2020 period, though this estimate remains statistically imprecise (p equals 0.440), preventing definitive causal conclusions. This pattern of suggestive but inconclusive findings reflects the temporal limitations of observing policies during early implementation rather than as evidence of policy ineffectiveness.

AI Readiness & Moderation

The more consistent finding across specifications concerns the role of artificial intelligence readiness as a predictor of educational outcomes and potential moderator of policy effectiveness. Countries with higher AI readiness scores demonstrate better performance on both primary completion rates and out-of-school rate reduction.

The findings reveal that AI readiness demonstrates consistent positive associations with educational outcomes, with a ten-point increase in the readiness index corresponding to approximately 0.46 percentage point improvements in primary completion rates and 0.31 percentage point reductions in out-of-school rates across fixed effects specifications. Interaction effects between policies and readiness yield consistently positive coefficients across specifications, but these associations similarly fail to achieve conventional significance thresholds given sample size constraints and limited within-country variation. While the directional patterns align with theoretical expectations that policy effectiveness depends on digital capacity, the evidence should be characterized as suggestive rather than conclusive.

Contextual Insights & Heterogeneity

Subsample analyses reveal meaningful heterogeneity in policy effects across country income groups. The interaction between AI readiness and OER policy shows stronger positive associations in high-income countries, achieving marginal statistical significance at the 0.10 level in some specifications. This pattern suggests that countries with greater economic resources and more developed institutional capacity realize larger benefits from open educational resource policies, consistent with the hypothesis of readiness-dependent scalability. In contrast, OER coefficients in low-income country subsamples remain close to zero, indicating minimal short-term effects in contexts with limited digital infrastructure and institutional capacity.